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O'Hare AM, Al-Aly Z. Variability in Estimated GFR: When the Signal Is the Noise. Am J Kidney Dis 2025; 85:676-678. [PMID: 40293385 DOI: 10.1053/j.ajkd.2025.03.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2025] [Accepted: 03/30/2025] [Indexed: 04/30/2025]
Affiliation(s)
- Ann M O'Hare
- VA Puget Sound Health Care System, Seattle, Washington; University of Washington, Seattle, Washington.
| | - Ziyad Al-Aly
- Clinical Epidemiology Center, Research and Development Service, VA Saint Louis Health Care System, Saint Louis, Missouri
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Calderon-Margalit R, Lev Bar-Or R, Afek A, Tzur D, Levin D, Ben-Ruby D, Furer A, Twig G, Skorecki K, Vivante A. Walking versus running and GFR trajectory in healthy young adults. PLoS One 2025; 20:e0323392. [PMID: 40440325 PMCID: PMC12121832 DOI: 10.1371/journal.pone.0323392] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2024] [Accepted: 04/08/2025] [Indexed: 06/02/2025] Open
Abstract
BACKGROUND The effect of physical activity on the primary prevention of chronic kidney disease (CKD) is unclear. We assessed walking and running as exercise behaviors and their associations with individual-level risk for kidney function decline. METHODS We conducted a historical cohort study in which we followed 20,976 young adults. Participants were interviewed periodically about their lifestyle, and clinical parameters were assessed. The decline in estimated glomerular filtration rate (eGFR) over time was divided into quartiles. Using logistic regressions, we estimated the odds ratio (OR) for being in the slowest declining quartile by consistency of running or walking. We also used Cox proportional hazards models to estimate the associations of physical activity with future eGFR < 90 ml/min/1.73m2. All models were adjusted for age, sex, smoking status, family history of kidney diseases, BMI, blood-pressure, baseline eGFR and serum cholesterol. RESULTS During 9.5 years of follow-up, the eGFR decreased by 0.97 ml/min/1.73m2 per year. Participants who reported in two consecutive questionnaires on walking as a leisure time activity had an OR of 1.21 (95% confidence interval: 1.03-1.41) to have slow eGFR decline compared to those who were physically inactive. Participants who predominantly reported on running as their physical activity were less likely to be slow eGFR decliners (OR:0.81, 95% CI:0.71-0.93). Similarly, consistent walking was associated with decreased risk for future eGFR < 90 ml/min/1.73m2 in contrast to consistent running which was associated with an increased risk for reduced eGFR. All associations showed dose dependent effects in terms of the number of weekly activity sessions. CONCLUSIONS Consistent walking, as opposed to consistent running, was associated with slower eGFR decline compared to inactive participants. These associations start already within the normal GFR range.
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Affiliation(s)
- Ronit Calderon-Margalit
- Braun School of Public Health, Hadassah Medical Organization, Faculty of Medicine, Hebrew University, Jerusalem, Israel
| | - Ruth Lev Bar-Or
- Braun School of Public Health, Hadassah Medical Organization, Faculty of Medicine, Hebrew University, Jerusalem, Israel
| | - Arnon Afek
- The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Ramat Gan, Israel
- The Dina Recanati School of Medicine, Reichman University, Herzliya, Israel
| | - Dorit Tzur
- Braun School of Public Health, Hadassah Medical Organization, Faculty of Medicine, Hebrew University, Jerusalem, Israel
| | | | - Dror Ben-Ruby
- Sheba Medical Center, Ramat Gan, Israel
- Faculty of Medical and Health Sciences, Tel-Aviv University, Tel-Aviv, Israel
| | - Ariel Furer
- Sheba Medical Center, Ramat Gan, Israel
- Department of Military Medicine, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem, Israel
| | - Gilad Twig
- The Gertner Institute for Epidemiology and Health Policy Research, Sheba Medical Center, Ramat Gan, Israel
- The Institute of Endocrinology, Diabetes and Metabolism, Sheba Medical Center, Ramat Gan, Israel
- Department of Epidemiology and Preventive Medicine, School of Public Health, Faculty of Medical and Health Sciences, Tel-Aviv University, Tel-Aviv, Israel
- Incumbent of the Hella Gertner Chair for Research in Hypertension, Faculty of Medical and Health Sciences, Tel-Aviv University, Tel-Aviv, Israel
| | - Karl Skorecki
- Department of Nephrology, Rambam Health Care Campus, Rappaport Faculty of Medicine and Research Institute, The Technion–Israel Institute of Technology, Haifa, Israel
- Bar-Ilan University Faculty of Medicine, Safed, Israel
| | - Asaf Vivante
- Faculty of Medical and Health Sciences, Tel-Aviv University, Tel-Aviv, Israel
- Pediatric Department B and Pediatric Nephrology Unit, Talpiot Medical Leadership Program, Edmond and Lily Safra Children’s Hospital, Faculty of Medical and Health Sciences Sheba Medical Center, Ramat Gan, Israel
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Yang EM, Kim J, Park E, Han KH, Kim SH, Cho H, Shin JI, Cho MH, Lee JH, Kim JH, Kang HG, Ha IS, Ahn YH. Longitudinal progression trajectory of estimated glomerular filtration rate in children with chronic kidney disease: results from the KNOW-Ped CKD (KoreaN cohort study for Outcomes in patients With Pediatric Chronic Kidney Disease). Kidney Res Clin Pract 2025; 44:376-388. [PMID: 38389150 PMCID: PMC11985292 DOI: 10.23876/j.krcp.23.198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Revised: 11/02/2023] [Accepted: 12/01/2023] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND The natural course of chronic kidney disease (CKD) progression in children varies according to their underlying conditions. This study aims to identify different patterns of subsequent decline in kidney function and investigate factors associated with different patterns of estimated glomerular filtration rate (eGFR) trajectories. METHODS We analyzed data from the KNOW-Ped CKD (KoreaN cohort study for Outcomes in patients With Pediatric Chronic Kidney Disease), which is a longitudinal, prospective cohort study. A latent class linear mixed model was applied to identify the trajectory groups. RESULTS In a total of 287 patients, the median baseline eGFR (mL/min/1.73 m2) was 63.3, and the median age was 11.5 years. The eGFR decline rate was -1.54 during a 6.0-year follow-up. The eGFR trajectory over time was classified into four groups. Classes 1 (n = 103) and 2 (n = 11) had a slightly reduced eGFR at enrollment with a stable trend (ΔeGFR, -0.2/year) and a rapid decline eGFR over time (ΔeGFR, -10.5/year), respectively. Class 3 had a normal eGFR (n = 16), and class 4 had a moderately reduced eGFR (n = 157); both these chasses showed a linear decline in eGFR over time (ΔeGFR, -4.1 and -2.4/year). In comparison with classes 1 and 2, after adjusting for age, causes of primary renal disease, and baseline eGFR, nephrotic-range proteinuria was associated with a rapid decline in eGFR (odds ratio, 8.13). CONCLUSION We identified four clinically relevant subgroups of kidney function trajectories in children with CKD. Most children showed a linear decline in eGFR; however, there are different patterns of eGFR trajectories.
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Grants
- (2011 E3300300, 2012E3301100, 2013E3301600, 2013E3301601, 2013E3301602, 2016E3300200, 2016E3300201, 2016E330 0202, 2019E320100, 2019E320101, 2019E320102, 2022- 11-007 Korea Disease Control and Prevention Agency
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Affiliation(s)
- Eun Mi Yang
- Department of Pediatrics, Chonnam National University Hospital, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Jayoun Kim
- Medical Research Collaborating Center, Seoul National University Hospital, Seoul, Republic of Korea
| | - Eujin Park
- Department of Pediatrics, Korea University Guro Hospital, Seoul, Republic of Korea
| | - Kyoung Hee Han
- Department of Pediatrics, College of Medicine, Jeju National University, Jeju, Republic of Korea
| | - Seong Heon Kim
- Department of Pediatrics, Seoul National University Children’s Hospital, Seoul, Republic of Korea
- Department of Pediatrics, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Heeyeon Cho
- Department of Pediatrics, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Jae Il Shin
- Department of Pediatrics, Yonsei University College of Medicine, Seoul, Republic of Korea
- Division of Pediatric Nephrology, Severance Children’s Hospital, Seoul, Republic of Korea
| | - Min Hyun Cho
- Department of Pediatrics, Kyungpook National University School of Medicine, Daegu, Republic of Korea
| | - Joo Hoon Lee
- Department of Pediatrics, Asan Medical Center Children’s Hospital, Ulsan University, College of Medicine, Seoul, Republic of Korea
| | - Ji Hyun Kim
- Department of Pediatrics, Seoul National University College of Medicine, Seoul, Republic of Korea
- Department of Pediatrics, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Hee Gyung Kang
- Department of Pediatrics, Seoul National University Children’s Hospital, Seoul, Republic of Korea
- Department of Pediatrics, Seoul National University College of Medicine, Seoul, Republic of Korea
- Kidney Research Institute, Medical Research Center, Seoul National University College of Medicine, Seoul, Republic of Korea
- Wide River Institute of Immunology, Seoul National University, Hongcheon, Republic of Korea
| | - Il-Soo Ha
- Department of Pediatrics, Seoul National University Children’s Hospital, Seoul, Republic of Korea
- Department of Pediatrics, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Yo Han Ahn
- Department of Pediatrics, Seoul National University Children’s Hospital, Seoul, Republic of Korea
- Department of Pediatrics, Seoul National University College of Medicine, Seoul, Republic of Korea
- Kidney Research Institute, Medical Research Center, Seoul National University College of Medicine, Seoul, Republic of Korea
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Zbib F, Deschamps A, Velly L, Blin O, Guilhaumou R, Gattacceca F. Physiologically Based Pharmacokinetic Model of Cefotaxime in Patients with Impaired Renal Function. Clin Pharmacokinet 2025; 64:257-273. [PMID: 39762592 DOI: 10.1007/s40262-024-01469-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/09/2024] [Indexed: 02/01/2025]
Abstract
BACKGROUND Cefotaxime is a widely prescribed cephalosporin antibiotic used to treat various infections. It is mainly eliminated unchanged by the kidney through tubular secretion and glomerular filtration. Therefore, a reduction of kidney function may increase exposure to the drug and induce toxic side effects. OBJECTIVES The objectives of this study were to develop a physiologically based pharmacokinetic (PBPK) model of cefotaxime in healthy European adults, to mechanistically describe the impact of chronic kidney disease (CKD) on cefotaxime pharmacokinetics, and to assess the applicability of the model to patients requiring intensive care. METHODS Using PK-Sim® software, we developed a PBPK model for cefotaxime, including basolateral and apical renal transporters and renal esterases, in healthy subjects and then extrapolated to patients with CKD by incorporating pathophysiological changes and reductions in activity of drug-metabolizing enzymes and transporters into the model. We then evaluated the predictive performance of the model in patients requiring intensive care using clinical routine data. RESULTS Model predictions were considered adequate in healthy subjects and patients with CKD, with predicted-to-observed area under the curve ratios within the two-fold acceptance criterion. Mean prediction error and mean absolute prediction error did not exceed ± 30 and 30%, respectively, except in patients with stage 4 CKD, where they were 70.5 and 75.6%, respectively. The model showed good predictive performance when applied to patients requiring intensive care, but its clinical applicability in this population needs to be further evaluated. CONCLUSION We successfully developed whole-body PBPK models to predict cefotaxime pharmacokinetics in different populations. These models represent an additional step toward improving personalized cefotaxime dosing regimens in vulnerable populations.
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Affiliation(s)
- Fatima Zbib
- Aix Marseille University, APHM, INSERM, Service de Pharmacologie Clinique et Pharmacosurveillance, INS Institute Neuroscience Syst, Marseille, France
| | - Anthéa Deschamps
- Aix Marseille University, APHM, INSERM, Service de Pharmacologie Clinique et Pharmacosurveillance, INS Institute Neuroscience Syst, Marseille, France
- Inria-Inserm COMPO Team, Centre Inria Sophia Antipolis-Méditerranée, CRCM, Inserm U1068-CNRS UMR7258-Aix-Marseille University UM105, Marseille, France
| | - Lionel Velly
- Aix Marseille University, APHM, Department of Anaesthesiology and Critical Care Medicine, University Hospital Timone, Marseille, France
- Aix Marseille University, CNRS, INT, Institute Neuroscience Timone, UMR7289, Marseille, France
| | - Olivier Blin
- Aix Marseille University, APHM, INSERM, Service de Pharmacologie Clinique et Pharmacosurveillance, INS Institute Neuroscience Syst, Marseille, France
| | - Romain Guilhaumou
- Aix Marseille University, APHM, INSERM, Service de Pharmacologie Clinique et Pharmacosurveillance, INS Institute Neuroscience Syst, Marseille, France.
| | - Florence Gattacceca
- Inria-Inserm COMPO Team, Centre Inria Sophia Antipolis-Méditerranée, CRCM, Inserm U1068-CNRS UMR7258-Aix-Marseille University UM105, Marseille, France
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Pérez-Segovia A, Cojuc-Konigsberg G, Reul-Linares E, Hernández-Paredes EN, Chapa-Ibargüengoitia M, Ramírez-Sandoval JC. Kidney Growth Progression Patterns in Autosomal Dominant Polycystic Kidney Disease. Arch Med Res 2025; 56:103099. [PMID: 39393160 DOI: 10.1016/j.arcmed.2024.103099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2024] [Revised: 08/13/2024] [Accepted: 09/25/2024] [Indexed: 10/13/2024]
Abstract
BACKGROUND Prognosis for autosomal dominant polycystic kidney disease (ADPKD), the main inherited cause of kidney failure, relies on estimating cystic growth using linear formulas derived from height-adjusted total kidney volume (Ht-TKV). However, nonlinear renal growth patterns may occur in typical ADPKD. AIMS To determine kidney outcomes of subjects diagnosed with typical ADPKD exhibiting nonlinear, and unpredictable cystic growth during follow-up. METHODS Retrospective cohort study. We categorized TKV changes in individuals with typical ADPKD according to observed kidney growth trajectories. Ht-TKV was calculated from consecutive CT or MRI using the ellipsoid method. We compared estimated glomerular filtration rate (eGFR) trajectories with linear mixed models. RESULTS We included 83 individuals with ADPKD (67% women; age 47 ± 12 years; follow-up 5.2 years [IQR 2.8-9.0]). Three kidney growth patterns were observed: slow progression (24%, <3%/year linear increase), fast progression (39%, ≥3%/year linear increase), and atypical progression (37%, nonlinear growth). Adjusted ht-TKV change in mL/m/year was +1.4 (IQR -4.5 to +10.0), +40.3 (+16.9 to +89.3), and +32.8 (+15.9 to +85.9) for slow, fast, and atypical progressors, respectively (p <0.001). Atypical progressors exhibited a significantly greater decline in eGFR in mL/min/m²/year (-7.9, 95% CI -6.5, -3.9) compared to slow (-0.5, 95% CI -3.1 to +0.5) and fast progressors (-3.4, 95% CI -7.9, -2.0; between-group p <0.001). Atypical progressors had a higher proportion of acute complications, including hemorrhages, infections, and urolithiasis (84%), compared to slow (20%) and fast progressors (31%) (p <0.001). CONCLUSION In typical ADPKD, nonlinear, abrupt, and unpredictable cyst growth occurs frequently, leading to a higher risk of acute complications and kidney function decline.
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Affiliation(s)
- Aaron Pérez-Segovia
- Department of Radiology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Gabriel Cojuc-Konigsberg
- Departament of Nephrology and Mineral Metabolism, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Estefania Reul-Linares
- Departament of Nephrology and Mineral Metabolism, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Elisa Naomi Hernández-Paredes
- Departament of Nephrology and Mineral Metabolism, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Mónica Chapa-Ibargüengoitia
- Department of Radiology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico
| | - Juan C Ramírez-Sandoval
- Department of Radiology, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Mexico City, Mexico.
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Christiadi D, Chai K, Chuah A, Loong B, Andrews TD, Chakera A, Walters GD, Jiang SHT. Dynamic survival prediction of end-stage kidney disease using random survival forests for competing risk analysis. Front Med (Lausanne) 2024; 11:1428073. [PMID: 39722823 PMCID: PMC11668785 DOI: 10.3389/fmed.2024.1428073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2024] [Accepted: 11/28/2024] [Indexed: 12/28/2024] Open
Abstract
Background and hypothesis A static predictive model relying solely on baseline clinicopathological data cannot capture the heterogeneity in predictor trajectories observed in the progression of chronic kidney disease (CKD). To address this, we developed and validated a dynamic survival prediction model using longitudinal clinicopathological data to predict end-stage kidney disease (ESKD), with death as a competing risk. Methods We trained a sequence of random survival forests using a landmarking approach and optimized the model with a pre-specified prediction horizon of 5 years. The predicted cumulative incidence function (CIF) values were used to generate a personalized dynamic prediction plot. Results The model was developed using baseline demographics and 13 longitudinal clinicopathological variables from 4,950 patients. Variable importance analysis for ESKD and death informed the creation of a sequence of reduced models that utilized six key variables: age, serum albumin, bicarbonate, chloride, eGFR, and hemoglobin. The models demonstrated robust predictive performance, with a median concordance index of 84.84% for ESKD and 84.1% for death. The median integrated Brier scores were 0.03 for ESKD and 0.038 for death across all landmark times. External validation with 8,729 patients confirmed these results. Conclusion We successfully developed and validated a dynamic survival prediction model using common longitudinal clinicopathological data. This model predicts ESKD with death as a competing risk and aims to assist clinicians in dialysis planning for patients with CKD.
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Affiliation(s)
- Daniel Christiadi
- Department of Immunology and Infectious Disease, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia
- Department of Renal Medicine, The Canberra Hospital, Garran, ACT, Australia
- Centre of Personalised Medicine, Australian National University and Canberra Health Services, Canberra, ACT, Australia
| | - Kevin Chai
- School of Population Health, Curtin University, Perth, WA, Australia
| | - Aaron Chuah
- Department of Immunology and Infectious Disease, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia
| | - Bronwyn Loong
- Research School of Finance, Actuarial Studies & Statistics, Australian National University, Canberra, ACT, Australia
| | - Thomas D. Andrews
- Department of Immunology and Infectious Disease, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia
| | - Aron Chakera
- Department of Renal Medicine, Sir Charles Gairdner Osborn Park Health Care Group, Nedlands, WA, Australia
| | - Giles Desmond Walters
- Department of Renal Medicine, The Canberra Hospital, Garran, ACT, Australia
- Centre of Personalised Medicine, Australian National University and Canberra Health Services, Canberra, ACT, Australia
- Australian National University Medical School, Garran, ACT, Australia
| | - Simon Hee-Tang Jiang
- Department of Immunology and Infectious Disease, John Curtin School of Medical Research, Australian National University, Canberra, ACT, Australia
- Department of Renal Medicine, The Canberra Hospital, Garran, ACT, Australia
- Centre of Personalised Medicine, Australian National University and Canberra Health Services, Canberra, ACT, Australia
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Ettleson MD, Penna GCE, Wan W, Benseñor IM, Laiteerapong N, Bianco AC. TSH Trajectories During Levothyroxine Treatment in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) Cohort. J Clin Endocrinol Metab 2024; 109:3065-3075. [PMID: 38780968 PMCID: PMC11570358 DOI: 10.1210/clinem/dgae294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Indexed: 05/25/2024]
Abstract
CONTEXT Thyroid-stimulating hormone (TSH) trajectory classification represents a novel approach to defining the adequacy of levothyroxine (LT4) treatment for hypothyroidism over time. OBJECTIVE This is a proof of principle study that uses longitudinal clinical data, including thyroid hormone levels from a large prospective study to define classes of TSH trajectories and examine changes in cardiovascular (CV) health markers over the study period. METHODS Growth mixture modeling (GMM), including latent class growth analysis (LCGA), was used to classify LT4-treated individuals participating in the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil) based on serial TSH levels. Repeated measure analyses were then utilized to assess within-class changes in blood pressure, lipid levels, hemoglobin A1c, and CV-related medication utilization. RESULTS From the 621 LT4-treated study participants, the best-fit GMM approach identified 4 TSH trajectory classes, as defined by their relationship to the normal TSH range: (1) high-high normal TSH, (2) normal TSH, (3) normal to low TSH, and (4) low to normal TSH. Notably, the average baseline LT4 dose was lowest in the high-high normal TSH group (77.7 µg, P < .001). There were no significant differences in CV health markers between the classes at baseline. At least 1 significant difference in CV markers occurred in all classes, highlighted by the low to normal class, in which total and high-density lipoprotein cholesterol, triglycerides, and A1c all increased significantly (P = .049, P < .001, P < .001, and P = .001, respectively). Utilization of antihypertensive, antihyperlipidemic, and antidiabetes medications increased in all classes. CONCLUSION GMM/LCGA represents a viable approach to define and examine LT4 treatment by TSH trajectory. More comprehensive datasets should allow for more complex trajectory modeling and analysis of clinical outcome differences between trajectory classes.
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Affiliation(s)
- Matthew D Ettleson
- Section of Endocrinology, Diabetes, and Metabolism, University of Chicago, Chicago, IL 60637, USA
| | - Gustavo C E Penna
- Section of Endocrinology, Diabetes, and Metabolism, University of Chicago, Chicago, IL 60637, USA
| | - Wen Wan
- Section of General Internal Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Isabela M Benseñor
- Center for Clinical and Epidemiological Research, Clinical Hospital, Department of Medicine, University of Sao Paulo, Sao Paulo, 05508-000, Brazil
| | - Neda Laiteerapong
- Section of General Internal Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Antonio C Bianco
- Section of Endocrinology, Diabetes, and Metabolism, University of Chicago, Chicago, IL 60637, USA
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Lee J, Liu JJ, Liu S, Liu A, Zheng H, Chan C, Shao YM, Gurung RL, Ang K, Lim SC. Acute kidney injury predicts the risk of adverse cardio renal events and all cause death in southeast Asian people with type 2 diabetes. Sci Rep 2024; 14:27027. [PMID: 39505973 PMCID: PMC11541721 DOI: 10.1038/s41598-024-77981-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Accepted: 10/28/2024] [Indexed: 11/08/2024] Open
Abstract
Patients with diabetes are susceptible to acute kidney injury (AKI) as compared to counterparts without diabetes. However, data on the long-term clinical outcome of AKI specifically in people with diabetes are still scarce. We sought to study risk factors for and adverse cardio-renal outcomes of AKI in multi-ethnic Southeast Asian people with type 2 diabetes. 1684 participants with type 2 diabetes from a regional hospital were followed an average of 4.2 (SD 2.0) years. Risks for end stage kidney disease (ESKD), major adverse cardiovascular events (MACE) and all-cause death after AKI were assessed by survival analyses. 219 participants experienced at least one AKI episode. Age, cardiovascular disease history, minor ethnicity, diuretics usage, HbA1c, baseline eGFR and albuminuria independently predicted risk for AKI with good discrimination. Compared to those without AKI, participants with any AKI episode had a significantly high risk for ESKD, MACE and all-cause death after adjustment for multiple risk factors including baseline eGFR and albuminuria. Even AKI defined by a mild serum creatinine elevation (0.3 mg/dL) was independently associated with a significantly high risk for premature death. Therefore, individuals with diabetes and any episode of AKI deserve intensive surveillance for cardio-renal dysfunction.
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Affiliation(s)
- Janus Lee
- Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, 768828, Singapore
| | - Jian-Jun Liu
- Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, 768828, Singapore
| | - Sylvia Liu
- Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, 768828, Singapore
| | - Allen Liu
- Department of Medicine, Khoo Teck Puat hospital, Singapore, 768828, Singapore
| | - Huili Zheng
- Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, 768828, Singapore
| | - Clara Chan
- Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, 768828, Singapore
| | - Yi Ming Shao
- Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, 768828, Singapore
| | - Resham L Gurung
- Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, 768828, Singapore
| | - Keven Ang
- Clinical Research Unit, Khoo Teck Puat Hospital, Singapore, 768828, Singapore
| | - Su Chi Lim
- Department of Medicine, Khoo Teck Puat hospital, Singapore, 768828, Singapore.
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117549, Singapore.
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore.
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Liu C, Yang L, Wei W, Fu P. Efficacy of probiotics/synbiotics supplementation in patients with chronic kidney disease: a systematic review and meta-analysis of randomized controlled trials. Front Nutr 2024; 11:1434613. [PMID: 39166132 PMCID: PMC11333927 DOI: 10.3389/fnut.2024.1434613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2024] [Accepted: 07/17/2024] [Indexed: 08/22/2024] Open
Abstract
Background Chronic kidney disease (CKD) is a serious and steadily growing health problem worldwide. Probiotic and synbiotic supplementation are expected to improve kidney function in CKD patients by altering imbalanced intestinal flora, regulating microbiota metabolites, modulating the brain-gut axis, and reducing inflammation. Objectives Our aim is to report the latest and largest pooled analyses and evidence updates to explore whether probiotic and synbiotic have beneficial effects on renal function and general conditions in patients with CKD. Methods We conducted a systematic literature search using PubMed, Embase, Web of Science, and the Cochrane Central Register of Controlled Trials from inception until 1 December 2023. Eligible literatures were screened according to inclusion and exclusion criteria, data were extracted, and a systematic review and meta-analysis was performed. Measurements included renal function-related markers, inflammatory markers, uremic toxins, lipid metabolism-related markers and electrolytes levels. Results Twenty-one studies were included. The results showed that probiotic/synbiotic significantly reduced blood urea nitrogen (BUN) (standardized mean difference (SMD), -0.23, 95% confidence interval (CI) -0.41, -0.04; p = 0.02, I2 = 10%) and lowered c-reactive protein level (CRP) (SMD: -0.34; 95% CI: -0.62, -0.07; p = 0.01, I2 = 37%) in CKD patients, compared with the control group. Conclusion In summary, probiotic/synbiotic supplementation seems to be effective in improving renal function indices and inflammation indices in CKD patients. Subgroup analyses suggested that longer-term supplementation is more favorable for CKD patients, but there is a high degree of heterogeneity in the results of partial subgroup analyses. The efficacy of probiotic/synbiotic in treating CKD needs to be supported by more evidence from large-scale clinical studies. Systematic review registration https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024526836, Unique identifier: CRD42024526836.
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Affiliation(s)
| | | | | | - Ping Fu
- Department of Nephrology, Institute of Kidney Diseases, West China Hospital of Sichuan University, Chengdu, China
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Lai J, Shan H, Cui S, Xiao L, Huang X, Xiao Y. Bioinformatics analysis reveals CCR7 as a potential biomarker for predicting CKD progression. Medicine (Baltimore) 2024; 103:e33705. [PMID: 39058890 PMCID: PMC11272288 DOI: 10.1097/md.0000000000033705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 04/14/2023] [Indexed: 07/28/2024] Open
Abstract
Chronic kidney disease (CKD) inevitably progresses to end-stage renal disease if intervention does not occur timely. However, there are limitations in predicting the progression of CKD by solely relying on changes in renal function. A biomarker with high sensitivity and specificity that can predict CKD progression early is required. We used the online Gene Expression Omnibus microarray dataset GSE45980 to identify differentially expressed genes (DEGs) in patients with progressive and stable CKD. We then performed functional enrichment and protein-protein interaction network analysis on DEGs and identified key genes. Finally, the expression patterns of key genes were verified using the GSE60860 dataset, and the receiver operating characteristic curve analysis was performed to clarify their predictive ability of progressive CKD. Ultimately, we verified the expression profiles of these hub genes in an in vitro renal interstitial fibrosis model by real-time PCR and western blot analysis. Differential expression analysis identified 50 upregulated genes and 47 downregulated genes. The results of the functional enrichment analysis revealed that upregulated DEGs were mainly enriched in immune response, inflammatory response, and NF-κB signaling pathways, whereas downregulated DEGs were mainly related to angiogenesis and the extracellular environment. Protein-protein interaction network and key gene analysis identified CCR7 as the most important gene. CCR7 mainly plays a role in immune response, and its only receptors, CCL19 and CCL21, have also been identified as DEGs. The receiver operating characteristic curve analysis of CCR7, CCL19, and CCL21 found that CCR7 and CCL19 present good disease prediction ability. CCR7 may be a stable biomarker for predicting CKD progression, and the CCR7-CCL19/CCL21 axis may be a therapeutic target for end-stage renal disease. However, further experiments are needed to explore the relationship between these genes and CKD.
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Affiliation(s)
- Junju Lai
- Division of Nephrology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Guangdong Key Laboratory of Urology, Division of Urology Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Division of Nephrology, Dongguan People’s Hospital, Dongguan, China
| | - Huizhi Shan
- Division of Nephrology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
- Guangdong Key Laboratory of Urology, Division of Urology Surgery, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Sini Cui
- Division of Nephrology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Lingfeng Xiao
- Division of Nephrology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Xiaowen Huang
- Division of Nephrology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Yun Xiao
- Division of Nephrology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
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11
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Lamb EJ, Barratt J, Brettell EA, Cockwell P, Dalton RN, Deeks JJ, Eaglestone G, Pellatt-Higgins T, Kalra PA, Khunti K, Loud FC, Ottridge RS, Potter A, Rowe C, Scandrett K, Sitch AJ, Stevens PE, Sharpe CC, Shinkins B, Smith A, Sutton AJ, Taal MW. Accuracy of glomerular filtration rate estimation using creatinine and cystatin C for identifying and monitoring moderate chronic kidney disease: the eGFR-C study. Health Technol Assess 2024; 28:1-169. [PMID: 39056437 PMCID: PMC11331378 DOI: 10.3310/hyhn1078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/28/2024] Open
Abstract
Background Estimation of glomerular filtration rate using equations based on creatinine is widely used to manage chronic kidney disease. In the UK, the Chronic Kidney Disease Epidemiology Collaboration creatinine equation is recommended. Other published equations using cystatin C, an alternative marker of kidney function, have not gained widespread clinical acceptance. Given higher cost of cystatin C, its clinical utility should be validated before widespread introduction into the NHS. Objectives Primary objectives were to: (1) compare accuracy of glomerular filtration rate equations at baseline and longitudinally in people with stage 3 chronic kidney disease, and test whether accuracy is affected by ethnicity, diabetes, albuminuria and other characteristics; (2) establish the reference change value for significant glomerular filtration rate changes; (3) model disease progression; and (4) explore comparative cost-effectiveness of kidney disease monitoring strategies. Design A longitudinal, prospective study was designed to: (1) assess accuracy of glomerular filtration rate equations at baseline (n = 1167) and their ability to detect change over 3 years (n = 875); (2) model disease progression predictors in 278 individuals who received additional measurements; (3) quantify glomerular filtration rate variability components (n = 20); and (4) develop a measurement model analysis to compare different monitoring strategy costs (n = 875). Setting Primary, secondary and tertiary care. Participants Adults (≥ 18 years) with stage 3 chronic kidney disease. Interventions Estimated glomerular filtration rate using the Chronic Kidney Disease Epidemiology Collaboration and Modification of Diet in Renal Disease equations. Main outcome measures Measured glomerular filtration rate was the reference against which estimating equations were compared with accuracy being expressed as P30 (percentage of values within 30% of reference) and progression (variously defined) studied as sensitivity/specificity. A regression model of disease progression was developed and differences for risk factors estimated. Biological variation components were measured and the reference change value calculated. Comparative costs of monitoring with different estimating equations modelled over 10 years were calculated. Results Accuracy (P30) of all equations was ≥ 89.5%: the combined creatinine-cystatin equation (94.9%) was superior (p < 0.001) to other equations. Within each equation, no differences in P30 were seen across categories of age, gender, diabetes, albuminuria, body mass index, kidney function level and ethnicity. All equations showed poor (< 63%) sensitivity for detecting patients showing kidney function decline crossing clinically significant thresholds (e.g. a 25% decline in function). Consequently, the additional cost of monitoring kidney function annually using a cystatin C-based equation could not be justified (incremental cost per patient over 10 years = £43.32). Modelling data showed association between higher albuminuria and faster decline in measured and creatinine-estimated glomerular filtration rate. Reference change values for measured glomerular filtration rate (%, positive/negative) were 21.5/-17.7, with lower reference change values for estimated glomerular filtration rate. Limitations Recruitment of people from South Asian and African-Caribbean backgrounds was below the study target. Future work Prospective studies of the value of cystatin C as a risk marker in chronic kidney disease should be undertaken. Conclusions Inclusion of cystatin C in glomerular filtration rate-estimating equations marginally improved accuracy but not detection of disease progression. Our data do not support cystatin C use for monitoring of glomerular filtration rate in stage 3 chronic kidney disease. Trial registration This trial is registered as ISRCTN42955626. Funding This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 11/103/01) and is published in full in Health Technology Assessment; Vol. 28, No. 35. See the NIHR Funding and Awards website for further award information.
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Affiliation(s)
- Edmund J Lamb
- Clinical Biochemistry, East Kent Hospitals University NHS Foundation Trust, Canterbury, UK
| | - Jonathan Barratt
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Elizabeth A Brettell
- Birmingham Clinical Trials Unit, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Paul Cockwell
- Renal Medicine, Queen Elizabeth Hospital Birmingham and Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK
| | - R Nei Dalton
- WellChild Laboratory, Evelina London Children's Hospital, St. Thomas' Hospital, London, UK
| | - Jon J Deeks
- Birmingham Clinical Trials Unit, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University of Birmingham and University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Gillian Eaglestone
- Kent Kidney Care Centre, East Kent Hospitals University NHS Foundation Trust, Kent, UK
| | | | - Philip A Kalra
- Department of Renal Medicine, Salford Royal Hospital Northern Care Alliance NHS Foundation Trust, Salford, UK
| | - Kamlesh Khunti
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | | | - Ryan S Ottridge
- Birmingham Clinical Trials Unit, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Aisling Potter
- Clinical Biochemistry, East Kent Hospitals University NHS Foundation Trust, Canterbury, UK
| | - Ceri Rowe
- Clinical Biochemistry, East Kent Hospitals University NHS Foundation Trust, Canterbury, UK
| | - Katie Scandrett
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
| | - Alice J Sitch
- Test Evaluation Research Group, Institute of Applied Health Research, University of Birmingham, Birmingham, UK
- NIHR Birmingham Biomedical Research Centre, University of Birmingham and University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
| | - Paul E Stevens
- Kent Kidney Care Centre, East Kent Hospitals University NHS Foundation Trust, Kent, UK
| | - Claire C Sharpe
- Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Bethany Shinkins
- Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
| | - Alison Smith
- Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
| | - Andrew J Sutton
- Academic Unit of Health Economics, Leeds Institute of Health Sciences, University of Leeds, Leeds, UK
| | - Maarten W Taal
- Department of Renal Medicine, University Hospitals of Derby and Burton NHS Foundation Trust, Derby, UK
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12
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Chen K, Abtahi F, Xu H, Fernandez-Llatas C, Carrero JJ, Seoane F. The Assessment of the Association of Proton Pump Inhibitor Usage with Chronic Kidney Disease Progression through a Process Mining Approach. Biomedicines 2024; 12:1362. [PMID: 38927569 PMCID: PMC11201399 DOI: 10.3390/biomedicines12061362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2024] [Revised: 06/12/2024] [Accepted: 06/13/2024] [Indexed: 06/28/2024] Open
Abstract
Previous studies have suggested an association between Proton Pump Inhibitors (PPIs) and the progression of chronic kidney disease (CKD). This study aims to assess the association between PPI use and CKD progression by analysing estimated glomerular filtration rate (eGFR) trajectories using a process mining approach. We conducted a retrospective cohort study from 1 January 2006 to 31 December 2011, utilising data from the Stockholm Creatinine Measurements (SCREAM). New users of PPIs and H2 blockers (H2Bs) with CKD (eGFR < 60) were identified using a new-user and active-comparator design. Process mining discovery is a technique that discovers patterns and sequences in events over time, making it suitable for studying longitudinal eGFR trajectories. We used this technique to construct eGFR trajectory models for both PPI and H2B users. Our analysis indicated that PPI users exhibited more complex and rapidly declining eGFR trajectories compared to H2B users, with a 75% increased risk (adjusted hazard ratio [HR] 1.75, 95% confidence interval [CI] 1.49 to 2.06) of transitioning from moderate eGFR stage (G3) to more severe stages (G4 or G5). These findings suggest that PPI use is associated with an increased risk of CKD progression, demonstrating the utility of process mining for longitudinal analysis in epidemiology, leading to an improved understanding of disease progression.
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Affiliation(s)
- Kaile Chen
- Department of Clinical Science, Intervention and Technology, Karolinska Institutet, 17177 Stockholm, Sweden; (F.A.); (C.F.-L.); (F.S.)
- Department of Biomedical Engineering and Health Systems, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 14157 Huddinge, Sweden
| | - Farhad Abtahi
- Department of Clinical Science, Intervention and Technology, Karolinska Institutet, 17177 Stockholm, Sweden; (F.A.); (C.F.-L.); (F.S.)
- Department of Biomedical Engineering and Health Systems, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, 14157 Huddinge, Sweden
- Department of Clinical Physiology, Karolinska University Hospital, 17176 Stockholm, Sweden
| | - Hong Xu
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society (NVS), Karolinska Institutet, 17177 Stockholm, Sweden;
| | - Carlos Fernandez-Llatas
- Department of Clinical Science, Intervention and Technology, Karolinska Institutet, 17177 Stockholm, Sweden; (F.A.); (C.F.-L.); (F.S.)
- Institute of Information and Communication Technologies (SABIEN-ITACA), Universitat Politècnica de València, Camino de Vera S/N, 46022 Valencia, Spain
| | - Juan-Jesus Carrero
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, 17177 Stockholm, Sweden;
| | - Fernando Seoane
- Department of Clinical Science, Intervention and Technology, Karolinska Institutet, 17177 Stockholm, Sweden; (F.A.); (C.F.-L.); (F.S.)
- Department of Clinical Physiology, Karolinska University Hospital, 17176 Stockholm, Sweden
- Department of Medical Technology, Karolinska University Hospital, 17176 Stockholm, Sweden
- Department of Textile Technology, University of Borås, 50190 Borås, Sweden
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13
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Ito J, Fukagawa M. Slope of the estimated glomerular filtration rate and its associated factors among individuals with chronic kidney disease in the general Japanese population. Clin Exp Nephrol 2024; 28:522-530. [PMID: 38340246 PMCID: PMC11116171 DOI: 10.1007/s10157-024-02466-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Accepted: 01/17/2024] [Indexed: 02/12/2024]
Abstract
BACKGROUND To suppress the incidence of end-stage kidney disease, we need to identify chronic kidney disease (CKD) patients with a high risk of rapid decline in the estimated glomerular filtration rate (eGFR). However, the current status of eGFR slope and its associated factors in the Japanese population have not been fully elucidated. METHODS Among examinees aged 40-70 years in the 2014 Specific Health Checkup conducted by the National Health Insurance in Kobe, Japan (n = 61,985), we prospectively observed 7291 examinees with CKD stage G3 from 2014 to 2018. RESULTS Until 2018, 4221 examinees continued to undergo annual SHCs for a total of five checkups per subject and had available records of all necessary data. The median eGFR change was -0.22 ml/min/1.73 m2/year. Only 9.2% of those subjects showed rapid eGFR decline (faster than -2.0 ml/min/1.73 m2/year). Logistic regression analysis identified diabetes, smoking habits, high urinary protein levels, older age, high systolic blood pressure, and low serum low-density lipoprotein cholesterol levels as independent predictors for rapid eGFR decline. Hemoglobin A1c levels did not contribute to the eGFR slope in CKD stage-G3 subjects with diabetes and proteinuria. CONCLUSION Most Japanese CKD stage-G3 subjects had a very slow decline in eGFR. A small proportion of CKD individuals who have a predictive factor of rapid eGFR decline should receive considerable attention from a nephrologist.
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Affiliation(s)
- Jun Ito
- Faculty of Nursing, Hyogo University, 2301, Hiraokacho-Shinzaike, Kakogawa, Hyogo, 675-0195, Japan.
- Division of Nephrology, School of Medicine, International University of Health and Welfare, 4-3, Kozunomori, Narita, Chiba, 286-8686, Japan.
- Division of Nephrology, Endocrinology and Metabolism, School of Medicine, Tokai University, 143, Shimokasuya, Isehara, Kanagawa, 259-1193, Japan.
| | - Masafumi Fukagawa
- Division of Nephrology, Endocrinology and Metabolism, School of Medicine, Tokai University, 143, Shimokasuya, Isehara, Kanagawa, 259-1193, Japan
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14
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Dos Santos Bitencourt A, Vargas Filho RL, da Silveira Prestes G, Rodrigues Uggioni ML, Marçal F, Colonetti T, da Rosa MI. Evaluation of N-acetyl-β-D-glucosaminidase as a prognostic marker for diabetic nephropathy in type 2 diabetics: systematic review and meta-analysis. Int Urol Nephrol 2024; 56:1651-1661. [PMID: 37898960 DOI: 10.1007/s11255-023-03843-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 10/08/2023] [Indexed: 10/31/2023]
Abstract
OBJECTIVE This review aimed to assess the utility of urinary N-acetyl-β-D-glucosaminidase (uNAG) as a prognostic biomarker for nephropathy in patients with type 2 diabetes mellitus. METHODS The search for relevant studies was conducted across multiple databases, including PubMed (Medline), EMBASE, LILACS, CENTRAL, IBECS, and gray literature. We employed a random effects model to calculate the standardized mean difference and 95% confidence interval. Furthermore, we assessed heterogeneity using Cochrane's Q test and Higgins' I2 statistics. RESULTS This review included a total of 16 articles involving 1669 patients, with 13 being case-control studies and three being cohorts. The meta-analysis conducted across all studies revealed significant heterogeneity. However, subgroup analysis of four studies indicated that an increase in uNAG among normoalbuminuric patients was associated with the development of macroalbuminuria (DMP = - 1.47; 95% CI = - 1.98 to 0.95; p < 0.00001; I2 = 45%). Conversely, it did not demonstrate effectiveness in predicting the development of microalbuminuria (DMP = 0.26; 95% CI = - 0.08 to 0.60; p = 0.13; I2 = 17%). CONCLUSIONS Elevated uNAG levels in normoalbuminuric patients may indicate an increased risk for the development of macroalbuminuria, but not microalbuminuria. However, the high heterogeneity observed among the studies highlights the necessity for further research to validate these findings.
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Affiliation(s)
| | - Régis Leães Vargas Filho
- Laboratory of Translational Biomedicine, University of Extremo Sul Catarinense, Criciúma, Santa Catarina, Brazil
| | - Gabriele da Silveira Prestes
- Laboratory of Translational Biomedicine, University of Extremo Sul Catarinense, Criciúma, Santa Catarina, Brazil
| | | | - Fernanda Marçal
- Laboratory of Translational Biomedicine, University of Extremo Sul Catarinense, Criciúma, Santa Catarina, Brazil
| | - Tamy Colonetti
- Laboratory of Translational Biomedicine, University of Extremo Sul Catarinense, Criciúma, Santa Catarina, Brazil
| | - Maria Inês da Rosa
- Laboratory of Translational Biomedicine, University of Extremo Sul Catarinense, Criciúma, Santa Catarina, Brazil.
- , Rua Cruz e Souza, 510, Bairro Pio Correa, Criciúma, SC, 88811-550, Brazil.
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15
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Carbayo J, Verdalles Ú, Díaz-Crespo F, Lázaro A, González-Nicolás M, Arroyo D, Blanco D, García-Gámiz M, Goicoechea M. Tubular biomarkers in proteinuric kidney disease: histology correlation and kidney prognosis of tubular biomarkers. Clin Kidney J 2024; 17:sfae146. [PMID: 38803396 PMCID: PMC11129590 DOI: 10.1093/ckj/sfae146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2024] [Indexed: 05/29/2024] Open
Abstract
Background Proteinuria is not only a biomarker of chronic kidney disease (CKD) but also a driver of CKD progression. The aim of this study was to evaluate serum and urinary tubular biomarkers in patients with biopsied proteinuric kidney disease and to correlate them with histology and kidney outcomes. Methods A single-center retrospective study was conducted on a cohort of 156 patients from January 2016 to December 2021. The following urinary and serum biomarkers were analyzed on the day of kidney biopsy: beta 2 microglobulin (β2-mcg), alpha 1 microglobulin (α1-mcg), neutrophil gelatinase-associated lipocalin (NGAL), urinary kidney injury molecule-1 (uKIM-1), monocyte chemoattractant protein-1 (MCP-1), urinary Dickkopf-3 (uDKK3), uromodulin (urinary uUMOD), serum kidney injury molecule-1 (sKIM-1) and serum uromodulin (sUMOD). A composite outcome of kidney progression or death was recorded during a median follow-up period of 26 months. Results Multivariate regression analysis identified sUMOD (β-0.357, P < .001) and uDKK3 (β 0.483, P < .001) as independent predictors of interstitial fibrosis, adjusted for age, estimated glomerular filtration rate (eGFR) and log proteinuria. Elevated levels of MCP-1 [odds ratio 15.61, 95% confidence interval (CI) 3.52-69.20] were associated with a higher risk of cortical interstitial inflammation >10% adjusted for eGFR, log proteinuria and microhematuria. Upper tertiles of uDKK3 were associated with greater eGFR decline during follow-up. Although not a predictor of the composite outcome, doubling of uDKK3 was a predictor of kidney events (hazard ratio 2.26, 95% CI 1.04-4.94) after adjustment for interstitial fibrosis, eGFR and proteinuria. Conclusions Tubular markers may have prognostic value in proteinuric kidney disease, correlating with specific histologic parameters and identifying cases at higher risk of CKD progression.
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Affiliation(s)
- Javier Carbayo
- Department of Nephrology, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Úrsula Verdalles
- Department of Nephrology, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Francisco Díaz-Crespo
- Department of Pathology, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Alberto Lázaro
- Renal Pathophysiology Laboratory, Instituto Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | - Marian González-Nicolás
- Renal Pathophysiology Laboratory, Instituto Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | - David Arroyo
- Department of Nephrology, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - David Blanco
- Renal Pathophysiology Laboratory, Instituto Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | - Mercedes García-Gámiz
- Department of Biochemistry, Hospital General Universitario Gregorio Marañón, Madrid, Spain
| | - Marian Goicoechea
- Department of Nephrology, Hospital General Universitario Gregorio Marañón, Madrid, Spain
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Chang TH, Chen YD, Lu HHS, Wu JL, Mak K, Yu CS. Specific patterns and potential risk factors to predict 3-year risk of death among non-cancer patients with advanced chronic kidney disease by machine learning. Medicine (Baltimore) 2024; 103:e37112. [PMID: 38363886 PMCID: PMC10869094 DOI: 10.1097/md.0000000000037112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 01/09/2024] [Indexed: 02/18/2024] Open
Abstract
Chronic kidney disease (CKD) is a major public health concern. But there are limited machine learning studies on non-cancer patients with advanced CKD, and the results of machine learning studies on cancer patients with CKD may not apply directly on non-cancer patients. We aimed to conduct a comprehensive investigation of risk factors for a 3-year risk of death among non-cancer advanced CKD patients with an estimated glomerular filtration rate < 60.0 mL/min/1.73m2 by several machine learning algorithms. In this retrospective cohort study, we collected data from in-hospital and emergency care patients from 2 hospitals in Taiwan from 2009 to 2019, including their international classification of disease at admission and laboratory data from the hospital's electronic medical records (EMRs). Several machine learning algorithms were used to analyze the potential impact and degree of influence of each factor on mortality and survival. Data from 2 hospitals in northern Taiwan were collected with 6565 enrolled patients. After data cleaning, 26 risk factors and approximately 3887 advanced CKD patients from Shuang Ho Hospital were used as the training set. The validation set contained 2299 patients from Taipei Medical University Hospital. Predictive variables, such as albumin, PT-INR, and age, were the top 3 significant risk factors with paramount influence on mortality prediction. In the receiver operating characteristic curve, the random forest had the highest values for accuracy above 0.80. MLP, and Adaboost had better performance on sensitivity and F1-score compared to other methods. Additionally, SVM with linear kernel function had the highest specificity of 0.9983, while its sensitivity and F1-score were poor. Logistic regression had the best performance, with an area under the curve of 0.8527. Evaluating Taiwanese advanced CKD patients' EMRs could provide physicians with a good approximation of the patients' 3-year risk of death by machine learning algorithms.
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Affiliation(s)
- Tzu-Hao Chang
- Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
- Clinical Big Data Research Center, Taipei Medical University Hospital, Taipei, Taiwan
| | - Yu-Da Chen
- Department of Family Medicine, Taipei Medical University Hospital, Taipei, Taiwan
- School of Health Care Administration, College of Management, Taipei Medical University, Taipei, Taiwan
- Department of Family Medicine, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Henry Horng-Shing Lu
- Institute of Statistics, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
- Institute of Data Science and Engineering, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Jenny L. Wu
- Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
| | | | - Cheng-Sheng Yu
- Graduate Institute of Data Science, College of Management, Taipei Medical University, Taipei, Taiwan
- Clinical Data Center, Office of Data Science, Taipei Medical University, Taipei, Taiwan
- Fintech RD Center, Nan Shan Life Insurance Co., Ltd
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17
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Al Dhaybi O, Bakris GL. Albuminuria is Your Guide to Assessing Future GFR Slope. Kidney Int Rep 2024; 9:194-196. [PMID: 38344724 PMCID: PMC10851060 DOI: 10.1016/j.ekir.2023.11.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2024] Open
Affiliation(s)
- Omar Al Dhaybi
- Department of Medicine, University of Chicago Medicine, Chicago, Illinois, USA
| | - George L. Bakris
- Department of Medicine, University of Chicago Medicine, Chicago, Illinois, USA
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18
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Jørgensen IF, Muse VP, Aguayo-Orozco A, Brunak S, Sørensen SS. Stratification of Kidney Transplant Recipients Into Five Subgroups Based on Temporal Disease Trajectories. Transplant Direct 2024; 10:e1576. [PMID: 38274475 PMCID: PMC10810574 DOI: 10.1097/txd.0000000000001576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 11/02/2023] [Accepted: 11/28/2023] [Indexed: 01/27/2024] Open
Abstract
Background Kidney transplantation is the treatment of choice for patients with end-stage renal disease. Considerable clinical research has focused on improving graft survival and an increasing number of kidney recipients die with a functioning graft. There is a need to improve patient survival and to better understand the individualized risk of comorbidities and complications. Here, we developed a method to stratify recipients into similar subgroups based on previous comorbidities and subsequently identify complications and for a subpopulation, laboratory test values associated with survival. Methods First, we identified significant disease patterns based on all hospital diagnoses from the Danish National Patient Registry for 5752 kidney transplant recipients from 1977 to 2018. Using hierarchical clustering, these longitudinal patterns of diseases segregate into 3 main clusters of glomerulonephritis, hypertension, and diabetes. As some recipients are diagnosed with diseases from >1 cluster, recipients are further stratified into 5 more fine-grained trajectory subgroups for which survival, stratified complication patterns as well as laboratory test values are analyzed. Results The study replicated known associations indicating that diabetes and low levels of albumin are associated with worse survival when investigating all recipients. However, stratification of recipients by trajectory subgroup showed additional associations. For recipients with glomerulonephritis, higher levels of basophils are significantly associated with poor survival, and these patients are more often diagnosed with bacterial infections. Additional associations were also found. Conclusions This study demonstrates that disease trajectories can confirm known comorbidities and furthermore stratify kidney transplant recipients into clinical subgroups in which we can characterize stratified risk factors. We hope to motivate future studies to stratify recipients into more fine-grained, homogenous subgroups to better discover associations relevant for the individual patient and thereby enable more personalized disease-management and improve long-term outcomes and survival.
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Affiliation(s)
- Isabella F. Jørgensen
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen N, Denmark
| | - Victorine P. Muse
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen N, Denmark
| | - Alejandro Aguayo-Orozco
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen N, Denmark
| | - Søren Brunak
- Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen N, Denmark
| | - Søren S. Sørensen
- Department of Nephrology, Rigshospitalet, Copenhagen University Hospital, Copenhagen Ø, Denmark
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Palomo-Piñón S, Enciso-Muñoz JM, Meaney E, Díaz-Domínguez E, Cardona-Muller D, Pérez FP, Cantoral-Farfán E, Anda-Garay JC, Mijangos-Chavez J, Antonio-Villa NE. Strategies to prevent, diagnose and treat kidney disease related to systemic arterial hypertension: a narrative review from the Mexican Group of Experts on Arterial Hypertension. BMC Nephrol 2024; 25:24. [PMID: 38238661 PMCID: PMC10797813 DOI: 10.1186/s12882-023-03450-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 12/27/2023] [Indexed: 01/22/2024] Open
Abstract
This narrative review highlights strategies proposed by the Mexican Group of Experts on Arterial Hypertension endorsed to prevent, diagnose, and treat chronic kidney disease (CKD) related to systemic arterial hypertension (SAH). Given the growing prevalence of CKD in Mexico and Latin America caused by SAH, there is a need for context-specific approaches to address the effects of SAH, given the diverse population and unique challenges faced by the region. This narrative review provides clinical strategies for healthcare providers on preventing, diagnosing, and treating kidney disease related to SAH, focusing on primary prevention, early detection, evidence-based diagnostic approaches, and selecting pharmacological treatments. Key-strategies are focused on six fundamental areas: 1) Strategies to mitigate kidney disease in SAH, 2) early detection of CKD in SAH, 3) diagnosis and monitoring of SAH, 4) blood pressure targets in patients living with CKD, 5) hypertensive treatment in patients with CKD and 6) diuretics and Non-Steroidal Mineralocorticoid Receptor Inhibitors in Patients with CKD. This review aims to provide relevant strategies for the Mexican and Latin American clinical context, highlight the importance of a multidisciplinary approach to managing SAH, and the role of community-based programs in improving the quality of life for affected individuals. This position paper seeks to contribute to reducing the burden of SAH-related CKD and its complications in Mexico and Latin America.
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Affiliation(s)
- Silvia Palomo-Piñón
- Grupo de Expertos en Hipertensión Arterial México (GREHTA), Ciudad de México, México.
- Colaborador Externo, Unidad de Investigación Médica en Enfermedades Nefrológicas Siglo XXI (UIMENSXII), UMAE Hospital de Especialidades "Dr. Bernardo Sepúlveda G" Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Ciudad de México, México.
- Grupo Colaborativo en Hipertensión Arterial (GCHTA), Ciudad de México, México.
- Grupo de Expertos en Hipertensión Arterial México (GREHTA), Calle Retorno del Escorial #13, Col. El Dorado, Tlanepantla de Baz, Estado de México, 54020, México.
| | - José Manuel Enciso-Muñoz
- Grupo de Expertos en Hipertensión Arterial México (GREHTA), Ciudad de México, México
- Asociación Mexicana para la Prevención de la Aterosclerosis y sus Complicaciones A.C, Ciudad de México, México
| | - Eduardo Meaney
- Grupo de Expertos en Hipertensión Arterial México (GREHTA), Ciudad de México, México
- Escuela Superior de Medicina, Instituto Politecnico Nacional, Ciudad de México, México
| | - Ernesto Díaz-Domínguez
- Grupo de Expertos en Hipertensión Arterial México (GREHTA), Ciudad de México, México
- UMAE Hospital de Cardiología, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Ciudad de México, México
| | - David Cardona-Muller
- Grupo de Expertos en Hipertensión Arterial México (GREHTA), Ciudad de México, México
- Universidad de Guadalajara, Guadalajara, Jalisco, México
| | - Fabiola Pazos Pérez
- Grupo de Expertos en Hipertensión Arterial México (GREHTA), Ciudad de México, México
- UMAE Hospital de Especialidades "Dr. Bernardo Sepúlveda G" Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Ciudad de México, México
| | - Emilia Cantoral-Farfán
- Grupo de Expertos en Hipertensión Arterial México (GREHTA), Ciudad de México, México
- Jefatura de Nefrología, Hospital General De Zona Médico Familiar No. 8 Gilberto Flores Izquierdo, Instituto Mexicano del Seguro Social, Ciudad de México, México
| | - Juan Carlos Anda-Garay
- Grupo de Expertos en Hipertensión Arterial México (GREHTA), Ciudad de México, México
- UMAE Hospital de Especialidades "Dr. Bernardo Sepúlveda G" Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Ciudad de México, México
| | - Janet Mijangos-Chavez
- Grupo de Expertos en Hipertensión Arterial México (GREHTA), Ciudad de México, México
- Jefatura de Cardiología, UMAE Dr. Antonio Fraga Mouret, Centro Médico Nacional La Raza, Instituto Mexicano del Seguro Social, Ciudad de México, México
| | - Neftali Eduardo Antonio-Villa
- Grupo de Expertos en Hipertensión Arterial México (GREHTA), Ciudad de México, México
- Departamento de Endocrinologia, Instituto Nacional de Cardiología Ignacio Chávez, Ciudad de México, México
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Rahamimov R, Agur T, Zingerman B, Bielopolski D, Steinmetz T, Nesher E, Hanniel I, Rozen-Zvi B. Multi-phasic eGFR trajectory during follow up and long-term graft failure after kidney transplantation. Clin Transplant 2023; 37:e15129. [PMID: 37742094 DOI: 10.1111/ctr.15129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Revised: 08/25/2023] [Accepted: 09/01/2023] [Indexed: 09/25/2023]
Abstract
BACKGROUND The prevailing assumption is that following kidney transplantation the pattern of kidney function decline is consistent. Nevertheless, numerous factors leading to graft loss may emerge, altering the trajectory of kidney function. In this study, we aim to assess alterations in estimated glomerular filtration rate (eGFR) trajectory over an extended period of follow-up and examine its correlation with graft survival. METHODS We calculated eGFR using all creatinine values available from 1-year post transplantation to the end of follow-up. For pattern analysis, we used a piecewise linear model. RESULTS Nine hundred eighty-eight patients were included in the study. After a median follow-up of 5.2 years, 297 (30.1%) patients had a multi-phasic eGFR trajectory. Change in eGFR trajectory was associated with increased risk for graft failure (HR 7.15, 95% CI 5.17-9.89, p < .001), longer follow-up time, younger age, longer cold ischemia time, high prevalence of acute rejection, longer hospitalization and a lower initial eGFR. Of the 988 patients included in the study, 494 (50.0%) had a mono-phasic stable trajectory, 197 (19.9%) had a mono-phasic decreasing trajectory, 184 (18.6%) had bi-phasic decreasing trajectory (initial stability and then decline, 46(4.7%) had a bi-phasic stabilized (initial decline and then stabilization) and 67(6.8%) had a more complex trajectory (tri-phasic). Out of the total 144 patients who experienced graft loss, the predominant pattern was a bi-phasic decline characterized by a bi-linear trajectory (66 events, 45.8%). CONCLUSIONS Changes in eGFR trajectory during long-term follow-up can serve as a valuable tool for assessing the underlying mechanisms contributing to graft loss.
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Affiliation(s)
- Ruth Rahamimov
- Department of Nephrology and Hypertension, Rabin Medical Center, Beilinson Campus, Petah-Tikva, Israel
- Department of Transplantation, Rabin Medical Center, Beilinson Campus, Petah-Tikva, Israel
- Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Timna Agur
- Department of Nephrology and Hypertension, Rabin Medical Center, Beilinson Campus, Petah-Tikva, Israel
- Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Boris Zingerman
- Department of Nephrology and Hypertension, Rabin Medical Center, Beilinson Campus, Petah-Tikva, Israel
- Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Dana Bielopolski
- Department of Nephrology and Hypertension, Rabin Medical Center, Beilinson Campus, Petah-Tikva, Israel
- Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Tali Steinmetz
- Department of Nephrology and Hypertension, Rabin Medical Center, Beilinson Campus, Petah-Tikva, Israel
- Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Eviatar Nesher
- Department of Transplantation, Rabin Medical Center, Beilinson Campus, Petah-Tikva, Israel
- Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Iddo Hanniel
- MobilEye Vision Technologies INC, Petah-Tikva, Israel
| | - Benaya Rozen-Zvi
- Department of Nephrology and Hypertension, Rabin Medical Center, Beilinson Campus, Petah-Tikva, Israel
- Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
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21
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Hsu RK, Rubinsky AD, Shlipak MG, Johansen KL, Estrella MM, Lee BJ, Peralta CA, Hsu CY. Associations between abrupt transition, dialysis-requiring AKI, and early mortality in ESKD among U.S. veterans. BMC Nephrol 2023; 24:339. [PMID: 37964185 PMCID: PMC10647139 DOI: 10.1186/s12882-023-03387-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 11/03/2023] [Indexed: 11/16/2023] Open
Abstract
BACKGROUND Mortality is high within the first few months of starting chronic dialysis. Pre-ESKD trajectory of kidney function has been shown to be predictive of early death after dialysis initiation. We aim to better understand how two key aspects of pre-dialysis kidney function-an abrupt transition pattern and an episode of dialysis-requiring AKI (AKI-D) leading directly to ESKD-are associated with early mortality after dialysis initiation. METHODS We extracted national data from U.S. Veterans Health Administration cross-linked with the United States Renal Data System (USRDS) to identify patients who initiated hemodialysis during 2009-2013. We defined abrupt transition as having a mean outpatient eGFR ≥ 30 ml/min/1.73m2 within 1 year prior to ESKD. AKI-D was identified using inpatient serum creatinine measurements (serum Cr increase by at least 50% from baseline) along with billing codes for inpatient receipt of dialysis for AKI within 30 days prior to the ESKD start date. We used multivariable proportional hazards models to examine the association between patterns of kidney function prior to ESKD and all-cause mortality within 90 days after ESKD. RESULTS Twenty-two thousand eight hundred fifteen patients were identified in the final analytic cohort of Veterans who initiated hemodialysis and entered the USRDS. We defined five patterns of kidney function decline. Most (68%) patients (N = 15,484) did not have abrupt transition and did not suffer an episode of AKI-D prior to ESKD (reference group). The remaining groups had abrupt transition, AKI-D, or both. Patients who had an abrupt transition with (N = 503) or without (N = 3611) AKI-D had the highest risk of early mortality after ESKD onset after adjustment for demographics and comorbidities (adjusted HR 2.10, 95% CI 1.66-2.65 for abrupt transition with AKI-D; adjusted HR 2.10, 95% CI 1.90-2.33 for abrupt transition without AKI-D). In contrast, patients who experienced AKI-D without an abrupt transition pattern (N = 2141 had only a modestly higher risk of early death (adjusted HR 1.19, 95% CI 1.01-1.40). CONCLUSIONS An abrupt decline in kidney function within 1 year prior to ESKD occurred in nearly 1 in 5 incident hemodialysis patients (18%) in this national cohort of Veterans and was strongly associated with higher early mortality after ESKD onset.
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Affiliation(s)
- Raymond K Hsu
- Division of Nephrology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
| | - Anna D Rubinsky
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Michael G Shlipak
- Department of Medicine, Kidney Health Research Collaborative, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
| | - Kirsten L Johansen
- Chronic Disease Research Group, Hennepin Healthcare Research Institute, Minneapolis, MN, USA
- Division of Nephrology, Hennepin Healthcare, Minneapolis, MN, USA
| | - Michelle M Estrella
- Division of Nephrology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Department of Medicine, Kidney Health Research Collaborative, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
| | - Benjamin J Lee
- Houston Methodist Institute for Academic Medicine, Houston, TX, USA
- Houston Kidney Consultants, Houston, TX, USA
| | - Carmen A Peralta
- Division of Nephrology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Department of Medicine, Kidney Health Research Collaborative, San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
- Cricket Health, Inc, San Francisco, CA, USA
| | - Chi-Yuan Hsu
- Division of Nephrology, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
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Zheng S, Parikh RV, Tan TC, Pravoverov L, Patel JK, Horiuchi KM, Go AS. CKD stage-specific utility of two equations for predicting 1-year risk of ESKD. PLoS One 2023; 18:e0293293. [PMID: 37910454 PMCID: PMC10619781 DOI: 10.1371/journal.pone.0293293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Accepted: 10/09/2023] [Indexed: 11/03/2023] Open
Abstract
BACKGROUND The Kidney Failure Risk Equation (KFRE) and Kaiser Permanente Northwest (KPNW) models have been proposed to predict progression to ESKD among adults with CKD within 2 and 5 years. We evaluated the utility of these equations to predict the 1-year risk of ESKD in a contemporary, ethnically diverse CKD population. METHODS We conducted a retrospective cohort study of adult members of Kaiser Permanente Northern California (KPNC) with CKD Stages 3-5 from January 2008-September 2015. We ascertained the onset of ESKD through September 2016, and calculated stage-specific estimates of model discrimination and calibration for the KFRE and KPNW equations. RESULTS We identified 108,091 eligible adults with CKD (98,757 CKD Stage 3; 8,384 CKD Stage 4; and 950 CKD Stage 5 not yet receiving kidney replacement therapy), with mean age of 75 years, 55% women, and 37% being non-white. The overall 1-year risk of ESKD was 0.8% (95%CI: 0.8-0.9%). The KFRE displayed only moderate discrimination for CKD 3 and 5 (c = 0.76) but excellent discrimination for CKD 4 (c = 0.86), with good calibration for CKD 3-4 patients but suboptimal calibration for CKD 5. Calibration by CKD stage was similar to KFRE for the KPNW equation but displayed worse calibration across CKD stages for 1-year ESKD prediction. CONCLUSIONS In a large, ethnically diverse, community-based CKD 3-5 population, both the KFRE and KPNW equation were suboptimal in accurately predicting the 1-year risk of ESKD within CKD stage 3 and 5, but more accurate for stage 4. Our findings suggest these equations can be used in1-year prediction for CKD 4 patients, but also highlight the need for more personalized, stage-specific equations that predicted various short- and long-term adverse outcomes to better inform overall decision-making.
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Affiliation(s)
- Sijie Zheng
- Department of Nephrology, Kaiser Permanente Oakland Medical Center, Oakland, California, United States of America
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
- Department of Medicine, University of California, San Francisco, San Francisco, California, United States of America
| | - Rishi V. Parikh
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
| | - Thida C. Tan
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
| | - Leonid Pravoverov
- Department of Nephrology, Kaiser Permanente Oakland Medical Center, Oakland, California, United States of America
| | - Jignesh K. Patel
- Department of Nephrology, Kaiser Permanente Sacramento Medical Center, Sacramento, California, United States of America
| | - Kate M. Horiuchi
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
| | - Alan S. Go
- Division of Research, Kaiser Permanente Northern California, Oakland, California, United States of America
- Department of Health Systems Science, Kaiser Permanente Bernard J. Tyson School of Medicine, Pasadena, California, United States of America
- Departments of Epidemiology, Biostatistics and Medicine, University of California, San Francisco, San Francisco, California, United States of America
- Department of Medicine, Stanford University School of Medicine, Stanford, California, United States of America
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23
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Rashid I, Tiwari P, Cruz SD, Jaswal S. Rates and determinants of fast chronic kidney disease progression distinguished by nutritional status, and the impact of malnutrition on mortality - evidence from a clinical population. Clin Nutr ESPEN 2023; 57:683-690. [PMID: 37739723 DOI: 10.1016/j.clnesp.2023.08.008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2023] [Revised: 07/07/2023] [Accepted: 08/05/2023] [Indexed: 09/24/2023]
Abstract
BACKGROUND & AIMS Malnutrition is a serious problem that influences morbidity, mortality, functional activity, and quality of life in patients with chronic kidney disease (CKD). However, there has not been much research done on how nutritional status appears to affect mortality in non-dialysis CKD patients. This study aimed to recognize the rates and predictors of fast CKD progression distinguished by nutritional status, and also sought to determine the impact of malnutrition on mortality in non-dialysis CKD patients. METHODS This prospective cohort study (n = 360) involved non-dialysis CKD patients with index estimated glomerular filtration rate (eGFR) between the range of 15-89 ml/min/1.73 m2. Nutritional status was evaluated by using the "Pt-Global web tool/PG-SGA". A loss of eGFR >4 ml/min/1.73 m2 per year was considered to be a sign of fast CKD progression. Kaplan-Meier plots were used to evaluate the cumulative survival, and Cox-proportional hazard models were used to analyze the renal outcomes. RESULTS Around 244 (67.8%) of patients have experienced a fast decline in kidney function. In the malnourished group, systolic blood pressure and hyperphosphatemia were observed to have increased hazards for fast CKD progression. The overall incidence of mortality and composite endpoints were found to be 13.9% & 37.6%, respectively. Death rates (11.6%) and composite endpoints (29.8%) were higher in the malnourished (severe & moderate) group. Cox regression hazard model reported 4 times increased hazards for death [HR 4.41 (1.99-9.77) 95% CI; P ≤ 0.005] and 3 times increased hazards for composite endpoints [HR 3.29 (2.10-5.16) 95% CI; P ≤ 0.005] for 'severely malnourished' category in reference to 'normal nutrition' category. CONCLUSIONS Fast CKD progression was observed to be more common in malnourished patients. Systolic blood pressure and hyperphosphatemia were recognized as potential predictors of fast CKD progression. Moreover, malnutrition was found to be a significant predictor of mortality among non-dialysis CKD patients. The findings of this study advocate for early nutritional evaluation and timely dietary interventions to halt the progression of CKD.
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Affiliation(s)
- Ishfaq Rashid
- National Institute of Pharmaceutical Education and Research (NIPER), S.A.S. Nagar, Punjab, 160062, India; M.M. College of Pharmacy, M.M. University Ambala, 133203, India.
| | - Pramil Tiwari
- Department of Pharmacy Practice, National Institute of Pharmaceutical Education and Research (NIPER), S.A.S. Nagar, Punjab, 160062, India.
| | - Sanjay D Cruz
- Department of General Medicine, Government Medical College and Hospital (GMCH), Chandigarh, 160030, India.
| | - Shivani Jaswal
- Department of Biochemistry, Government Medical College and Hospital (GMCH), Chandigarh, 160030, India.
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Kosinski L, Frey E, Klein A, O'Doherty I, Romero K, Stegall M, Helanterä I, Gaber AO, Fitzsimmons WE, Aggarwal V, Transplant Therapeutics Consortium (TTC). Longitudinal estimated glomerular filtration rate (eGFR) modeling in long-term renal function to inform clinical trial design in kidney transplantation. Clin Transl Sci 2023; 16:1680-1690. [PMID: 37350196 PMCID: PMC10499426 DOI: 10.1111/cts.13579] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 06/10/2023] [Indexed: 06/24/2023] Open
Abstract
Kidney transplantation is the preferred treatment for individuals with end-stage kidney disease. From a modeling perspective, our understanding of kidney function trajectories after transplantation remains limited. Current modeling of kidney function post-transplantation is focused on linear slopes or percent decline and often excludes the highly variable early timepoints post-transplantation, where kidney function recovers and then stabilizes. Using estimated glomerular filtration rate (eGFR), a well-known biomarker of kidney function, from an aggregated dataset of 4904 kidney transplant patients including both observational studies and clinical trials, we developed a longitudinal model of kidney function trajectories from time of transplant to 6 years post-transplant. Our model is a nonlinear, mixed-effects model built in NONMEM that captured both the recovery phase after kidney transplantation, where the graft recovers function, and the long-term phase of stabilization and slow decline. Model fit was assessed using diagnostic plots and individual fits. Model performance, assessed via visual predictive checks, suggests accurate model predictions of eGFR at the median and lower 95% quantiles of eGFR, ranges which are of critical clinical importance for assessing loss of kidney function. Various clinically relevant covariates were also explored and found to improve the model. For example, transplant recipients of deceased donors recover function more slowly after transplantation and calcineurin inhibitor use promotes faster long-term decay. Our work provides a generalizable, nonlinear model of kidney allograft function that will be useful for estimating eGFR up to 6 years post-transplant in various clinically relevant populations.
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Affiliation(s)
| | - Eric Frey
- Critical Path InstituteTucsonArizonaUSA
| | | | | | | | - Mark Stegall
- Department of SurgeryMayo ClinicRochesterMinnesotaUSA
| | - Ilkka Helanterä
- Department of Transplantation and Liver SurgeryHelsinki University HospitalHelsinkiFinland
| | - Ahmed Osama Gaber
- Department of Surgery, Houston Methodist HospitalHoustonTexasUSA
- Weill Cornell MedicineNew YorkNew YorkUSA
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Bienaimé F, Muorah M, Metzger M, Broeuilh M, Houiller P, Flamant M, Haymann JP, Vonderscher J, Mizrahi J, Friedlander G, Stengel B, Terzi F. Combining robust urine biomarkers to assess chronic kidney disease progression. EBioMedicine 2023; 93:104635. [PMID: 37285616 DOI: 10.1016/j.ebiom.2023.104635] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 04/21/2023] [Accepted: 05/15/2023] [Indexed: 06/09/2023] Open
Abstract
BACKGROUND Urinary biomarkers may improve the prediction of chronic kidney disease (CKD) progression. Yet, data reporting the applicability of most commercial biomarker assays to the detection of their target analyte in urine together with an evaluation of their predictive performance are scarce. METHODS 30 commercial assays (ELISA) were tested for their ability to quantify the target analyte in urine using strict (FDA-approved) validation criteria. In an exploratory analysis, LASSO (Least Absolute Shrinkage and Selection Operator) logistic regression analysis was used to identify potentially complementary biomarkers predicting fast CKD progression, determined as the 51CrEDTA clearance-based measured glomerular filtration rate (mGFR) decline (>10% per year) in a subsample of 229 CKD patients (mean age, 61 years; 66% men; baseline mGFR, 38 mL/min) from the NephroTest prospective cohort. FINDINGS Among the 30 assays, directed against 24 candidate biomarkers, encompassing different pathophysiological mechanisms of CKD progression, 16 assays fulfilled the FDA-approved criteria. LASSO logistic regressions identified a combination of five biomarkers including CCL2, EGF, KIM1, NGAL, and TGF-α that improved the prediction of fast mGFR decline compared to the kidney failure risk equation variables alone: age, gender, mGFR, and albuminuria. Mean area under the curves (AUC) estimated from 100 re-samples was higher in the model with than without these biomarkers, 0.722 (95% confidence interval 0.652-0.795) vs. 0.682 (0.614-0.748), respectively. Fully-adjusted odds-ratios (95% confidence interval) for fast progression were 1.87 (1.22, 2.98), 1.86 (1.23, 2.89), 0.43 (0.25, 0.70), 1.10 (0.71, 1.83), 0.55 (0.33, 0.89), and 2.99 (1.89, 5.01) for albumin, CCL2, EGF, KIM1, NGAL, and TGF-α, respectively. INTERPRETATION This study provides a rigorous validation of multiple assays for relevant urinary biomarkers of CKD progression which combination may improve the prediction of CKD progression. FUNDING This work was supported by Institut National de la Santé et de la Recherche Médicale, Université de Paris, Assistance Publique Hôpitaux de Paris, Agence Nationale de la Recherche, MSDAVENIR, Pharma Research and Early Development Roche Laboratories (Basel, Switzerland), and Institut Roche de Recherche et Médecine Translationnelle (Paris, France).
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Affiliation(s)
- Frank Bienaimé
- Département « Croissance et Signalisation », Institut Necker Enfants Malades, INSERM U1151, CNRS UMR 8253, Université de Paris Cité, Paris, France; Service d'Explorations Fonctionnelles, Hôpital Necker Enfants Malades, Assistance Publique-Hôpitaux de Paris, Paris, France.
| | - Mordi Muorah
- Département « Croissance et Signalisation », Institut Necker Enfants Malades, INSERM U1151, CNRS UMR 8253, Université de Paris Cité, Paris, France
| | - Marie Metzger
- CESP, Centre de Recherche en Epidémiologie et Santé des Populations, INSERM U1018, Université Paris-Saclay, Villejuif, France
| | - Melanie Broeuilh
- Département « Croissance et Signalisation », Institut Necker Enfants Malades, INSERM U1151, CNRS UMR 8253, Université de Paris Cité, Paris, France
| | - Pascal Houiller
- Service d'Explorations Fonctionnelles, Hôpital Européen George Pompidou, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Martin Flamant
- Service d'Explorations Fonctionnelles, Hôpital Bichat, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Jean-Philippe Haymann
- Service d'Explorations Fonctionnelles, Hôpital Tenon, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Jacky Vonderscher
- Pharma Research and Early Development, Hoffmann-La-Roche Ltd, Basel, France
| | - Jacques Mizrahi
- Pharma Research and Early Development, Hoffmann-La-Roche Ltd, Basel, France
| | - Gérard Friedlander
- Département « Croissance et Signalisation », Institut Necker Enfants Malades, INSERM U1151, CNRS UMR 8253, Université de Paris Cité, Paris, France
| | - Bénédicte Stengel
- CESP, Centre de Recherche en Epidémiologie et Santé des Populations, INSERM U1018, Université Paris-Saclay, Villejuif, France
| | - Fabiola Terzi
- Département « Croissance et Signalisation », Institut Necker Enfants Malades, INSERM U1151, CNRS UMR 8253, Université de Paris Cité, Paris, France.
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Diamantidis CJ, Storfer-Isser A, Fishman E, Wang V, Zepel L, Maciejewski ML. Costs Associated With Progression of Mildly Reduced Kidney Function Among Medicare Advantage Enrollees. Kidney Med 2023; 5:100636. [PMID: 37250500 PMCID: PMC10220400 DOI: 10.1016/j.xkme.2023.100636] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/01/2023] Open
Abstract
Rationale & Objective The prevalence of early chronic kidney disease (CKD) in older adults has increased in the past 2 decades, yet CKD disease progression, overall, is variable. It is unclear whether health care costs differ by progression trajectory. The purpose of this study was to estimate the trajectories of CKD progression and examine Medicare Advantage (MA) health care costs of each trajectory over a 3-year period in a large cohort of MA enrollees with mildly reduced kidney function. Study Design Cohort study. Setting & Population 421,187 MA enrollees with stage G2 CKD in 2014-2017. Outcomes We identified 5 trajectories of kidney function over time. Model Perspective & Timeframe Mean total health care costs for each of the trajectories were described in each of the following 3 years from a payer perspective: 1 year before and 2 years after the index date establishing stage G2 CKD (study entry). Results The mean estimated glomerular filtration rate (eGFR) at study entry was 75.9 mL/min/1.73 m2 and the median (interquartile range) follow-up period was 2.6 (1.6, 3.7) years. The cohort had a mean age of 72.6 years and had predominantly female participants (57.2%), and White (71.2%). We identified the following 5 distinct trajectories of kidney function: a stable eGFR (22.3%); slow eGFR decline with a mean eGFR at study entry of 78.6 (30.2%); slow eGFR decline with an eGFR at study entry of 70.9 (28.4%); steep eGFR decline (16.3%); and accelerated eGFR decline (2.8%). Mean costs of enrollees with accelerated eGFR decline were double the MA enrollees' mean costs in each of the other 4 trajectories in every year ($27,738 vs $13,498 for a stable eGFR 1 year after study entry). Limitations Results may not generalized beyond MA and a lack of albumin values. Conclusions The small fraction of MA enrollees with accelerated eGFR decline has disproportionately higher costs than other enrollees with mildly reduced kidney function.
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Affiliation(s)
- Clarissa J. Diamantidis
- Division of General Internal Medicine, Duke University School of Medicine, Durham, North Carolina
- Division of Nephrology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina
- Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina
| | | | - Ezra Fishman
- National Committee for Quality Assurance, Washington DC
- Optum Labs, Minneapolis, Minnesota
| | - Virginia Wang
- Division of General Internal Medicine, Duke University School of Medicine, Durham, North Carolina
- Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Health Care System, Durham, North Carolina
- Duke-Margolis Center for Health Policy, Duke University, Durham, North Carolina
| | - Lindsay Zepel
- Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina
- Optum Labs, Minneapolis, Minnesota
| | - Matthew L. Maciejewski
- Division of General Internal Medicine, Duke University School of Medicine, Durham, North Carolina
- Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina
- Center of Innovation to Accelerate Discovery and Practice Transformation, Durham Veterans Affairs Health Care System, Durham, North Carolina
- Duke-Margolis Center for Health Policy, Duke University, Durham, North Carolina
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Lucarelli N, Yun D, Han D, Ginley B, Moon KC, Rosenberg AZ, Tomaszewski JE, Zee J, Jen KY, Han SS, Sarder P. Discovery of Novel Digital Biomarkers for Type 2 Diabetic Nephropathy Classification via Integration of Urinary Proteomics and Pathology. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.28.23289272. [PMID: 37205413 PMCID: PMC10187347 DOI: 10.1101/2023.04.28.23289272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Background The heterogeneous phenotype of diabetic nephropathy (DN) from type 2 diabetes complicates appropriate treatment approaches and outcome prediction. Kidney histology helps diagnose DN and predict its outcomes, and an artificial intelligence (AI)-based approach will maximize clinical utility of histopathological evaluation. Herein, we addressed whether AI-based integration of urine proteomics and image features improves DN classification and its outcome prediction, altogether augmenting and advancing pathology practice. Methods We studied whole slide images (WSIs) of periodic acid-Schiff-stained kidney biopsies from 56 DN patients with associated urinary proteomics data. We identified urinary proteins differentially expressed in patients who developed end-stage kidney disease (ESKD) within two years of biopsy. Extending our previously published human-AI-loop pipeline, six renal sub-compartments were computationally segmented from each WSI. Hand-engineered image features for glomeruli and tubules, and urinary protein measurements, were used as inputs to deep-learning frameworks to predict ESKD outcome. Differential expression was correlated with digital image features using the Spearman rank sum coefficient. Results A total of 45 urinary proteins were differentially detected in progressors, which was most predictive of ESKD (AUC=0.95), while tubular and glomerular features were less predictive (AUC=0.71 and AUC=0.63, respectively). Accordingly, a correlation map between canonical cell-type proteins, such as epidermal growth factor and secreted phosphoprotein 1, and AI-based image features was obtained, which supports previous pathobiological results. Conclusions Computational method-based integration of urinary and image biomarkers may improve the pathophysiological understanding of DN progression as well as carry clinical implications in histopathological evaluation.
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Affiliation(s)
- Nicholas Lucarelli
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
| | - Donghwan Yun
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Dohyun Han
- Proteomics Core Facility, Biomedical Research Institute, Seoul National University Hospital, Seoul, Republic of Korea
| | - Brandon Ginley
- The Janssen Pharmaceutical Companies of Johnson & Johnson, Raritan NJ, USA
| | - Kyung Chul Moon
- Department of Pathology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Avi Z. Rosenberg
- Department of Pathology, Johns Hopkins University, Baltimore, MD, USA
| | - John E. Tomaszewski
- Department of Pathology and Anatomical Sciences, University at Buffalo – The State University of New York
| | - Jarcy Zee
- Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania and Children’s Hospital of Philadelphia, PA, USA
| | - Kuang-Yu Jen
- Department of Pathology and Laboratory Medicine, University of California, Davis Medical Center, CA, USA
| | - Seung Seok Han
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Pinaki Sarder
- Department of Medicine-Quantitative Health, University of Florida College of Medicine, Gainesville, FL, USA
- Department of Electrical and Computer Engineering, University of Florida College of Engineering, Gainesville, FL, USA
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Missikpode C, Ricardo AC, Brown J, Durazo-Arvizi RA, Fischer MJ, Hernandez R, Porter AC, Cook JA, Anderson A, Dolata J, Feldman HI, Horwitz E, Lora C, Wright Nunes J, Rao PS, Lash JP. Association between Depressive Symptom Trajectory and Chronic Kidney Disease Progression: Findings from the Chronic Renal Insufficiency Cohort Study. KIDNEY360 2023; 4:606-614. [PMID: 36814088 PMCID: PMC10278792 DOI: 10.34067/kid.0000000000000087] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 01/26/2023] [Indexed: 05/27/2023]
Abstract
Key Points Depressive symptoms are largely stable over time among individuals with mild-to-moderate CKD Low educational attainment, cigarette smoking, and poor quality of life are associated with persistent depressive symptoms Persistent depressive symptoms are associated with nonlinear and rapid decline in kidney function Background Although depression is highly prevalent among individuals with CKD, little is known about the course of depressive symptoms over time. We characterized trajectories of depressive symptoms and CKD progression and evaluated the association between depressive symptoms trajectory and CKD progression. Methods Two thousand three hundred sixty-one individuals with mild-to-moderate CKD enrolled in the Chronic Renal Insufficiency Cohort Study were analyzed. The Beck Depression Inventory (BDI) was used to assess depressive symptoms at baseline and biennially. Higher BDI scores indicate worse depressive symptoms. eGFR was calculated using the 2021 CKD-EPI equation. Group-based trajectory models were used to determine trajectories of BDI score and eGFR change over time. Multinomial logistic regression was used to examine factors associated with BDI trajectories and to evaluate the association of BDI trajectories with eGFR change. Results Over 8 years of follow-up, three patterns of depressive symptoms were identified: persistently low BDI score (57.7%), persistently moderate BDI score (33.1%), and persistently high BDI score (9.2%). Three eGFR trajectory groups were identified: nonlinear, rapid eGFR decline (21.5%); linear, expected eGFR decline (54.8%); and stable eGFR (23.7%). Predictors of persistently moderate and high BDI trajectories included low educational attainment, smoking, and poor quality of life. Compared with those with a persistently low BDI score, the odds for nonlinear, rapid eGFR decline were higher for those with persistently moderate BDI scores (odds ratio [OR], 1.45; 95% confidence interval [CI], 1.04 to 2.03) and persistently high BDI scores (OR, 1.90; 95% CI, 1.02 to 3.56). No association between moderate BDI score and linear, expected eGFR decline was observed. Conclusions Depressive symptoms remained largely stable among individuals with mild-to-moderate CKD, and persistently moderate and high BDI scores were associated with nonlinear, rapid eGFR decline. Future work is needed to better understand the interplay between depression and CKD progression.
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Affiliation(s)
- Celestin Missikpode
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
| | - Ana C. Ricardo
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
| | - Julia Brown
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
| | | | - Michael J. Fischer
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
- Medical Service, Jesse Brown VA Medical Center, Chicago, Illinois
| | - Rosalba Hernandez
- School of Social Work, University of Illinois at Urbana-Champaign, Urbana, Illinois
| | - Anna C. Porter
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
| | - Judith A. Cook
- Department of Psychiatry, University of Illinois at Chicago, Chicago, Illinois
| | - Amanda Anderson
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana
| | - Jacquie Dolata
- Division of Nephrology and Hypertension, MetroHealth Medical Center, Case Western Reserve University, Cleveland, Ohio
| | - Harold I. Feldman
- Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Edward Horwitz
- Division of Nephrology and Hypertension, MetroHealth Medical Center, Case Western Reserve University, Cleveland, Ohio
| | - Claudia Lora
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
| | | | | | - James P Lash
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois
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Wong SPY, Prince DK, Kurella Tamura M, Hall YN, Butler CR, Engelberg RA, Vig EK, Curtis JR, O’Hare AM. Value Placed on Comfort vs Life Prolongation Among Patients Treated With Maintenance Dialysis. JAMA Intern Med 2023; 183:462-469. [PMID: 36972031 PMCID: PMC10043804 DOI: 10.1001/jamainternmed.2023.0265] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Accepted: 01/29/2023] [Indexed: 03/29/2023]
Abstract
Importance Patients receiving maintenance dialysis experience intensive patterns of end-of-life care that might not be consistent with their values. Objective To evaluate the association of patients' health care values with engagement in advance care planning and end-of-life care. Design, Setting, and Participants Survey study of patients who received maintenance dialysis between 2015 and 2018 at dialysis centers in the greater metropolitan areas of Seattle, Washington, and Nashville, Tennessee, with longitudinal follow-up of decedents. Logistic regression models were used to estimate probabilities. Data analysis was conducted between May and October 2022. Exposures A survey question about the value that the participant would place on longevity-focused vs comfort-focused care if they were to become seriously ill. Main Outcomes and Measures Self-reported engagement in advance care planning and care received near the end of life through 2020 using linked kidney registry data and Medicare claims. Results Of 933 patients (mean [SD] age, 62.6 [14.0] years; 525 male patients [56.3%]; 254 [27.2%] identified as Black) who responded to the question about values and could be linked to registry data (65.2% response rate [933 of 1431 eligible patients]), 452 (48.4%) indicated that they would value comfort-focused care, 179 (19.2%) that they would value longevity-focused care, and 302 (32.4%) that they were unsure about the intensity of care they would value. Many had not completed an advance directive (estimated probability, 47.5% [95% CI, 42.9%-52.1%] of those who would value comfort-focused care vs 28.1% [95% CI, 24.0%-32.3%] of those who would value longevity-focused care or were unsure; P < .001), had not discussed hospice (estimated probability, 28.6% [95% CI, 24.6%-32.9%] comfort focused vs 18.2% [95% CI, 14.7%-21.7%] longevity focused or unsure; P < .001), or had not discussed stopping dialysis (estimated probability, 33.3% [95% CI, 29.0%-37.7%] comfort focused vs 21.9% [95% CI, 18.2%-25.8%] longevity focused or unsure; P < .001). Most respondents wanted to receive cardiopulmonary resuscitation (estimated probability, 78.0% [95% CI, 74.2%-81.7%] comfort focused vs 93.9% [95% CI, 91.4%-96.1%] longevity focused or unsure; P < .001) and mechanical ventilation (estimated probability, 52.0% [95% CI, 47.4%-56.6%] comfort focused vs 77.9% [95% CI, 74.0%-81.7%] longevity focused or unsure; P < .001). Among decedents, the percentages of participants who received an intensive procedure during the final month of life (estimated probability, 23.5% [95% CI, 16.5%-31.0%] comfort focused vs 26.1% [95% CI, 18.0%-34.5%] longevity focused or unsure; P = .64), discontinued dialysis (estimated probability, 38.3% [95% CI, 32.0%-44.8%] comfort focused vs 30.2% [95% CI, 23.0%-37.8%] longevity focused or unsure; P = .09), and enrolled in hospice (estimated probability, 32.2% [95% CI, 25.7%-38.7%] comfort focused vs 23.3% [95% CI, 16.4%-30.5%] longevity focused or unsure; P = .07) were not statistically different. Conclusions and Relevance This survey study found that there appeared to be a disconnect between patients' expressed values, which were largely comfort focused, and their engagement in advance care planning and end-of-life care, which reflected a focus on longevity. These findings suggest important opportunities to improve the quality of care for patients receiving dialysis.
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Affiliation(s)
| | | | | | - Yoshio N. Hall
- Department of Medicine, University of Washington, Seattle
| | | | | | | | - J. Randall Curtis
- Department of Medicine, Stanford University, Palo Alto, California
- Cambia Palliative Care Center of Excellence, Department of Medicine, University of Washington, Seattle
| | - Ann M. O’Hare
- Department of Medicine, University of Washington, Seattle
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30
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Piccoli GB, Chatrenet A, Cataldo M, Torreggiani M, Attini R, Masturzo B, Cabiddu G, Versino E. Adding creatinine to routine pregnancy tests: a decision tree for calculating the cost of identifying patients with CKD in pregnancy. Nephrol Dial Transplant 2023; 38:148-157. [PMID: 35238937 PMCID: PMC9869858 DOI: 10.1093/ndt/gfac051] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND Even in its early stages, chronic kidney disease (CKD) is associated with adverse pregnancy outcomes. The current guidelines for pregnancy management suggest identifying risk factors for adverse outcomes but do not mention kidney diseases. Since CKD is often asymptomatic, pregnancy offers a valuable opportunity for diagnosis. The present analysis attempts to quantify the cost of adding serum creatinine to prenatal screening and monitoring tests. METHODS The decision tree we built takes several screening scenarios (before, during and after pregnancy) into consideration, following the hypothesis that while 1:750 pregnant women are affected by stage 4-5 CKD and 1:375 by stage 3B, only 50% of CKD cases are known. Prevalence of abortions/miscarriages was calculated at 30%; compliance with tests was hypothesized at 50% pre- and post-pregnancy and 90% during pregnancy (30% for miscarriages); the cost of serum creatinine (production cost) was set at 0.20 euros. A downloadable calculator, which makes it possible to adapt these figures to other settings, is available. RESULTS The cost per detected CKD case ranged from 111 euros (one test during pregnancy, diagnostic yield 64.8%) to 281.90 euros (one test per trimester, plus one post-pregnancy or miscarriage, diagnostic yield 87.7%). The best policy is identified as one test pre-, one during and one post-pregnancy (191.80 euros, diagnostic yield 89.4%). CONCLUSIONS This study suggests the feasibility of early CKD diagnosis in pregnancy by adding serum creatinine to routinely performed prenatal tests and offers cost estimates for further discussion.
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Affiliation(s)
| | - Antoine Chatrenet
- Néphrologie et dialyse, Centre Hospitalier Le Mans, 194 Avenue Rubillard, Le Mans, France
- Laboratory “Movement, Interactions, Performance” (EA 4334), Le Mans University, Le Mans, France
| | | | - Massimo Torreggiani
- Néphrologie et dialyse, Centre Hospitalier Le Mans, 194 Avenue Rubillard, Le Mans, France
| | - Rossella Attini
- Department of Obstetrics and Gynecology, Città della Salute e della Scienza, Ospedale Sant'Anna, University of Torino, Turin, Italy
| | - Bianca Masturzo
- Department of Obstetrics and Gynecology, Città della Salute e della Scienza, Ospedale Sant'Anna, University of Torino, Turin, Italy
| | | | - Elisabetta Versino
- Epidemiology, Department of Clinical and Biological Sciences, University of Torino, Turin Italy
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Yao Y, Li L, Astor B, Yang W, Greene T. Predicting the risk of a clinical event using longitudinal data: the generalized landmark analysis. BMC Med Res Methodol 2023; 23:5. [PMID: 36611147 PMCID: PMC9824910 DOI: 10.1186/s12874-022-01828-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 12/22/2022] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND In the development of prediction models for a clinical event, it is common to use the static prediction modeling (SPM), a regression model that relates baseline predictors to the time to event. In many situations, the data used in training and validation are from longitudinal studies, where predictor variables are time-varying and measured at clinical visits. But these data are not used in SPM. The landmark analysis (LA), previously proposed for dynamic prediction with longitudinal data, has interpretational difficulty when the baseline is not a risk-changing clinical milestone, as is often the case in observational studies of chronic disease without intervention. METHODS This paper studies the generalized landmark analysis (GLA), a statistical framework to develop prediction models for longitudinal data. The GLA includes the LA as a special case, and generalizes it to situations where the baseline is not a risk-changing clinical milestone with a more useful interpretation. Unlike the LA, the landmark variable does not have to be time since baseline in the GLA, but can be any time-varying prognostic variable. The GLA can also be viewed as a longitudinal generalization of localized prediction, which has been studied in the context of low-dimensional cross-sectional data. We studied the GLA using data from the Chronic Renal Insufficiency Cohort (CRIC) Study and the Wisconsin Allograft Replacement Database (WisARD) and compared the prediction performance of SPM and GLA. RESULTS In various validation populations from longitudinal data, the GLA generally had similarly or better predictive performance than SPM, with notable improvement being seen when the validation population deviated from the baseline population. The GLA also demonstrated similar or better predictive performance than LA, due to its more general model specification. CONCLUSIONS GLA is a generalization of the LA such that the landmark variable does not have to be the time since baseline. It has better interpretation when the baseline is not a risk-changing clinical milestone. The GLA is more adaptive to the validation population than SPM and is more flexible than LA, which may help produce more accurate prediction.
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Affiliation(s)
- Yi Yao
- Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX, US
| | - Liang Li
- Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston, TX, US
| | - Brad Astor
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, US
| | - Wei Yang
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, US
| | - Tom Greene
- School of Medicine, University of Utah, Madison, UT, US
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Jagannathan R, Anand S, Hogan J, Mandal S, Kondal D, Gupta R, Patel SA, Anjana RM, Deepa M, Ali MK, Mohan V, Tandon N, Narayan KV, Prabhakaran D. Estimated glomerular filtration rate trajectories in south Asians: Findings from the cardiometabolic risk reduction in south Asia study. THE LANCET REGIONAL HEALTH. SOUTHEAST ASIA 2022; 6:100062. [PMID: 37383342 PMCID: PMC10305991 DOI: 10.1016/j.lansea.2022.100062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/30/2023]
Abstract
Background Few longitudinal data characterize kidney function decline among South Asians, one of the world's largest population groups. We aimed to identify estimated glomerular filtration rate (eGFR) trajectories in a population-based cohort from India and assess predictors of rapid kidney function decline. Methods We used 6-year longitudinal data from participants of a population-representative study from Delhi and Chennai, India who had at least two serum creatinine measures and baseline CKD-EPI eGFR> 60 ml/min/1.73m2 (n=7779). We used latent class trajectory modeling to identify patterns of kidney function trajectory (CKD-EPI eGFR) over time. In models accounting for age, sex, education, and city, we tested the association between 15 hypothesized risk factors and rapid kidney function decline. Findings Baseline mean eGFR was 108 (SD 16); median eGFR was 110 [IQR: 99-119] ml/min/1.73m2. Latent class trajectory modeling and functional characterization identified three distinct patterns of eGFR: class-1 (no decline; 58%) annual eGFR change 0.2 [0.1, 0.3]; class-2 (slow decline; 40%) annual eGFR change -0.2 [-0.4, -0.1], and class-3 (rapid decline; 2%) annual eGFR change -2.7 [-3.4, -2.0] ml/min/1.73m2. Albuminuria (>30 mg/g) was associated with rapid eGFR decline (OR for class-3 vs class-1: 5.1 [95% CI: 3.2; 7.9]; class-3 vs. class-2: 4.3 [95% CI:2.7; 6.6]). Other risk factors including self-reported diabetes, cardiovascular disease, peripheral arterial disease, and metabolic biomarkers such as HbA1c and systolic blood pressure were associated with rapid eGFR decline phenotype but potential 'non-traditional' risk factors such as manual labor or household water sources were not. Interpretation Although mean and median eGFRs in our population-based cohort were higher than those reported in European cohorts, we found that a sizeable number of adults residing in urban India are experiencing rapid kidney function decline. Early and aggressive risk modification among persons with albuminuria could improve kidney health among South Asians. Funding The CARRS study has been funded with federal funds from the National Heart, Lung, and Blood Institute, National Institutes of Health, under Contract No. HHSN2682009900026C and P01HL154996. Dr. Anand was supported by NIDDK K23DK101826 and R01DK127138.
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Affiliation(s)
- Ram Jagannathan
- Emory University School of Medicine, Division of Hospital Medicine, Atlanta, GA, United States
| | - Shuchi Anand
- Centers for Chronic Disease Control, India
- Stanford University School of Medicine, Division of Nephrology
| | - Julien Hogan
- Department of Surgery, Emory Transplant Center, Emory University School of Medicine, Atlanta, GA, United States
| | - Siddhartha Mandal
- Centers for Chronic Disease Control, India
- Public Health Foundation of India, New Delhi, India
| | | | - Ruby Gupta
- Centers for Chronic Disease Control, India
| | - Shivani A. Patel
- Hubert Department of Global Health, Emory University Rollins School of Public Health, Atlanta, GA, United States
| | - Ranjit Mohan Anjana
- Department of Family and Preventive Medicine, Emory University School of Medicine, Atlanta, GA, United States
| | - Mohan Deepa
- Department of Family and Preventive Medicine, Emory University School of Medicine, Atlanta, GA, United States
| | - Mohammed K. Ali
- Hubert Department of Global Health, Emory University Rollins School of Public Health, Atlanta, GA, United States
- Madras Diabetes Research Foundation, Chennai, India
| | - Viswanathan Mohan
- Department of Family and Preventive Medicine, Emory University School of Medicine, Atlanta, GA, United States
| | - Nikhil Tandon
- Department of Endocrinology & Metabolism, All India Institute of Medical Sciences, Delhi, India
| | - K.M. Venkat Narayan
- Hubert Department of Global Health, Emory University Rollins School of Public Health, Atlanta, GA, United States
| | - Dorairaj Prabhakaran
- Centers for Chronic Disease Control, India
- Public Health Foundation of India, New Delhi, India
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Mishra M, Nichols L, Dave AA, Pittman EH, Cheek JP, Caroland AJV, Lotwala P, Drummond J, Bridges CC. Molecular Mechanisms of Cellular Injury and Role of Toxic Heavy Metals in Chronic Kidney Disease. Int J Mol Sci 2022; 23:11105. [PMID: 36232403 PMCID: PMC9569673 DOI: 10.3390/ijms231911105] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 09/16/2022] [Accepted: 09/19/2022] [Indexed: 01/10/2023] Open
Abstract
Chronic kidney disease (CKD) is a progressive disease that affects millions of adults every year. Major risk factors include diabetes, hypertension, and obesity, which affect millions of adults worldwide. CKD is characterized by cellular injury followed by permanent loss of functional nephrons. As injured cells die and nephrons become sclerotic, remaining healthy nephrons attempt to compensate by undergoing various structural, molecular, and functional changes. While these changes are designed to maintain appropriate renal function, they may lead to additional cellular injury and progression of disease. As CKD progresses and filtration decreases, the ability to eliminate metabolic wastes and environmental toxicants declines. The inability to eliminate environmental toxicants such as arsenic, cadmium, and mercury may contribute to cellular injury and enhance the progression of CKD. The present review describes major molecular alterations that contribute to the pathogenesis of CKD and the effects of arsenic, cadmium, and mercury on the progression of CKD.
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Affiliation(s)
- Manish Mishra
- Department of Biomedical Sciences, Mercer University School of Medicine, Macon, GA 31207, USA
| | - Larry Nichols
- Department of Pathology and Clinical Sciences Education, Mercer University School of Medicine, Macon, GA 31207, USA
| | - Aditi A. Dave
- Department of Biomedical Sciences, Mercer University School of Medicine, Macon, GA 31207, USA
| | - Elizabeth H Pittman
- Department of Biomedical Sciences, Mercer University School of Medicine, Macon, GA 31207, USA
| | - John P. Cheek
- Department of Biomedical Sciences, Mercer University School of Medicine, Macon, GA 31207, USA
| | - Anasalea J. V. Caroland
- Department of Biomedical Sciences, Mercer University School of Medicine, Macon, GA 31207, USA
| | - Purva Lotwala
- Department of Biomedical Sciences, Mercer University School of Medicine, Macon, GA 31207, USA
| | - James Drummond
- Department of Biomedical Sciences, Mercer University School of Medicine, Macon, GA 31207, USA
| | - Christy C. Bridges
- Department of Biomedical Sciences, Mercer University School of Medicine, Macon, GA 31207, USA
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Cleary F, Prieto-Merino D, Nitsch D. A systematic review of statistical methodology used to evaluate progression of chronic kidney disease using electronic healthcare records. PLoS One 2022; 17:e0264167. [PMID: 35905096 PMCID: PMC9337679 DOI: 10.1371/journal.pone.0264167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 02/05/2022] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Electronic healthcare records (EHRs) are a useful resource to study chronic kidney disease (CKD) progression prior to starting dialysis, but pose methodological challenges as kidney function tests are not done on everybody, nor are tests evenly spaced. We sought to review previous research of CKD progression using renal function tests in EHRs, investigating methodology used and investigators' recognition of data quality issues. METHODS AND FINDINGS We searched for studies investigating CKD progression using EHRs in 4 databases (Medline, Embase, Global Health and Web of Science) available as of August 2021. Of 80 articles eligible for review, 59 (74%) were published in the last 5.5 years, mostly using EHRs from the UK, USA and East Asian countries. 33 articles (41%) studied rates of change in eGFR, 23 (29%) studied changes in eGFR from baseline and 15 (19%) studied progression to binary eGFR thresholds. Sample completeness data was available in 44 studies (55%) with analysis populations including less than 75% of the target population in 26 studies (33%). Losses to follow-up went unreported in 62 studies (78%) and 11 studies (14%) defined their cohort based on complete data during follow up. Methods capable of handling data quality issues and other methodological challenges were used in a minority of studies. CONCLUSIONS Studies based on renal function tests in EHRs may have overstated reliability of findings in the presence of informative missingness. Future renal research requires more explicit statements of data completeness and consideration of i) selection bias and representativeness of sample to the intended target population, ii) ascertainment bias where follow-up depends on risk, and iii) the impact of competing mortality. We recommend that renal progression studies should use statistical methods that take into account variability in renal function, informative censoring and population heterogeneity as appropriate to the study question.
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Affiliation(s)
- Faye Cleary
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - David Prieto-Merino
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Dorothea Nitsch
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
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Lim DKE, Boyd JH, Thomas E, Chakera A, Tippaya S, Irish A, Manuel J, Betts K, Robinson S. Prediction models used in the progression of chronic kidney disease: A scoping review. PLoS One 2022; 17:e0271619. [PMID: 35881639 PMCID: PMC9321365 DOI: 10.1371/journal.pone.0271619] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 07/04/2022] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVE To provide a review of prediction models that have been used to measure clinical or pathological progression of chronic kidney disease (CKD). DESIGN Scoping review. DATA SOURCES Medline, EMBASE, CINAHL and Scopus from the year 2011 to 17th February 2022. STUDY SELECTION All English written studies that are published in peer-reviewed journals in any country, that developed at least a statistical or computational model that predicted the risk of CKD progression. DATA EXTRACTION Eligible studies for full text review were assessed on the methods that were used to predict the progression of CKD. The type of information extracted included: the author(s), title of article, year of publication, study dates, study location, number of participants, study design, predicted outcomes, type of prediction model, prediction variables used, validation assessment, limitations and implications. RESULTS From 516 studies, 33 were included for full-text review. A qualitative analysis of the articles was compared following the extracted information. The study populations across the studies were heterogenous and data acquired by the studies were sourced from different levels and locations of healthcare systems. 31 studies implemented supervised models, and 2 studies included unsupervised models. Regardless of the model used, the predicted outcome included measurement of risk of progression towards end-stage kidney disease (ESKD) of related definitions, over given time intervals. However, there is a lack of reporting consistency on details of the development of their prediction models. CONCLUSIONS Researchers are working towards producing an effective model to provide key insights into the progression of CKD. This review found that cox regression modelling was predominantly used among the small number of studies in the review. This made it difficult to perform a comparison between ML algorithms, more so when different validation methods were used in different cohort types. There needs to be increased investment in a more consistent and reproducible approach for future studies looking to develop risk prediction models for CKD progression.
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Affiliation(s)
- David K. E. Lim
- Curtin School of Population Health, Curtin University, Perth, WA, Australia
| | - James H. Boyd
- Curtin School of Population Health, Curtin University, Perth, WA, Australia
- La Trobe University, Melbourne, Bundoora, VIC, Australia
| | - Elizabeth Thomas
- Curtin School of Population Health, Curtin University, Perth, WA, Australia
- Medical School, The University of Western Australia, Perth, WA, Australia
| | - Aron Chakera
- Medical School, The University of Western Australia, Perth, WA, Australia
- Renal Unit, Sir Charles Gairdner Hospital, Perth, WA, Australia
| | - Sawitchaya Tippaya
- Curtin Institute for Computation, Curtin University, Perth, WA, Australia
| | | | | | - Kim Betts
- Curtin School of Population Health, Curtin University, Perth, WA, Australia
| | - Suzanne Robinson
- Curtin School of Population Health, Curtin University, Perth, WA, Australia
- Deakin Health Economics, Deakin University, Burwood, VIC, Australia
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Inaguma D, Hayashi H, Yanagiya R, Koseki A, Iwamori T, Kudo M, Fukuma S, Yuzawa Y. Development of a machine learning-based prediction model for extremely rapid decline in estimated glomerular filtration rate in patients with chronic kidney disease: a retrospective cohort study using a large data set from a hospital in Japan. BMJ Open 2022; 12:e058833. [PMID: 35680264 PMCID: PMC9185577 DOI: 10.1136/bmjopen-2021-058833] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
OBJECTIVES Trajectories of estimated glomerular filtration rate (eGFR) decline vary highly among patients with chronic kidney disease (CKD). It is clinically important to identify patients who have high risk for eGFR decline. We aimed to identify clusters of patients with extremely rapid eGFR decline and develop a prediction model using a machine learning approach. DESIGN Retrospective single-centre cohort study. SETTINGS Tertiary referral university hospital in Toyoake city, Japan. PARTICIPANTS A total of 5657 patients with CKD with baseline eGFR of 30 mL/min/1.73 m2 and eGFR decline of ≥30% within 2 years. PRIMARY OUTCOME Our main outcome was extremely rapid eGFR decline. To study-complicated eGFR behaviours, we first applied a variation of group-based trajectory model, which can find trajectory clusters according to the slope of eGFR decline. Our model identified high-level trajectory groups according to baseline eGFR values and simultaneous trajectory clusters. For each group, we developed prediction models that classified the steepest eGFR decline, defined as extremely rapid eGFR decline compared with others in the same group, where we used the random forest algorithm with clinical parameters. RESULTS Our clustering model first identified three high-level groups according to the baseline eGFR (G1, high GFR, 99.7±19.0; G2, intermediate GFR, 62.9±10.3 and G3, low GFR, 43.7±7.8); our model simultaneously found three eGFR trajectory clusters for each group, resulting in nine clusters with different slopes of eGFR decline. The areas under the curve for classifying the extremely rapid eGFR declines in the G1, G2 and G3 groups were 0.69 (95% CI, 0.63 to 0.76), 0.71 (95% CI 0.69 to 0.74) and 0.79 (95% CI 0.75 to 0.83), respectively. The random forest model identified haemoglobin, albumin and C reactive protein as important characteristics. CONCLUSIONS The random forest model could be useful in identifying patients with extremely rapid eGFR decline. TRIAL REGISTRATION UMIN 000037476; This study was registered with the UMIN Clinical Trials Registry.
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Affiliation(s)
- Daijo Inaguma
- Internal Medicine, Fujita Health University Bantane Hospital, Nagoya, Japan
| | | | - Ryosuke Yanagiya
- Medical Information Systems, Fujita Health University, Toyoake, Japan
| | | | | | | | - Shingo Fukuma
- Human Health Science, Kyoto University, Kyoto, Japan
| | - Yukio Yuzawa
- Nephrology, Fujita Health University, Toyoake, Japan
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Samal L, D’Amore JD, Gannon MP, Kilgallon JL, Charles JP, Mann DM, Siegel LC, Burdge K, Shaykevich S, Lipsitz S, Waikar SS, Bates DW, Wright A. Impact of Kidney Failure Risk Prediction Clinical Decision Support on Monitoring and Referral in Primary Care Management of CKD: A Randomized Pragmatic Clinical Trial. Kidney Med 2022; 4:100493. [PMID: 35866010 PMCID: PMC9293940 DOI: 10.1016/j.xkme.2022.100493] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
Rationale & Objective To design and implement clinical decision support incorporating a validated risk prediction estimate of kidney failure in primary care clinics and to evaluate the impact on stage-appropriate monitoring and referral. Study Design Block-randomized, pragmatic clinical trial. Setting & Participants Ten primary care clinics in the greater Boston area. Patients with stage 3-5 chronic kidney disease (CKD) were included. Patients were randomized within each primary care physician panel through a block randomization approach. The trial occurred between December 4, 2015, and December 3, 2016. Intervention Point-of-care noninterruptive clinical decision support that delivered the 5-year kidney failure risk equation as well as recommendations for stage-appropriate monitoring and referral to nephrology. Outcomes The primary outcome was as follows: Urine and serum laboratory monitoring test findings measured at one timepoint 6 months after the initial primary care visit and analyzed only in patients who had not undergone the recommended monitoring test in the preceding 12 months. The secondary outcome was nephrology referral in patients with a calculated kidney failure risk equation value of >10% measured at one timepoint 6 months after the initial primary care visit. Results The clinical decision support application requested and processed 569,533 Continuity of Care Documents during the study period. Of these, 41,842 (7.3%) documents led to a diagnosis of stage 3, 4, or 5 CKD by the clinical decision support application. A total of 5,590 patients with stage 3, 4, or 5 CKD were randomized and included in the study. The link to the clinical decision support application was clicked 122 times by 57 primary care physicians. There was no association between the clinical decision support intervention and the primary outcome. There was a small but statistically significant difference in nephrology referral, with a higher rate of referral in the control arm. Limitations Contamination within provider and clinic may have attenuated the impact of the intervention and may have biased the result toward null. Conclusions The noninterruptive design of the clinical decision support was selected to prevent cognitive overload; however, the design led to a very low rate of use and ultimately did not improve stage-appropriate monitoring. Funding Research reported in this publication was supported by the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health under award K23DK097187. Trial Registration ClinicalTrials.gov Identifier: NCT02990897.
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Affiliation(s)
- Lipika Samal
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA
- Harvard Medical School, Boston, MA
- Address for Correspondence: Lipika Samal, MD, MPH, Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, 1620 Tremont St, Boston, MA 02120.
| | | | - Michael P. Gannon
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA
| | - John L. Kilgallon
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA
| | - Jean-Pierre Charles
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA
| | - Devin M. Mann
- New York University School of Medicine, New York, NY
| | - Lydia C. Siegel
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA
- Harvard Medical School, Boston, MA
- Mass General Brigham Digital Health eCare, Boston, MA
| | - Kelly Burdge
- Nephrology, Mass General Brigham-Salem Hospital, Salem, MA
| | - Shimon Shaykevich
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA
| | - Stuart Lipsitz
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA
- Harvard Medical School, Boston, MA
| | - Sushrut S. Waikar
- Nephrology, Mass General Brigham-Salem Hospital, Salem, MA
- Section of Nephrology, Boston University School of Medicine and Boston Medical Center, Boston, MA
| | - David W. Bates
- Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA
- Harvard Medical School, Boston, MA
| | - Adam Wright
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN
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Kim HJ, Kim SS, Song SH. Glomerular filtration rate as a kidney outcome of diabetic kidney disease: a focus on new antidiabetic drugs. Korean J Intern Med 2022; 37:502-519. [PMID: 35368179 PMCID: PMC9082447 DOI: 10.3904/kjim.2021.515] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 02/17/2022] [Indexed: 11/27/2022] Open
Abstract
Diabetes has reached epidemic proportions, both in Korea and worldwide and is associated with an increased risk of chronic kidney disease and kidney failure (KF). The natural course of kidney function among people with diabetes (especially type 2 diabetes) may be complex in real-world situations. Strong evidence from observational data and clinical trials has demonstrated a consistent association between decreased estimated glomerular filtration rate (eGFR) and subsequent development of hard renal endpoints (such as KF or renal death). The disadvantage of hard renal endpoints is that they require a long follow-up duration. In addition, there are many patients with diabetes whose renal function declines without the appearance of albuminuria, measurement of the eGFR is emphasized. Many studies have used GFR-related parameters, such as its change, decline, or slope, as clinical endpoints for kidney disease progression. In this respect, understanding the trends in GFR changes could be crucial for developing clinical management strategies for the prevention of diabetic complications. This review focuses on the clinical implication of the eGFR-related parameters that have been used so far in diabetic kidney disease. We also discuss the use of recently developed new antidiabetic drugs for kidney protection, with a focus on the GFR as clinical endpoints.
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Affiliation(s)
- Hyo Jin Kim
- Division of Nephrology, Department of Internal Medicine, Pusan National University Hospital, Busan,
Korea
- Biomedical Research Institute, Pusan National University Hospital, Busan,
Korea
| | - Sang Soo Kim
- Biomedical Research Institute, Pusan National University Hospital, Busan,
Korea
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Pusan National University Hospital, Busan,
Korea
| | - Sang Heon Song
- Division of Nephrology, Department of Internal Medicine, Pusan National University Hospital, Busan,
Korea
- Biomedical Research Institute, Pusan National University Hospital, Busan,
Korea
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Pöhlmann J, Bergenheim K, Garcia Sanchez JJ, Rao N, Briggs A, Pollock RF. Modeling Chronic Kidney Disease in Type 2 Diabetes Mellitus: A Systematic Literature Review of Models, Data Sources, and Derivation Cohorts. Diabetes Ther 2022; 13:651-677. [PMID: 35290625 PMCID: PMC8991383 DOI: 10.1007/s13300-022-01208-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 01/20/2022] [Indexed: 11/26/2022] Open
Abstract
INTRODUCTION As novel therapies for chronic kidney disease (CKD) in type 2 diabetes mellitus (T2DM) become available, their long-term benefits should be evaluated using CKD progression models. Existing models offer different modeling approaches that could be reused, but it may be challenging for modelers to assess commonalities and differences between the many available models. Additionally, the data and underlying population characteristics informing model parameters may not always be evident. Therefore, this study reviewed and summarized existing modeling approaches and data sources for CKD in T2DM, as a reference for future model development. METHODS This systematic literature review included computer simulation models of CKD in T2DM populations. Searches were implemented in PubMed (including MEDLINE), Embase, and the Cochrane Library, up to October 2021. Models were classified as cohort state-transition models (cSTM) or individual patient simulation (IPS) models. Information was extracted on modeled kidney disease states, risk equations for CKD, data sources, and baseline characteristics of derivation cohorts in primary data sources. RESULTS The review identified 49 models (21 IPS, 28 cSTM). A five-state structure was standard among state-transition models, comprising one kidney disease-free state, three kidney disease states [frequently including albuminuria and end-stage kidney disease (ESKD)], and one death state. Five models captured CKD regression and three included cardiovascular disease (CVD). Risk equations most commonly predicted albuminuria and ESKD incidence, while the most predicted CKD sequelae were mortality and CVD. Most data sources were well-established registries, cohort studies, and clinical trials often initiated decades ago in predominantly White populations in high-income countries. Some recent models were developed from country-specific data, particularly for Asian countries, or from clinical outcomes trials. CONCLUSION Modeling CKD in T2DM is an active research area, with a trend towards IPS models developed from non-Western data and single data sources, primarily recent outcomes trials of novel renoprotective treatments.
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Affiliation(s)
| | - Klas Bergenheim
- Global Market Access and Pricing, BioPharmaceuticals, AstraZeneca, Gothenburg, Sweden
| | | | - Naveen Rao
- Global Market Access and Pricing, BioPharmaceuticals, AstraZeneca, Cambridge, UK
| | - Andrew Briggs
- London School of Hygiene and Tropical Medicine, London, UK
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Ellis RJ, Cameron A, Gobe GC, Diwan V, Healy HG, Lee J, Tan KS, Venuthurupalli S, Zhang J, Hoy WE. Kidney failure, CKD progression and mortality after nephrectomy. Int Urol Nephrol 2022; 54:2239-2245. [PMID: 35084650 PMCID: PMC9371989 DOI: 10.1007/s11255-022-03114-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Accepted: 01/11/2022] [Indexed: 12/01/2022]
Abstract
Purpose This study tested the hypothesis that progression of chronic kidney disease (CKD) is less aggressive in patients whose primary cause of CKD was nephrectomy, compared with non-surgical causes. Methods A sample of 5983 patients from five specialist nephrology practices was ascertained from the Queensland CKD Registry. Rates of kidney failure/death were compared on primary aetiology of CKD using multivariable Cox proportional hazards models. CKD progression was compared using multivariable linear and logistic regression analyses. Results Of 235 patients with an acquired single kidney as their primary cause of CKD, 24 (10%) and 38 (17%) developed kidney failure or died at median [IQR] follow-up times of 12.9 [2.5–31.0] and 33.6 [18.0–57.9] months after recruitment. Among patients with an eGFR < 45 mL/min per 1.73m2 at recruitment, patients with diabetic nephropathy and PCKD had the highest rates (per 1000 person-years) of kidney failure (107.8, 95% CI 71.0–163.8; 75.5, 95% CI 65.6–87.1); whereas, patients with glomerulonephritis and an acquired single kidney had lower rates (52.9, 95% CI 38.8–72.1; 34.6, 95% CI 20.5–58.4, respectively). Among patients with an eGFR ≥ 45 mL/min per 1.73m2, those with diabetic nephropathy had the highest rates of kidney failure (16.6, 95% CI 92.5–117.3); whereas, those with glomerulonephritis, PCKD and acquired single kidney had a lower risk (11.3, 95% CI 7.1–17.9; 11.7, 95% CI 3.8–36.2; 10.7, 95% CI 4.0–28.4, respectively). Conclusion Patients who developed CKD after nephrectomy had similar rates of adverse events to most other causes of CKD, except for diabetic nephropathy which was consistently associated with worse outcomes. While CKD after nephrectomy is not the most aggressive cause of kidney disease, it is by no means benign, and is associated with a tangible risk of kidney failure and death, which is comparable to other major causes of CKD. Supplementary Information The online version contains supplementary material available at 10.1007/s11255-022-03114-7.
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Affiliation(s)
- Robert J Ellis
- Princess Alexandra Hospital, Brisbane, QLD, Australia. .,Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia. .,Kidney Disease Research Collaborative, Translational Research Institute, 37 Kent Street, Woolloongabba, Brisbane, QLD, 4102, Australia.
| | - Anne Cameron
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia.,NHMRC CKD.CRE and the CKD.QLD Collaborative, University of Queensland, Brisbane, QLD, Australia
| | - Glenda C Gobe
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia.,Kidney Disease Research Collaborative, Translational Research Institute, 37 Kent Street, Woolloongabba, Brisbane, QLD, 4102, Australia.,NHMRC CKD.CRE and the CKD.QLD Collaborative, University of Queensland, Brisbane, QLD, Australia
| | - Vishal Diwan
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia.,NHMRC CKD.CRE and the CKD.QLD Collaborative, University of Queensland, Brisbane, QLD, Australia
| | - Helen G Healy
- NHMRC CKD.CRE and the CKD.QLD Collaborative, University of Queensland, Brisbane, QLD, Australia.,Kidney Health Service, Royal Brisbane and Women's Hospital, Brisbane, QLD, Australia.,Conjoint Internal Medicine Laboratory, Pathology Queensland, Brisbane, QLD, Australia
| | - Jeremy Lee
- Princess Alexandra Hospital, Brisbane, QLD, Australia
| | - Ken-Soon Tan
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia.,NHMRC CKD.CRE and the CKD.QLD Collaborative, University of Queensland, Brisbane, QLD, Australia.,Department of Nephrology, Logan Hospital, Logan, QLD, Australia
| | - Sree Venuthurupalli
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia.,NHMRC CKD.CRE and the CKD.QLD Collaborative, University of Queensland, Brisbane, QLD, Australia.,Renal Service, Ipswich Hospital, Brisbane, QLD, Australia
| | - Jianzhen Zhang
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia.,NHMRC CKD.CRE and the CKD.QLD Collaborative, University of Queensland, Brisbane, QLD, Australia
| | - Wendy E Hoy
- Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia.,NHMRC CKD.CRE and the CKD.QLD Collaborative, University of Queensland, Brisbane, QLD, Australia
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Stratifying individuals into non-alcoholic fatty liver disease risk levels using time series machine learning models. J Biomed Inform 2022; 126:103986. [PMID: 35007752 DOI: 10.1016/j.jbi.2022.103986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 12/01/2021] [Accepted: 01/03/2022] [Indexed: 02/07/2023]
Abstract
Non-alcoholic fatty liver disease (NAFLD) affects 25% of the population worldwide, and its prevalence is anticipated to increase globally. While most NAFLD patients are asymptomatic, NAFLD may progress to fibrosis, cirrhosis, cardiovascular disease, and diabetes. Research reports, with daunting results, show the challenge that NAFLD's burden causes to global population health. The current process for identifying fibrosis risk levels is inefficient, expensive, does not cover all potential populations, and does not identify the risk in time. Instead of invasive liver biopsies, we implemented a non-invasive fibrosis assessment process calculated from clinical data (accessed via EMRs/EHRs). We stratified patients' risks for fibrosis from 2007 to 2017 by modeling the risk in 5579 individuals. The process involved time-series machine learning models (Hidden Markov Models and Group-Based Trajectory Models) profiled fibrosis risk by modeling patients' latent medical status resulted in three groups. The high-risk group had abnormal lab test values and a higher prevalence of chronic conditions. This study can help overcome the inefficient, traditional process of detecting fibrosis via biopsies (that are also medically unfeasible due to their invasive nature, the medical resources involved, and costs) at early stages. Thus longitudinal risk assessment may be used to make population-specific medical recommendations targeting early detection of high risk patients, to avoid the development of fibrosis disease and its complications as well as decrease healthcare costs.
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Khan MS, Bakris GL, Shahid I, Weir MR, Butler J. Potential Role and Limitations of Estimated Glomerular Filtration Rate Slope Assessment in Cardiovascular Trials: A Review. JAMA Cardiol 2022; 7:549-555. [PMID: 34985495 DOI: 10.1001/jamacardio.2021.5151] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Importance Cardiovascular trials have traditionally been underpowered to assess advanced chronic kidney disease (CKD) outcomes, and when included as a secondary end point, trials have used progression of CKD as incidence of some variation of a composite of end-stage kidney disease (ESKD) outcomes. Such outcomes are infrequent or occur late in cardiovascular outcome trials, which highlights the need for alternate markers for assessing the impact of interventions on kidney function at an earlier stage of the disease and, from the prevention perspective, more relevant stage of the disease. Observations Estimated glomerular filtration rate (eGFR) slope has demonstrated strong association with subsequent progression to ESKD. With adequate sample size, treatment effects in the range of 0.5 to 1.00 mL/min/1.73 m2/y had 96% probability of predicting CKD progression, defined as doubling of serum creatinine, eGFR less than 15 mL/min/1.73 m2, or ESKD. eGFR slope can be used in patients with higher baseline values and may provide CKD progression insights when few hard kidney events are observed, especially in trials with limited follow-up. However, among trials that have determined eGFR slope, significant variations exist regarding inclusion of baseline values, calculation of eGFR values, and the follow-up period, which make it difficult to compare and gauge the incremental benefit of the interventions. There are multiple challenges in computing eGFR slope in cardiovascular trials, such as accounting for initial eGFR dip, nonlinearity, and heteroscedasticity. Conclusions and Relevance eGFR slope may serve as a valuable marker to determine progression of CKD in cardiovascular trials. Further work is required to standardize data collection, follow-up duration, time points for kidney function assessment, and analytic methods to compute eGFR slope in cardiovascular trials.
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Affiliation(s)
| | - George L Bakris
- Department of Medicine, University of Chicago Medical Center, Chicago
| | - Izza Shahid
- Department of Medicine, Ziauddin University, Karachi, Pakistan
| | - Matthew R Weir
- Division of Nephrology, University of Maryland School of Medicine, Baltimore
| | - Javed Butler
- Department of Medicine, University of Mississippi Medical Center, Jackson
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Weng SC, Chen CM, Chen YC, Wu MJ, Tarng DC. Trajectory of Estimated Glomerular Filtration Rate and Malnourishment Predict Mortality and Kidney Failure in Older Adults With Chronic Kidney Disease. Front Med (Lausanne) 2021; 8:760391. [PMID: 34912823 PMCID: PMC8666586 DOI: 10.3389/fmed.2021.760391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 11/08/2021] [Indexed: 11/29/2022] Open
Abstract
Objective: The trajectory patterns of estimated glomerular filtration rates (eGFR) in chronic kidney disease (CKD) older adults with malnourishment and their association with subsequent patient outcomes have not been elucidated. We aimed to assess the eGFR trajectory patterns for predicting patient survival and kidney failure in the elderly without or with malnourishment. Materials and Methods: Based on a prospective longitudinal cohort, CKD patients aged 65 years or older were enrolled from 2001 to 2013. Among the 3,948 patients whose eGFR trajectory patterns were analyzed, 1,872 patients were stratified by the absence or presence of malnourishment, and 765 patients were identified and categorized as having malnourishment. Four eGFR trajectory patterns [gradual decline (T0), early non-decline and then persistent decline (T1), persistent increase (T2), and low baseline and then progressive increase (T3)] were classified by utilizing a linear mixed-effect model with a quadratic term in time. The malnourishment was defined as body mass index < 22 kg/m2, serum albumin < 3.0 mg/dL, or Geriatric Nutritional Risk Index (GNRI) < 98. This study assessed the effectiveness of eGFR trajectory patterns in a median follow-up of 2.27 years for predicting all-cause mortality and kidney failure. Results: The mean age was 76.9 ± 6.7 years, and a total of 82 (10.7%) patients with malnourishment and 57 (5.1%) patients without malnourishment died at the end of the study. Compared with the reference trajectory T0, the overall mortality of T1 was markedly reduced [adjusted hazard ratio (aHR) = 0.52, 95% confidence interval (CI) 0.32–0.83]. In patients with trajectory, T3 was associated with a high risk for kidney failure (aHR = 5.68, 95% CI 3.12–10.4) compared with the reference, especially higher risk in the presence of malnourishment. Patients with high GNRI values were significantly associated with a lower risk of death and kidney failure, but patients with malnourishment and concomitant alcohol consumption had a higher risk of kidney failure. Conclusions: Low baseline eGFR and progressively increasing eGFR trajectory were high risks for kidney failure in CKD patients. These findings may be attributed to multimorbidity, malnourishment, and decompensation of renal function.
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Affiliation(s)
- Shuo-Chun Weng
- College of Medicine, National Chung Hsing University, Taichung, Taiwan.,Center for Geriatrics and Gerontology, Division of Nephrology, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan.,Institute of Clinical Medicine, School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chyong-Mei Chen
- Institute of Public Health, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yu-Chi Chen
- Institute of Clinical Nursing, College of Nursing, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Ming-Ju Wu
- College of Medicine, National Chung Hsing University, Taichung, Taiwan.,Center for Geriatrics and Gerontology, Division of Nephrology, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan.,School of Medicine, Chung Shan Medical University, Taichung, Taiwan.,Rong Hsing Research Center for Translational Medicine, Institute of Biomedical Science, College of Life Science, National Chung Hsing University, Taichung, Taiwan.,Graduate Institute of Clinical Medical Science, School of Medicine, China Medical University, Taichung, Taiwan
| | - Der-Cherng Tarng
- Institute of Clinical Medicine, School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Department and Institute of Physiology, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Division of Nephrology, Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.,Center for Intelligent Drug Systems and Smart Bio-devices (IDS2B), National Yang Ming Chiao Tung University, Hsinchu, Taiwan
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Diamantidis CJ, Zepel L, Wang V, Smith VA, Hudson Scholle S, Tamayo L, Maciejewski ML. Disparities in Chronic Kidney Disease Progression by Medicare Advantage Enrollees. Am J Nephrol 2021; 52:949-957. [PMID: 34875668 DOI: 10.1159/000519758] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Accepted: 09/06/2021] [Indexed: 11/19/2022]
Abstract
INTRODUCTION The prevalence of chronic kidney disease (CKD) in Medicare beneficiaries has quadrupled in the past 2 decades, but little is known about risk factors affecting the progression of CKD. This study aims to understand the progression in Medicare Advantage enrollees and whether it differs by provider recognition of CKD, race and ethnicity, or geographic location. In a large cohort of Medicare Advantage (MA) enrollees, we examined whether CKD progression, up to 5 years after study entry, differed by demographic and clinical factors and identified additional risk factors of CKD progression. METHODS In a cohort of 1,002,388 MA enrollees with CKD stages 1-4 based on 2013-2018 labs, progression was estimated using a mixed-effects model that adjusted for demographics, geographic location, comorbidity, urine albumin-to-creatinine ratio, clinical recognition via diagnosed CKD, and time-fixed effects. Race and ethnicity, geographic location, and clinical recognition of CKD were interacted with time in 3 separate regression models. RESULTS Mean (median) follow-up was 3.1 (3.0) years. Black and Hispanic MA enrollees had greater kidney function at study entry than other beneficiaries, but their kidney function declined faster. MA enrollees with clinically recognized CKD had estimated glomerular filtration rate levels that were 18.6 units (95% confidence interval [CI]: 18.5-18.7) lower than levels of unrecognized patients, but kidney function declined more slowly in enrollees with clinical recognition. There were no differences in CKD progression by geography. After removal of the race coefficient from the eGFR equation in a sensitivity analysis, kidney function was much lower in all years among Black MA enrollees, but patterns of progression remained the same. DISCUSSION/CONCLUSIONS These results suggest that patients with clinically recognized CKD and racial and ethnic minorities merit closer surveillance and management to reduce their risk of faster progression.
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Affiliation(s)
- Clarissa Jonas Diamantidis
- Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
- Division of Nephrology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
- Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA
| | - Lindsay Zepel
- Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA
- OptumLabs Visiting Fellow, Cambridge, Massachusetts, USA
| | - Virginia Wang
- Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
- Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA
- Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, Durham, North Carolina, USA
| | - Valerie A Smith
- Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA
- Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, Durham, North Carolina, USA
| | | | - Loida Tamayo
- Centers for Medicare & Medicaid Services, Baltimore, Maryland, USA
| | - Matthew L Maciejewski
- Division of General Internal Medicine, Department of Medicine, Duke University School of Medicine, Durham, North Carolina, USA
- Department of Population Health Sciences, Duke University School of Medicine, Durham, North Carolina, USA
- Center for Health Services Research in Primary Care, Durham Veterans Affairs Medical Center, Durham, North Carolina, USA
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Yan MT, Chao CT, Lin SH. Chronic Kidney Disease: Strategies to Retard Progression. Int J Mol Sci 2021; 22:ijms221810084. [PMID: 34576247 PMCID: PMC8470895 DOI: 10.3390/ijms221810084] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 09/12/2021] [Accepted: 09/13/2021] [Indexed: 12/11/2022] Open
Abstract
Chronic kidney disease (CKD), defined as the presence of irreversible structural or functional kidney damages, increases the risk of poor outcomes due to its association with multiple complications, including altered mineral metabolism, anemia, metabolic acidosis, and increased cardiovascular events. The mainstay of treatments for CKD lies in the prevention of the development and progression of CKD as well as its complications. Due to the heterogeneous origins and the uncertainty in the pathogenesis of CKD, efficacious therapies for CKD remain challenging. In this review, we focus on the following four themes: first, a summary of the known factors that contribute to CKD development and progression, with an emphasis on avoiding acute kidney injury (AKI); second, an etiology-based treatment strategy for retarding CKD, including the approaches for the common and under-recognized ones; and third, the recommended approaches for ameliorating CKD complications, and the final section discusses the novel agents for counteracting CKD progression.
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Affiliation(s)
- Ming-Tso Yan
- Department of Medicine, Division of Nephrology, Cathay General Hospital, School of Medicine, Fu-Jen Catholic University, Taipei 106, Taiwan;
- National Defense Medical Center, Graduate Institute of Medical Sciences, Taipei 114, Taiwan
| | - Chia-Ter Chao
- Department of Internal Medicine, Nephrology Division, National Taiwan University Hospital, Taipei 104, Taiwan;
- Graduate Institute of Toxicology, National Taiwan University College of Medicine, Taipei 104, Taiwan
- Department of Internal Medicine, Nephrology Division, National Taiwan University College of Medicine, Taipei 104, Taiwan
| | - Shih-Hua Lin
- National Defense Medical Center, Graduate Institute of Medical Sciences, Taipei 114, Taiwan
- Department of Internal Medicine, Nephrology Division, National Defense Medical Center, Taipei 104, Taiwan
- Correspondence: or
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Ramaswamy R, Wee SN, George K, Ghosh A, Sarkar J, Burghaus R, Lippert J. CKD subpopulations defined by risk-factors: A longitudinal analysis of electronic health records. CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2021; 10:1343-1356. [PMID: 34510793 PMCID: PMC8592509 DOI: 10.1002/psp4.12695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 05/24/2021] [Accepted: 06/21/2021] [Indexed: 12/05/2022]
Abstract
Chronic kidney disease (CKD) is a progressive disease that evades early detection and is associated with various comorbidities. Although clinical comprehension and control of these comorbidities is crucial for CKD management, complex pathophysiological interactions and feedback loops make this a formidable task. We have developed a hybrid semimechanistic modeling methodology to investigate CKD progression. The model is represented as a system of ordinary differential equations with embedded neural networks and takes into account complex disease progression pathways, feedback loops, and effects of 53 medications to generate time trajectories of eight clinical biomarkers that capture CKD progression due to various risk factors. The model was applied to real world data of US patients with CKD to map the available longitudinal information onto a set of time‐invariant patient‐specific parameters with a clear biological interpretation. These parameters describing individual patients were used to segment the cohort using a clustering approach. Model‐based simulations were conducted to investigate cluster‐specific treatment strategies. The model was able to reliably reproduce the variability in biomarkers across the cohort. The clustering procedure segmented the cohort into five subpopulations – four with enhanced sensitivity to a specific risk factor (hypertension, hyperlipidemia, hyperglycemia, or impaired kidney) and one that is largely insensitive to any of the risk factors. Simulation studies were used to identify patient‐specific strategies to restrain or prevent CKD progression through management of specific risk factors. The semimechanistic model enables identification of disease progression phenotypes using longitudinal data that aid in prioritizing treatment strategies at individual patient level.
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Affiliation(s)
| | | | | | | | | | - Rolf Burghaus
- Pharmacometrics, Bayer AG - Pharmaceuticals, Wuppertal, Germany
| | - Jörg Lippert
- Pharmacometrics, Bayer AG - Pharmaceuticals, Wuppertal, Germany
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47
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Cohen NM, Schwartzman O, Jaschek R, Lifshitz A, Hoichman M, Balicer R, Shlush LI, Barbash G, Tanay A. Personalized lab test models to quantify disease potentials in healthy individuals. Nat Med 2021; 27:1582-1591. [PMID: 34426707 DOI: 10.1038/s41591-021-01468-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Accepted: 07/12/2021] [Indexed: 12/27/2022]
Abstract
Standardized lab tests are central for patient evaluation, differential diagnosis and treatment. Interpretation of these data is nevertheless lacking quantitative and personalized metrics. Here we report on the modeling of 2.1 billion lab measurements of 92 different lab tests from 2.8 million adults over a span of 18 years. Following unsupervised filtering of 131 chronic conditions and 5,223 drug-test pairs we performed a virtual survey of lab tests distributions in healthy individuals. Age and sex alone explain less than 10% of the within-normal test variance in 89 out of 92 tests. Personalized models based on patients' history explain 60% of the variance for 17 tests and over 36% for half of the tests. This allows for systematic stratification of the risk for future abnormal test levels and subsequent emerging disease. Multivariate modeling of within-normal lab tests can be readily implemented as a basis for quantitative patient evaluation.
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Affiliation(s)
| | - Omer Schwartzman
- Department of Mathematics and Computer Science, Weizmann Institute, Rehovot, Israel.,The Division of Internal Medicine, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Ram Jaschek
- Department of Mathematics and Computer Science, Weizmann Institute, Rehovot, Israel
| | - Aviezer Lifshitz
- Department of Mathematics and Computer Science, Weizmann Institute, Rehovot, Israel
| | - Michael Hoichman
- Department of Mathematics and Computer Science, Weizmann Institute, Rehovot, Israel
| | - Ran Balicer
- Innovation Division, Clalit Research Institute, Clalit Health Services, Tel Aviv, Israel
| | - Liran I Shlush
- Department of Immunology, Weizmann Institute, Rehovot, Israel
| | - Gabi Barbash
- Bench to Bedside Program, Weizmann Institute, Rehovot, Israel
| | - Amos Tanay
- Department of Mathematics and Computer Science, Weizmann Institute, Rehovot, Israel.
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Santos J, Oliveira P, Severo M, Lobato L, Cabrita A, Fonseca I. Different kidney function trajectory patterns before dialysis in elderly patients: clinical implications and outcomes. Ren Fail 2021; 43:1049-1059. [PMID: 34187290 PMCID: PMC8253175 DOI: 10.1080/0886022x.2021.1945464] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Background. Identifying trajectories of kidney disease progression in chronic kidney disease (CKD) patients may help to deliver better care. We aimed to identify and characterize trajectories of renal function decline in CKD patients and to investigate their association with mortality after dialysis. Methods. This retrospective cohort study included 378 CKD patients who initiated dialysis (aged 65 years and over) between 2009 and 2016. Were considered mixed models using linear quadratic and cubic models to define the trajectories, and we used probabilistic clustering procedures. Patient characteristics and care practices at and before dialysis were examined by multivariable multinomial logistic regression. The association of these trajectories with mortality after dialysis was examined using Cox models. Results. Four distinct groups of eGFR trajectories decline before dialysis were identified: slower decline (18.3%), gradual decline (18.3%), early rapid decline (41.2%), and rapid decline (22.2%). Patients with rapid eGFR decline were more likely to have diabetes, more cognitive impairment, to have been hospitalized before dialysis, and were less likely to have received pre-dialysis care compared to the patients with a slower decline. They had a higher risk of death within the first and fourth year after dialysis initiation, and after being more than 4 years in dialysis. Conclusions. There are different patterns of eGFR trajectories before dialysis initiation in the elderly, that may help to identify those who are more likely to experience an accelerated decline in kidney function, with impact on pre ESKD care and in the mortality risk after dialysis.
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Affiliation(s)
- Josefina Santos
- Nephrology Department, Centro Hospitalar Universitário do Porto (CHUP), Porto, Portugal.,Unit for Multidisciplinary Research in Biomedicine, Institute of Biomedical Sciences Abel Salazar, University of Porto, Porto, Portugal
| | - Pedro Oliveira
- EPI Unit, ISPUP - Institute of Public Health, University of Porto, Porto, Portugal.,Department of Population Studies, Institute of Biomedical Sciences Abel Salazar, University of Porto, Porto, Portugal
| | - Milton Severo
- EPI Unit, ISPUP - Institute of Public Health, University of Porto, Porto, Portugal
| | - Luísa Lobato
- Nephrology Department, Centro Hospitalar Universitário do Porto (CHUP), Porto, Portugal.,Unit for Multidisciplinary Research in Biomedicine, Institute of Biomedical Sciences Abel Salazar, University of Porto, Porto, Portugal
| | - António Cabrita
- Nephrology Department, Centro Hospitalar Universitário do Porto (CHUP), Porto, Portugal
| | - Isabel Fonseca
- Nephrology Department, Centro Hospitalar Universitário do Porto (CHUP), Porto, Portugal.,Unit for Multidisciplinary Research in Biomedicine, Institute of Biomedical Sciences Abel Salazar, University of Porto, Porto, Portugal.,EPI Unit, ISPUP - Institute of Public Health, University of Porto, Porto, Portugal
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Longitudinal Studies 5: Development of Risk Prediction Models for Patients with Chronic Disease. Methods Mol Biol 2021. [PMID: 33871844 DOI: 10.1007/978-1-0716-1138-8_10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
Abstract
Chronic diseases are now the major cause of ill health in both developed and developing countries. Chronic diseases evolve, over decades, from an early reversible phase, to a late stage of irreversible organ damage. Importantly, the trajectory of individual patients with a chronic disease is highly variable. This uncertainty causes substantial stress and difficulty for patients, care providers, and health systems. Clinical risk prediction models address this uncertainty by incorporating multiple variables to more precisely estimate the risk of adverse events for an individual patient. In the current chapter, we describe the general approach to developing a risk prediction model. We then illustrate how these methods are applied in the development and validation of the kidney failure risk equation (KFRE), which accurately predicts the risk of kidney failure in patients with chronic kidney disease stages 3-5.
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Thorsness R, Swaminathan S, Lee Y, Sommers BD, Mehrotra R, Nguyen KH, Kim D, Rivera-Hernandez M, Trivedi AN. Medicaid Expansion and Incidence of Kidney Failure among Nonelderly Adults. J Am Soc Nephrol 2021; 32:1425-1435. [PMID: 33795426 PMCID: PMC8259656 DOI: 10.1681/asn.2020101511] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 01/30/2021] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Low-income individuals without health insurance have limited access to health care. Medicaid expansions may reduce kidney failure incidence by improving access to chronic disease care. METHODS Using a difference-in-differences analysis, we examined the association between Medicaid expansion status under the Affordable Care Act (ACA) and the kidney failure incidence rate among all nonelderly adults, aged 19-64 years, in the United States, from 2012 through 2018. We compared changes in kidney failure incidence in states that implemented Medicaid expansions with concurrent changes in nonexpansion states during pre-expansion, early postexpansion (years 2 and 3 postexpansion), and later postexpansion (years 4 and 5 postexpansion). RESULTS The unadjusted kidney failure incidence rate increased in the early years of the study period in both expansion and nonexpansion states before stabilizing. After adjustment for population sociodemographic characteristics, Medicaid expansion status was associated with 2.20 fewer incident cases of kidney failure per million adults per quarter in the early postexpansion period (95% CI, -3.89 to -0.51) compared with nonexpansion status, a 3.07% relative reduction (95% CI, -5.43% to -0.72%). In the later postexpansion period, Medicaid expansion status was not associated with a statistically significant change in kidney failure incidence (-0.56 cases per million per quarter; 95% CI, -2.71 to 1.58) compared with nonexpansion status and the pre-expansion time period. CONCLUSIONS The ACA Medicaid expansion was associated with an initial reduction in kidney failure incidence among the entire, nonelderly, adult population in the United States; but the changes did not persist in the later postexpansion period. Further study is needed to determine the long-term association between Medicaid expansion and changes in kidney failure incidence.
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Affiliation(s)
- Rebecca Thorsness
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
| | - Shailender Swaminathan
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island,Providence Veterans Affairs Medical Center, Providence, Rhode Island
| | - Yoojin Lee
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
| | - Benjamin D. Sommers
- Department of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, Massachusetts,Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Rajnish Mehrotra
- Division of Nephrology, Department of Medicine, University of Washington School of Medicine, Seattle, Washington
| | - Kevin H. Nguyen
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
| | - Daeho Kim
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
| | - Maricruz Rivera-Hernandez
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island
| | - Amal N. Trivedi
- Department of Health Services, Policy, and Practice, Brown University School of Public Health, Providence, Rhode Island,Providence Veterans Affairs Medical Center, Providence, Rhode Island
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