• Acute kidney injury
• Biomarker
• Group-based trajectory modeling
• Liver-type fatty acid-binding protein
• Major adverse kidney event
• Neutrophil gelatinase-associated lipocalin
• Trajectory

• Adult
• Humans
• Creatinine
• Brazil/epidemiology
• Hospital Mortality
• Hospitalization
• Hypotension

• Acute kidney injury
• Dialysis
• Non-coronavirus disease-2019
• Renal survival

• Acute kidney injury
• Delayed graft function
• End-stage kidney disease
• Transplantation

• Humans
• Retrospective Studies
• Kidney Transplantation
• Tissue and Organ Procurement
• Tissue Donors
• Kidney
• Acute Kidney Injury
• Graft Survival
• Biopsy
• Delayed Graft Function/epidemiology

• Universitätsklinikum Magdeburg (8973)

Patients with severe acute kidney injury (AKI) may require renal replacement therapy (RRT), such as hemodialysis and peritoneal dialysis. Neutrophil gelatinase-associated lipocalin (NGAL) is a sensitive indicator for early diagnosis and recognition of AKI; however, its predictive value of AKI-associated need for RRT needs further evaluation.

Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, relevant articles were systematically searched and selected from seven databases. The random effects model was applied to evaluate the predictive performance of NGAL for AKI requiring RRT. The Newcastle–Ottawa Scale (NOS) was used to assess the quality of each included study.

A total of 18 studies including 1,787 patients with AKI and having an average NOS score of 7.67 were included in the meta-analysis. For plasma/serum NGAL, the pooled sensitivity and specificity with corresponding 95% confidence interval (CI) were 0.75 (95% CI: 0.68–0.81) and 0.76 (95% CI: 0.70–0.81), respectively. The pooled positive likelihood ratio (PLR) was 2.9 (95% CI: 2.1–4.1), and the pooled negative likelihood ratio (NLR) was 0.34 (95% CI: 0.25–0.46). Subsequently, the pooled diagnostic odds ratio (DOR) was 9 (95% CI: 5–16) using a random effects model, and the area under the curve (AUC) of summary receiver operating characteristic to summarize predictive accuracy was 0.82 (95% CI: 0.79–0.85). For urine NGAL, the pooled sensitivity, specificity, PLR, NLR, DOR, and AUC values were 0.78 (95% CI: 0.61–0.90), 0.77 (95% CI: 0.65–0.85), 3.4 (95% CI: 2.4–4.8), 0.28 (95% CI: 0.15–0.52), 12 (95% CI: 6–24), and 0.84 (95% CI: 0.80–0.87), respectively.

Plasma/serum and urine NGAL levels performed comparably well in predicting AKI requiring RRT. Our findings suggested that NGAL is an effective predictive biomarker for the AKI-associated need for RRT. Nevertheless, more pieces of high-quality evidence and future trials with larger sample sizes are needed for further improvement of patient outcomes.

[https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022346595], identifier [CRD42022346595].

• Acute kidney injury
• Critically ill patients
• Emergency surgery
• Prognosis
• Risk factor

• Acute Kidney Injury/epidemiology
• Acute Kidney Injury/surgery
• Aged
• Critical Illness
• Emergency Treatment
• Female
• Humans
• Incidence
• Male
• Middle Aged
• Prospective Studies
• Risk Factors
• Treatment Outcome

• Office of Talent Work Leading Group in Maoming
• Guangzhou Science and Technology Program
• National Natural Science Foundation of China (NSFC)
• Major Program of Summit Project, Guangdong Province High-level Hospital Construction Project of Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences
• Emergent Science and Technology Project for Prevention and Treatment of Novel Coronavirus Pneumonia
• High-level Hospital Construction Research Project of Maoming People's Hospital

A disruption of several metabolic pathways in critically ill patients with sepsis indicates that metabolomics might be used as a more precise tool for sepsis and septic shock when compared with the conventional biomarkers. This article provides information regarding metabolomics studies in sepsis and septic shock patients. It has been shown that a variety of metabolomic pathways are altered in sepsis and septic shock, including amino acid metabolism, fatty acid oxidation, phospholipid metabolism, glycolysis, and tricarboxylic acid cycle. Based upon this comprehensive review, here, we demonstrate that metabolomics is about to change the world of sepsis biomarkers, not only for its utilization in sepsis diagnosis, but also for prognosticating and monitoring the therapeutic response. Additionally, the future direction regarding the establishment of studies integrating metabolomics with other molecular modalities and studies identifying the relationships between metabolomic profiles and clinical characteristics to address clinical application are discussed in this article. All of the information from this review indicates the important impact of metabolomics as a tool for diagnosis, monitoring therapeutic response, and prognostic assessment of sepsis and septic shock. These findings also encourage further clinical investigations to warrant its use in routine clinical settings.

• critically ill patients
• diagnosis
• metabolism
• metabolomics
• prognosis
• sepsis
• septic shock
• treatment monitoring

Acute kidney injury (AKI), chronic kidney disease (CKD), and decreased estimated glomerular filtration rate (eGFR) are all associated with poor clinical outcomes among emergency department (ED) patients. This study aimed to evaluate the effect of different types of renal dysfunction and the degree of eGFR reduction on the clinical outcomes in a real-world ED setting.

Adult patients with an eGFR lower than 60 mL/min/1.73m² in our ED, from October 1, 2016, to December 31, 2016, were enrolled in this retrospective observational study. Besides AKI and CKD, patients with unknown baseline renal function before an ED visit were categorized in the undetermined renal dysfunction (URD) category.

Among 1495 patients who had eGFR evaluation at ED, this study finally enrolled 441 patients; 22 patients (5.0%) had AKI only, 32 (7.3%) had AKI on CKD, 196 (44.4%) had CKD only, 27 (6.1%) had subclinical kidney injury (those who met neither criteria for AKI nor CKD), and 164 (37.2%) had URD. There was a significant association between eGFR and critical illness defined as the composite outcome of death or intensive care unit (ICU) need, hospitalization, ICU need, death, and renal replacement therapy need (odds ratio [95% confidence interval]: 1.72 [1.45–2.05], 1.36 [1.16–1.59], 1.66 [1.39–2.00], 1.73 [1.32–2.28], and 2.71 [1.73–4.24] for every 10 mL/min/1.73m² of reduction, respectively). Multivariate logistic regression analysis showed eGFR was an independent predictor of critical illness composite outcome (death or ICU need), hospitalization, and ICU need even after adjustment with AKI or URD.

Estimated GFR may be a sufficient predictor of clinical outcomes of ED patients regardless of AKI complication. Considerable ED patients were determined as URD, which might have a significant impact on the ED statistics regarding renal dysfunction.

Background and Objective: Acute kidney injury (AKI) remains a serious health condition around the world, and is related to high morbidity, mortality, longer hospitalization duration and worse long-term outcomes. The aim of our study was to estimate the significant related factors for poor outcomes of patients with severe AKI requiring renal replacement therapy (RRT). Materials and Methods: We retrospectively analyzed data from patients (n = 573) with severe AKI requiring RRT within a 5-year period and analyzed the outcomes on discharge from the hospital. We also compared the clinical data of the surviving and non-surviving patients and examined possible related factors for poor patient outcomes. Logistic regression was used to analyze the odds ratio for patient mortality and its related factors. Results: In 32.5% (n = 186) of the patients, the renal function improved and RRT was stopped, 51.7% (n = 296) of the patients died, and 15.9% (n = 91) of the patients remained dialysis-dependent on the day of discharge from the hospital. During the period of 5 years, the outcomes of the investigated patients did not change statistically significantly. Administration of vasopressors, aminoglycosides, sepsis, pulmonary edema, oliguria, artificial pulmonary ventilation (APV), patient age ≥ 65 y, renal cause of AKI, AKI after cardiac surgery, a combination of two or more RRT methods, dysfunction of three or more organs, systolic blood pressure (BP) ≤ 120 mmHg, diastolic BP ≤ 65 mmHg, and Sequential Organ Failure Assessment (SOFA) score on the day of the first RRT procedure ≥ 7.5 were related factors for lethal patient outcome. Conclusions: The mortality rate among patients with severe AKI requiring RRT is very high—52%. Patient death was significantly predicted by the causes of AKI (sepsis, cardiac surgery), clinical course (oliguria, pulmonary edema, hypotension, acidosis, lesion of other organs) and the need for a continuous renal replacement therapy.

• acute kidney injury
• mortality prediction
• renal replacement therapy

• Critically-ill surgical patient
• End-stage kidney disease
• Intensive care unit
• Major operation
• Morbidity
• Mortality

Acute kidney injury is common in the surgical intensive care unit (ICU). It is associated with poor patient outcomes and high healthcare resource usage. This study’s primary objective is to help identify which ICU patients are at high risk for acute kidney injury. Its secondary objective is to examine the effect of acute kidney injury on a patient’s prognosis during and after the ICU admission.

A retrospective cohort of patients admitted to a Singaporean surgical ICU between 2015 to 2017 was collated. Patients undergoing chronic dialysis were excluded. The outcomes were occurrence of ICU acute kidney injury, hospital mortality and one-year mortality. Predictors were identified using decision tree algorithms. Confirmatory analysis was performed using a generalized structural equation model.

A total of 201/940 (21.4%) patients suffered acute kidney injury in the ICU. Low ICU haemoglobin levels, low ICU bicarbonate levels, ICU sepsis, low pre-ICU estimated glomerular filtration rate (eGFR) and congestive heart failure was associated with the occurrence of ICU acute kidney injury. Acute kidney injury, together with old age (> 70 years), and low pre-ICU eGFR, was associated with hospital mortality, and one-year mortality. ICU haemoglobin level was discretized into 3 risk categories for acute kidney injury: high risk (haemoglobin ≤9.7 g/dL), moderate risk (haemoglobin between 9.8–12 g/dL), and low risk (haemoglobin > 12 g/dL).

The occurrence of acute kidney injury is common in the surgical ICU. It is associated with a higher risk for hospital and one-year mortality. These results, in particular the identified haemoglobin thresholds, are relevant for stratifying a patient’s acute kidney injury risk.

The online version contains supplementary material available at 10.1186/s12882-021-02238-9.

• Acute kidney injury
• Critically ill
• Hemoglobin
• Mortality
• Surgery

Background: Acute kidney injury (AKI) is a common complication encountered in an intensive care unit (ICU). In 2020, the AKI prediction score was developed specifically for critically ill surgical patients who underwent major non-cardiothoracic surgeries. This study aimed to externally validate the AKI prediction score in terms of performance and clinical utility. Methods: External validation was carried out in a prospective cohort of patients admitted to the ICU of the Faculty of Medicine Vajira Hospital between September 2014 and September 2015. The endpoint was AKI within seven days following ICU admission. Discriminative ability was based on the area under the receiver operating characteristic curves (AuROC). Calibration and clinical usefulness were evaluated. Results: A total of 201 patients were included in the analysis. AKI occurred in 37 (18.4%) patients. The discriminative ability dropped from good in the derivation cohort, to acceptable in the validation cohort (0.839 (95%CI 0.825–0.852) vs. 0.745 (95%CI 0.652–0.838)). No evidence of lack-of-fit was identified (p = 0.754). The score had potential clinical usefulness across the range of threshold probability from 10 to 50%. Conclusions: The AKI prediction score showed an acceptable discriminative performance and calibration with potential clinical usefulness for predicting AKI risk in surgical patients who underwent major non-cardiothoracic surgery.

• acute kidney injury
• critical care
• prediction
• surgery
• validation study

Acute kidney injury (AKI) is common in patients undergoing major surgeries, and leads to the need for renal replacement therapy and increased morbidity, intensive care unit (ICU) and hospital length of stay (LOS), cost, and mortality. We evaluated the incidence and predictors of postoperative AKI in patients undergoing hepatic resections and their short-term outcomes.

This prospective observational study was conducted over a 3-year period in 180 patients undergoing elective hepatic resections for a variety of indications. We used the Acute Kidney Injury Network criteria to determine the incidence of AKI at 72 hours. Perioperative variables contributing to the development of AKI and the short-term postoperative outcomes of patients were evaluated.

Postoperative AKI occurred in 29.4% of patients. Persistent renal dysfunction was seen in five patients. Development of AKI was associated with hepatic failure (18.5 vs 5.5%, p < 0.005), prolonged ICU (2 vs 1 days, p < 0.001) and hospital LOS (11 vs 8 days, p < 0.004), and increased ICU and hospital mortality (9.6 vs 1.4%, p < 0.02). Age [OR (odds ratio) 1.033, 95% CI (confidence interval) 1.003–1.065, p = 0.03], BMI (body mass index) (OR 1.131, 95% CI 1.043–1.227, p = 0.003), and need for postoperative ventilation (OR 3.456, 95% CI 1.593–7.495, p = 0.002) were independent predictors of AKI.

AKI after elective hepatic resection occurred in nearly one-third of our patients. Persistent renal dysfunction was seen in five patients. Age, BMI, and need for postoperative ventilation were independent predictors of postoperative AKI. (CTRI reg. No.: CTRI/2016/06/007044).

Joshi M, Milmile R, Dhakane P, Bhosale SJ, Kulkarni AP. Incidence and Predictors of Acute Kidney Injury in Patients Undergoing Elective Hepatic Resection for Malignant Tumors: A 3-year Prospective Observational Study. Indian J Crit Care Med 2021;25(4):398–404.

• Acute kidney injury
• Hepatic resection
• Obesity
• Postoperative mechanical ventilation
• Postoperative morbidity
• Postoperative mortality
• Predictors of outcome

• Acute kidney injury
• Arterial lactate
• Gastrointestinal and hepatobiliary surgery
• Neutrophil-to-lymphocyte ratio
• Sepsis
• Surgical intensive care unit

There has been a global increase in the incidence of acute kidney injury (AKI), including among critically-ill surgical patients. AKI prediction score provides an opportunity for early detection of patients who are at risk of AKI; however, most of the AKI prediction scores were derived from cardiothoracic surgery. Therefore, we aimed to develop an AKI prediction score for major non-cardiothoracic surgery patients who were admitted to the intensive care unit (ICU).

The data of critically-ill patients from non-cardiothoracic operations in the Thai Surgical Intensive Care Unit (THAI-SICU) study were used to develop an AKI prediction score. Independent prognostic factors from regression analysis were included as predictors in the model. The outcome of interest was AKI within 7 days after the ICU admission. The AKI diagnosis was made according to the Kidney Disease Improving Global Outcomes (KDIGO)-2012 serum creatinine criteria. Diagnostic function of the model was determined by area under the Receiver Operating Curve (AuROC). Risk scores were categorized into four risk probability levels: low (0–2.5), moderate (3.0–8.5), high (9.0–11.5), and very high (12.0–16.5) risk. Risk of AKI was presented as likelihood ratios of positive (LH+).

A total of 3474 critically-ill surgical patients were included in the model; 333 (9.6%) developed AKI. Using multivariable logistic regression analysis, older age, high Sequential Organ Failure Assessment (SOFA) non-renal score, emergency surgery, large volume of perioperative blood loss, less urine output, and sepsis were identified as independent predictors for AKI. Then AKI prediction score was created from these predictors. The summation of the score was 16.5 and had a discriminative ability for predicting AKI at AuROC = 0.839 (95% CI 0.825–0.852). LH+ for AKI were: low risk = 0.117 (0.063–0.200); moderate risk = 0.927 (0.745–1.148); high risk = 5.190 (3.881–6.910); and very high risk = 9.892 (6.230–15.695), respectively.

The function of AKI prediction score to predict AKI among critically ill patients who underwent non-cardiothoracic surgery was good. It can aid in early recognition of critically-ill surgical patients who are at risk from ICU admission. The scores could guide decision making for aggressive strategies to prevent AKI during the perioperative period or at ICU admission.

TCTR20190408004, registered on April 4, 2019.

• Acute kidney injury
• Critically-ill surgical patient
• Intensive care unit
• Risk prediction score

Acute kidney injury (AKI) is a major global health problem. We aim to evaluate the epidemiology, risk factors and outcomes of AKI episodes in our single centre.

We prospectively identified 422 AKI and acute on chronic kidney disease episodes in 404 patients meeting KDIGO definitions using electronic medical records and clinical data from 15th July to 22nd October 2016, excluding patients with baseline estimated GFR (eGFR) of < 15 mL/min. Patients were followed up till 6 months after AKI diagnosis.

The mean age was 65.8 ± 14.1. Majority of patients were male (58.2%) of Chinese ethnicity (68.8%). One hundred and thirty-two patients (32.6%) were diagnosed in acute care units. Seventy-five percent of patients developed AKI during admission in a non-Renal specialty. Mean baseline eGFR was 50.2 ± 27.7 mL/min. Mean creatinine at AKI diagnosis was 297 ± 161 μmol/L. Renal consultations were initiated at KDIGO Stages 1, 2 and 3 in 58.9, 24.5 and 16.6% of patients, respectively. Three hundred and ten (76.7%) patients had a single etiology of AKI with the 3 most common etiologies of AKI being pre-renal (27.7%), sepsis-associated (25.5%) and ischemic acute tubular necrosis (15.3%). One hundred and nine (27%) patients received acute renal replacement therapy. In-hospital mortality was 20.3%. Six-month mortality post-AKI event was 9.4%. On survival analysis, patients with KDIGO Stage 3 AKI had significantly shorter survival than other stages.

AKI is associated with significant in-hospital to 6-month mortality. This signifies the pressing need for AKI prevention, early detection and intervention in mitigating reversible risk factors in order to optimize clinical outcomes.

The online version of this article (10.1186/s12882-019-1466-z) contains supplementary material, which is available to authorized users.

• Acute kidney injury
• Dialysis
• Mortality

• NSAIDS
• critically ill adults
• opioids
• pain treatment

• Analgesics, Non-Narcotic/adverse effects
• Analgesics, Non-Narcotic/therapeutic use
• Analgesics, Opioid/adverse effects
• Analgesics, Opioid/therapeutic use
• Critical Illness
• Drug Prescriptions/statistics & numerical data
• Humans
• Intensive Care Units
• Pain/drug therapy
• Pain Management/methods
• Pain Management/trends
• Pain Measurement
• Practice Patterns, Physicians'/trends

• autophagy
• acute kidney injury
• mesenchymal stem cells
• cell death

• Acute Kidney Injury/pathology
• Acute Kidney Injury/therapy
• Adenine/analogs & derivatives
• Adenine/therapeutic use
• Animals
• Autophagy
• Humans
• Mesenchymal Stem Cell Transplantation
• Mesenchymal Stem Cells/cytology
• Mesenchymal Stem Cells/metabolism
• MicroRNAs/metabolism
• Reperfusion Injury/pathology
• Reperfusion Injury/prevention & control
• TOR Serine-Threonine Kinases/metabolism