The coronavirus disease (COVID-19) pandemic is a global health emergency, and SARS-CoV-2 pneumonia poses significant challenges to health systems worldwide. Renal transplant recipients (RTRs) are a special group and are more vulnerable to viral pneumonia. However, few studies have elucidated the risk factors of SARS-CoV-2 pneumonia in RTRs infected with COVID-19. This study aimed to build a risk prediction model for SARS-CoV-2 pneumonia among RTRs based on demographic and clinical information.

We conducted a prospective cohort study among 383 RTRs (age ≥ 18 years) diagnosed with COVID-19 from December 21, 2022, to March 26, 2023. Patients' demographic and clinical information was collected through a questionnaire survey combined with electronic medical records. A stepwise logistic regression model was established to test the predictors of SARS-CoV-2 pneumonia. We assessed the diagnostic performance of the model by calculating the area under the curve (AUC) of the receiver operating characteristic (ROC) and calibration using the Hosmer-Lemeshow (HL) goodness-of-fit test.

Our study showed that the incidence of SARS-CoV-2 pneumonia among RTRs was 31.1%. Older age (OR = 2.08-3.37,95%CI:1.05-7.23), shorter post-transplantation duration (OR = 0.92,95% CI: 0.87,0.99), higher post-transplant Charlson Comorbidity Index (CCI) (OR = 1.84, 95%CI: 1.14,2.98), pulmonary infection history (OR = 3.44, 95%CI: 1.459, 8.099, P = 0.005), fatigue (OR = 2.11, 95%CI: 1.14, 3.90), cough (OR = 2.03, 95%CI: 1.08, 3.81), and lower estimated glomerular filtration rate (eGFR) at COVID-19 diagnosis (OR = 0.98, 95%CI:0.97,0.99) predicted a higher risk for SARS-CoV-2 pneumonia. The model showed good diagnostic performance with Chi-Square = 10.832 (P > 0.05) and AUC = 0.839 (P < 0.001).

Our study showed a high incidence of SARS-CoV-2 pneumonia among RTRs, and we built a risk prediction model for SARS-CoV-2 pneumonia based on patients' demographic and clinical characteristics. The model can help identify RTRs infected with COVID-19 at high risk of SARS-CoV-2 pneumonia to inform timely, targeted, and effective prevention and intervention efforts.

The effects of COVID-19 on the immune profile of kidney transplant recipients are unknown. Immunosuppression adjustment during the illness can increase the risk for de novo donor-specific anti-HLA antibodies (DSA) and acute rejection episodes. This single-center retrospective study includes adult kidney transplant recipients diagnosed with COVID-19 between March 2020 and December 2022, screened for anti-HLA antibodies (AbHLA) pre-transplant and after COVID-19. Analyzed data comprised demographics, immunosuppressive therapy before and during the illness, hospitalization rate, and AbHLA specificity. Two hundred sixty-seven transplant recipients were included and divided according to the pre-transplant AbHLA profile: absent [PRA- (n = 206, 77%)], non-DSA (N = 46, 17%), and DSA+ (n = 15, 6%). The DSA+ group was younger (40.5 ± 16.5; PRA- 50.3 ± 13.4; non-DSA 49.3 ± 11.7 years; p = 0.02). The hospitalization rate was higher in groups with preformed AbHLA (DSA+ n = 8, 53%; non-DSA = 24, 52%; PRA- n = 54, 26%; p < 0.01). Immunosuppression was maintained in 222 (83%), withdrawn in 33 (12%), and reduced in 11 (4%) cases without difference among groups. Twenty-two (8%) cases of de novo DSA were observed after COVID-19 [PRA-, n = 16 (73%) and non-DSA, n = 6 (27%)]. In the DSA+ group, the AbHLA profile remained stable. There were 6 (2%) cases of post-COVID-19 antibody-mediated rejection (DSA+ n = 4, 66%; non-DSA n = 1, 17%, PRA- n = 1, 17%) without T cell-mediated rejection cases. Post-COVID-19 de novo DSA was more frequent in groups without pre-transplant AbHLA, not having association with changes in immunosuppressive therapy.

The aim of this study was to assess the impact of immunosuppression management on coronavirus disease 2019 (COVID-19) outcomes.

We performed a single-center retrospective study in a cohort of 358 lung transplant recipients (LTx) over the period from March 2020 to April 2022. All included symptomatic patients had at least one positive SARS-CoV-2 rt-PCR. We used a composite primary outcome for COVID-19 including increased need for oxygen since the hospital admission, ICU transfer, and in-hospital mortality. We assessed by univariate and multivariate analyses the risk factors for poor outcomes.

Overall, we included 91 LTx who contracted COVID-19. The COVID-19 in-hospital mortality rate reached 4.4%. By hierarchical clustering, we found a strong and independent association between the composite poor outcome and the discontinuation of at least one immunosuppressive molecule among tacrolimus, cyclosporine, mycophenolate mofetil, and everolimus. Obesity (OR = 16, 95%CI (1.96; 167), p = 0.01) and chronic renal failure (OR = 4.6, 95%CI (1.4; 18), p = 0.01) were also independently associated with the composite poor outcome. Conversely, full vaccination was protective (OR = 0.23, 95%CI (0.046; 0.89), p = 0.047).

The administration of immunosuppressive drugs such as tacrolimus, cyclocporine or everolimus can have a protective effect in LTx with COVID-19, probably related to their intrinsic antiviral capacity.

Patients with chronic kidney disease (CKD), especially those on dialysis or who have received a kidney transplant (KT), are considered more vulnerable to severe COVID-19. This susceptibility is attributed to advanced age, a higher frequency of comorbidities, and the chronic immunosuppressed state, which may exacerbate their susceptibility to severe outcomes. Therefore, our study aimed to compare the clinical characteristics and outcomes of COVID-19 in KT patients with those on chronic dialysis and non-CKD patients in a propensity score-matched cohort study. This multicentric retrospective cohort included adult COVID-19 laboratory-confirmed patients admitted from March/2020 to July/2022, from 43 Brazilian hospitals. The primary outcome was in-hospital mortality. Propensity score analysis matched KT recipients with controls - patients on chronic dialysis and those without CKD (within 0.25 standard deviations of the logit of the propensity score) - according to age, sex, number of comorbidities, and admission year. This study included 555 patients: 163 KT, 146 on chronic dialysis, and 249 non-CKD patients (median age 57 years, 55.2% women). With regards to clinical outcomes, chronic dialysis patients had a higher prevalence of acute heart failure, compared to KT recipients, furthermore, both groups presented high in-hospital mortality, 34.0 and 28.1%, for KT and chronic dialysis patients, respectively. When comparing KT and non-CKD patients, the first group had a higher incidence of in-hospital dialysis (26.4% vs. 8.8%, p < 0.001), septic shock (24.1% vs. 12.0%, p = 0.002), and mortality (32.5% vs. 23.3%, p = 0.039), in addition to longer time spent in the intensive care unit (ICU). In this study, chronic dialysis patients presented a higher prevalence of acute heart failure, compared to KT recipients, whereas KT patients had a higher frequency of complications than those without CKD, including septic shock, dialysis during hospitalization, and in-hospital mortality as well as longer time spent in the ICU.

Kidney transplant recipients (KTRs) are at risk of severe coronavirus disease 2019 (COVID-19), and even now that Omicron subvariants have become dominant, cases of severe disease are certain to occur. The aims of this retrospective study were to evaluate the efficacy of antiviral treatment for COVID-19 and to identify risk factors for severe disease in KTRs during Omicron subvariant-dominant periods.

A total of 65 KTRs diagnosed with COVID-19 who received antiviral treatment between July 2022 and September 2023 were analyzed. Mild cases received oral molnupiravir (MP) as outpatient therapy, while moderate or worse cases received intravenous remdesivir (RDV) as inpatient therapy. In principle, mycophenolate mofetil was withdrawn and switched to everolimus. We investigated the efficacy of antiviral treatment and compared the clinical parameters of mild/moderate and severe/critical cases to identify risk factors for severe COVID-19.

Among 65 cases, 49 were mild, 6 were moderate, 9 were severe, and 1 was of critical severity. MP was administered to 57 cases; 49 (86%) improved and 8 (14%) progressed. RDV was administered to 16 cases; 14 (87%) improved and 2 (13%) progressed. Seventeen (26%) cases required hospitalization, and none died. Comparisons of the severe/critical group (n = 10) with the mild/moderate group (n = 55) demonstrated that the severe/critical group had a significantly higher median age (64 vs. 53 years, respectively; p = 0.0252), prevalence of diabetes (70% vs. 22%, respectively; p = 0.0047) and overweight/obesity (40% vs. 11%, respectively; p = 0.0393), as well as a significantly longer median time from symptom onset to initial antiviral therapy (3 days vs. 1 day, respectively; p = 0.0026). Multivariate analysis showed that a longer time from symptom onset to initial antiviral treatment was an independent risk factor for severe COVID-19 (p = 0.0196, odds ratio 1.625, 95% confidence interval 1.081-2.441).

These findings suggest that a longer time from symptom onset to initial antiviral treatment is associated with a higher risk of severe COVID-19 in KTRs. Initiating antiviral treatment as early as possible is crucial for preventing severe outcomes; this represents a valuable insight into COVID-19 management in KTRs.

The increasing use of electronic health records (EHR) based computable phenotypes in clinical research is providing new opportunities for development of data-driven medical applications. Adopted widely in the United States and globally, EHRs facilitate systematic collection of patients' longitudinal information, which serves as one of the important foundations for artificial intelligence applications in medicine. Harmonization of input variables and outcome definitions is critically important for wider clinical applicability of artificial intelligence (AI) methodologies. In this review, we focused on Coronavirus Disease 2019 (COVID-19) severity machine learning prediction models and explored the pipeline for standardizing future disease severity model development using EHR information. We identified 2,967 studies published between 01/01/2020 and 02/15/2022 and selected 135 independent studies that had built machine learning prediction models to predict severity related outcomes of COVID-19 patients based on EHR data for the final review. These 135 studies spanning across 27 counties covered a broad range of severity related prediction outcomes. We observed substantial inconsistency in COVID-19 severity phenotype definitions among models in these studies. Moreover, there was a gap between the outcome of these models and clinician-recognized clinical concepts. Accordingly, we recommend that robust clinical input metrics, with outcome definitions which eliminate ambiguity in interpretation, to reduce algorithmic bias, mitigate model brittleness and improve generalizability of a universal model for COVID-19 severity. This framework can potentially be extended to broader clinical application.

Prolonged symptoms after corona virus disease 2019 (Long-COVID) in dialysis-dependent patients and kidney transplant (KT) recipients are important as a possible risk factor for organ dysfunctions, especially gastrointestinal (GI) problems, during immunosuppressive therapy.

To identify the characteristics of GI manifestations of Long-COVID in patients with dialysis-dependent or KT status.

This observational, prospective study included patients with COVID-19 infection, confirmed by reverse transcription polymerase chain reaction, with the onset of symptoms between 1 January 2022 and 31 July 2022 which was explored at 3 mo after the onset, either through the out-patient follow-up or by telephone interviews.

The 645 eligible participants consisted of 588 cases with hemodialysis (HD), 38 patients with peritoneal dialysis (PD), and 19 KT recipients who were hospitalized with COVID-19 infection during the observation. Of these, 577 (89.5%) cases agreed to the interviews, while 64 (10.9%) patients with HD and 4 (10.5%) cases of PD were excluded. The mean age was 52 ± 11 years with 52% women. The median dialysis duration was 7 ± 3 and 5 ± 1 years for HD and PD groups, respectively, and the median time post-transplantation was 6 ± 2 years. Long-COVID was identified in 293/524 (56%) and 21/34 (62%) in HD and PD, respectively, and 7/19 (37%) KT recipients. Fatigue was the most prevalent (96%) of the non-GI tract symptoms, whereas anorexia (90.9%), loss of taste (64.4%), and abdominal pain (62.5%) were the first three common GI manifestations of Long-COVID. Notably, there were 6 cases of mesenteric panniculitis from 19 patients with GI symptoms in the KT group.

Different from patients with non-chronic kidney disease, there was a high prevalence of GI manifestations of Long-COVID in dialysis-dependent patients and KT recipients. An appropriate long-term follow-up in these vulnerable populations after COVID-19 infection is possibly necessary.

There are limited data on the performance of laboratory-derived biomarkers in kidney transplant recipients (KTR) with COVID-19. This observational study enrolled 65 KTR with COVID-19 who were treated at the University Hospital of Split up to March 2022. Laboratory-derived biomarkers (neutrophile-to-lymphocyte (NLR) ratio, platelet-to-lymphocyte ratio, monocyte-to-lymphocyte ratio, De Ritis ratio, C-reactive protein (CRP)-to-albumin ratio, lactate dehydrogenase (LDH)-to-hemoglobin ratio, CRP-to-lymphocyte ratio, red cell distribution width-to-albumin ratio, platelet-to-albumin ratio, D-Dimer-to-albumin ratio, D-Dimer-to-NLR ratio, LDH-to-albumin ratio, and LDH-to-white blood cell (WBC) ratio) were calculated, and their performance with regard to 30-day mortality was determined. Mortality events occurred in 12 patients (18.5%), which was significantly associated with increased De Ritis (HR 3.83, 95% CI 1.57-9.35, p = 0.003), CRP-to-albumin (HR 1.36, 95% CI 1.13-1.64, p = 0.001), LDH-to-hemoglobin (HR 1.44, 95% CI 1.07-1.92, p = 0.015), CRP-to-lymphocyte (HR 1.03, 95% CI 1.01-1.07, p = 0.003), D-dimer-to-albumin (HR 4.94, 95% CI 1.38-7.24, p = 0.038), LDH-to-albumin (HR 1.20, 95% CI 1.05-1.36, p = 0.008), and LDH-to-WBC (HR 1.03 95% CI 1.01-1.05, p = 0.024) ratios. Out of these, the best area-under-the-curve (AUC) values were achieved with De Ritis (AUC 0.691), CRP-to-albumin (AUC 0.764), LDH-to-hemoglobin (AUC 0.877), CRP-to-lymphocyte (AUC 0.739), and LDH-to-albumin (AUC 0.827) ratios, while the best discrimination displayed LDH-to-hemoglobin ratio (Harrell's C 0.808 and Somers' D 0.616). The overall calibration was satisfactory for all models. Derived laboratory biomarkers such as the de Ritis, CRP-to-albumin, LDH-to-hemoglobin, CRP-to-lymphocyte, and LDH-to-albumin ratios show significant association and discrimination with all-cause mortality in KTR with COVID-19, suggesting its potential risk stratification role.

Kidney transplant recipients are at a higher risk to develop more severe clinical forms of coronavirus disease 2019 (COVID-19), perhaps increasing the risk of presenting its long-term clinical complications, labeled as Long-COVID.

This single-center, observational, prospective study included adult kidney transplant recipients with COVID-19 confirmed by reverse transcription polymerase chain reaction between March 20, 2020, and May 31, 2021, who were alive and with functioning graft 3 mo after the onset of symptoms. The prevalence of Long-COVID was investigated by a phone survey using a structured questionnaire of organic symptoms. Adjusted multivariable logistic regression models were used to investigate independent risk factors.

Of 1741 patients who developed COVID-19, 465 died, and 37 returned to dialysis. Of the 1239 eligible patients, 780 (63%) answered the survey during the window period. The mean age was 48 ± 12 y, 41% were women, and the mean time from transplantation was 8 ± 6 y. During acute illness, 45% needed hospitalization. Long-COVID was identified in 214 (27%) of the subjects, with body aches being the most prevalent symptom (44%). Of 233 who provided working status, 17% did not return to work within 3 mo. No baseline characteristics or infection-related variables predicted Long-COVID; actually, the number of symptoms in the acute illness was the only independent risk factor identified (hazard ratio, 1.12; 95% confidence interval, 1.02-1.22).

In this cohort of kidney transplant recipients, Long-COVID was prevalent and associated with a reduced return to work. The burden of acute phase symptoms was the only risk factor associated with Long-COVID.

The chronic use of immunosuppressive drugs is a key risk factor of death because of coronavirus disease 2019 (COVID-19) in kidney transplant recipients (KTRs), although no evident association between the class of immunosuppressive and outcomes has been observed. Thus, we aimed to compare COVID-19-associated outcomes among KTRs receiving 3 different immunosuppressive maintenance regimes.

This study included data from 1833 KTRs with COVID-19 diagnosed between March 20 and April 21 extracted from the national registry before immunization. All patients were taking calcineurin inhibitor associated with mycophenolate acid (MPA, n = 1258), azathioprine (AZA, n = 389), or mammalian targets of rapamycin inhibitors (mTORi, n = 186). Outcomes within 30 and 90 d were assessed.

Compared with patients receiving MPA, the 30-d (79.9% versus 87.9% versus 89.2%; P < 0.0001) and 90-d (75% versus 83.5% versus 88.2%; P < 0.0001) unadjusted patient survivals were higher in those receiving AZA or mTORi, respectively. Using adjusted multivariable Cox regression, compared with patients receiving AZA, the use of MPA was associated with a higher risk of death within 30 d (adjusted hazard ratio [aHR], 1.70; 95% confidence interval [CI], 1.21-2.40; P = 0.003), which was not observed in patients using mTORi (aHR, 0.78; 95% CI, 0.45-1.35; P = 0.365). At 90 d, although higher risk of death was confirmed in patients receiving MPA (aHR, 1.46; 95% CI, 1.09-1.98; P = 0.013), a reduced risk was observed in patients receiving mTORi (aHR, 0.59; 95% CI, 0.35-0.97; P = 0.04) compared with AZA.

This national cohort data suggest that, in KTRs receiving calcineurin inhibitor and diagnosed with COVID-19, the use of MPA was associated with higher risk of death, whereas mTORi use was associated with lower risk of death.

Patients with novel coronavirus disease 2019 (COVID-19) worsen into critical illness suddenly is a matter of great concern. Early identification and effective triaging of patients with a high risk of developing critical illness COVID-19 upon admission can aid in improving patient care, increasing the cure rate, and mitigating the burden on the medical care system. This study proposed and extended classical least absolute shrinkage and selection operator (LASSO) logistic regression to objectively identify clinical determination and risk factors for the early identification of patients at high risk of progression to critical illness at the time of hospital admission.

In this retrospective multicenter study, data of 1,929 patients with COVID-19 were assessed. The association between laboratory characteristics measured at admission and critical illness was screened with logistic regression. LASSO logistic regression was utilized to construct predictive models for estimating the risk that a patient with COVID-19 will develop a critical illness.

The development cohort consisted of 1,363 patients with COVID-19 with 133 (9.7%) patients developing the critical illness. Univariate logistic regression analysis revealed 28 variables were prognosis factors for critical illness COVID-19 (p < 0.05). Elevated CK-MB, neutrophils, PCT, α-HBDH, D-dimer, LDH, glucose, PT, APTT, RDW (SD and CV), fibrinogen, and AST were predictors for the early identification of patients at high risk of progression to critical illness. Lymphopenia, a low rate of basophils, eosinophils, thrombopenia, red blood cell, hematocrit, hemoglobin concentration, blood platelet count, and decreased levels of K, Na, albumin, albumin to globulin ratio, and uric acid were clinical determinations associated with the development of critical illness at the time of hospital admission. The risk score accurately predicted critical illness in the development cohort [area under the curve (AUC) = 0.83, 95% CI: 0.78-0.86], also in the external validation cohort (n = 566, AUC = 0.84).

A risk prediction model based on laboratory findings of patients with COVID-19 was developed for the early identification of patients at high risk of progression to critical illness. This cohort study identified 28 indicators associated with critical illness of patients with COVID-19. The risk model might contribute to the treatment of critical illness disease as early as possible and allow for optimized use of medical resources.

Immunosuppression increases the risk of severe coronavirus disease 2019 (COVID-19). Morbidity and mortality of this disease in kidney transplant patients are higher than in the general population. As the vaccination response of transplant patients is weak, serological monitoring was performed. In this cohort study, we analyzed the determinants of vaccination response. All patients had no history of COVID-19. With anti-spike IgG monitoring, 148 responders and 415 non-responders were identified. We compared both groups using multivariate analyses of the cohort and a sub-cohort of mycophenolic-acid-treated patients. We investigated the influence of patient characteristics, immunosuppression, and erythrocyte inosine monophosphate dehydrogenase (IMPDH) activity. In responders, the time after transplantation was longer (13.5 vs. 8.5 years), the glomerular filtration rate was higher (56.9 vs. 47.8 mL/min/1.73 m2), and responders were younger (53.0 vs. 57.4 years). Heterologous vaccination was more effective than homologous vaccination. Calcineurin inhibitors plus mycophenolate reduced the seroconversion rate. No seroconversion was observed in belatacept patients. In mycophenolate-treated patients, IMPDH activity was a significantly better predictor of response than mycophenolate dose (AUC 0.84 vs. 0.62, p < 0.001). Immunosuppression strongly affects vaccine response. Modifications to immunosuppression should be considered in order to facilitate this response. Erythrocyte IMPDH activity can be used to guide mycophenolate treatment.

This analysis, using data from the Brazilian kidney transplant (KT) COVID-19 study, seeks to develop a prediction score to assist in COVID-19 risk stratification in KT recipients. In this study, 1379 patients (35 sites) were enrolled, and a machine learning approach was used to fit models in a derivation cohort. A reduced Elastic Net model was selected, and the accuracy to predict the 28-day fatality after the COVID-19 diagnosis, assessed by the area under the ROC curve (AUC-ROC), was confirmed in a validation cohort. The better calibration values were used to build the applicable ImAgeS score. The 28-day fatality rate was 17% (n = 235), which was associated with increasing age, hypertension and cardiovascular disease, higher body mass index, dyspnea, and use of mycophenolate acid or azathioprine. Higher kidney graft function, longer time of symptoms until COVID-19 diagnosis, presence of anosmia or coryza, and use of mTOR inhibitor were associated with reduced risk of death. The coefficients of the best model were used to build the predictive score, which achieved an AUC-ROC of 0.767 (95% CI 0.698-0.834) in the validation cohort. In conclusion, the easily applicable predictive model could assist health care practitioners in identifying non-hospitalized kidney transplant patients that may require more intensive monitoring. Trial registration: ClinicalTrials.gov NCT04494776.

Kidney transplant recipients (KTR) are a group of patients with heterogeneous risks for adverse outcomes with COVID-19, but risk stratification tools in this patient group are lacking.

This retrospective observational, hypothesis-generating study included 49 hospitalized adult KTR patients with COVID-19 at the University Hospital of Split (August 2020 to October 2021) and evaluated the performance of novel risk score CROW-65 (age, Charlson Comorbidity Index [CCI] lactate dehydrogenase to white blood cell [LDH:WBC] ratio, and respiratory rate oxygenation [ROX index]). The primary outcome of the study was 30-day postdischarge all-cause mortality.

A total of 8 fatal events (16.3%) occurred during the study follow-up. When comparing CROW-65 by survival status, it was significantly increased in patients with fatal event (P < 0.001). Using the Cox proportional hazards regression analysis, the CROW-65 risk score showed statistically significant association with mortality (HR 1.11, 95% CI 1.01-1.23, P = 0.027), while receiving operator characteristics (ROC) showed significant discrimination of all-cause mortality with an AUC of 0.85 (95% CI 0.72-0.94, P < 0.001), and satisfactory calibration (χ² 4.91, P = 0.555 and Harrell's C 0.835). Finally, survival Kaplan-Meier analysis confirmed significantly higher cumulative incidence of mortality with increasing risk score tertiles and curve separation after 13 days (P = 0.009).

A novel risk score CROW-65 showed significant association with all-cause mortality in KTR yielding important hypothesis-generating findings. Further powered studies should reassess the performance of CROW-65 risk score in this population, including predictability, calibration and discrimination.

Casirivimab-imdevimab is a cocktail of 2 monoclonal antibodies designed to prevent infection by SARS-CoV-2, the virus that causes COVID-19. Casirivimab-imdevimab has been approved in Japan for treating mild to moderate COVID-19; however, to our knowledge, there are no reports of its use after kidney transplant from a live donor. Everolimus, an antineoplastic chemotherapy drug, is expected to be effective in inhibiting the spread of SARS-CoV-2 and preventing its replication, which may facilitate treatment. Here, we report a case of COVID-19 infection after kidney transplant that was initially treated with casirivimab-imdevimab and mycophenolate mofetil but was later changed to everolimus.

A 47-year-old man underwent living donor kidney transplant from his mother in 2017. Immunosuppression therapy was underway through the administration of tacrolimus, mycophenolate mofetil, and methylprednisolone. In early September 2021, he was diagnosed as having COVID-19 and was hospitalized on day 3. On hospitalization, mycophenolate mofetil was discontinued and casirivimab-imdevimab and heparin were started. The patient started an everolimus regimen on day 5. The clinical course was successful without rejection. There was no exacerbation of COVID-19; the patient's serum creatinine levels and renal function had otherwise remained stable.

We could safely treat a patient with casirivimab-imdevimab after kidney transplant. It is suggested that casirivimab-imdevimab can prevent COVID-19 from becoming severe and can be administered without worsening renal function. In addition, everolimus may have inhibited the spread of the virus and prevented it from replicating.

Several studies of patients with COVID-19 have evaluated biological markers for predicting outcomes, most of them retrospectively and with a wide scope of clinical severity. We followed a prospective cohort of patients admitted in hospital wards with moderate COVID-19 disease, including those with a history of kidney transplantation, and examined the ability of changes in routine hematologic laboratory parameters to predict and mirror the patients' clinical course regarding the severity of their condition (classified as critical vs. non-critical) and in-hospital mortality or hospital discharge. Among the 68 patients, 20 (29%) were kidney transplanted patients (KT), and they had much higher mortality than non-kidney transplanted patients in this cohort (40% X 8.3%). Lymphocytes, neutrophils and neutrophils/lymphocytes ratio (NLR) at admission and platelets as well as the red blood cells parameters hemoglobin, hematocrit, and RDW by the time of hospital discharge or death clearly differentiated patients progressing to critical disease and those with clinical recovery. Patients with deteriorating clinical courses presented elevated and similar NLRs during the first week of hospitalization. However, they were dramatically different at hospital discharge, with a decrease in the survivors (NLR around 5.5) and sustained elevation in non-survivors (NLR around 21). Platelets also could distinguish survivors from non-survivors among the critical patients. In conclusion, routine hematologic tests are useful to monitor the clinical course of COVID-19 patients admitted with moderate disease. Unexpectedly, changes in hematologic tests, including lymphopenia, were not predictive of complicated outcomes among KT recipients.