Incidence and risk factors of kidney impairment on patients with COVID-19: A meta-analysis of 10180 patients

Evidence for the utility of cfDNA plasma concentrations to predict disease severity in COVID-19: a retrospective pilot study

Background

COVID-19 is a worldwide pandemic caused by the highly infective SARS-CoV-2. There is a need for biomarkers not only for overall prognosis but also for predicting the response to treatments and thus for improvements in the clinical management of patients with COVID-19. Circulating cell-free DNA (cfDNA) has emerged as a promising biomarker in the assessment of various pathological conditions. The aim of this retrospective and observational pilot study was to investigate the range of cfDNA plasma concentrations in hospitalized COVID-19 patients during the first wave of SARS-CoV-2 infection, to relate them to established inflammatory parameters as a correlative biomarker for disease severity, and to compare them with plasma levels in a healthy control group.

Methods

Lithium-Heparin plasma samples were obtained from COVID-19 patients (n = 21) during hospitalization in the University Medical Centre of Mainz, Germany between March and June 2020, and the cfDNA concentrations were determined by quantitative PCR yielding amplicons of long interspersed nuclear elements (LINE-1). The cfDNA levels were compared with those of an uninfected control group (n = 19).

Results

Plasma cfDNA levels in COVID-19 patients ranged from 247.5 to 6,346.25 ng/ml and the mean concentration was 1,831 ± 1,388 ng/ml (± standard deviation), which was significantly different from the levels of the uninfected control group (p < 0.001). Regarding clinical complications, the highest correlation was found between cfDNA levels and the myositis (p = 0.049). In addition, cfDNA levels correlated with the "WHO clinical progression scale". D-Dimer and C-reactive protein (CRP) were the clinical laboratory parameters with the highest correlations with cfDNA levels.

Conclusion

The results of this observational pilot study show a wide range in cfDNA plasma concentrations in patients with COVID-19 during the first wave of infection and confirm that cfDNA plasma concentrations serve as a predictive biomarker of disease severity in COVID-19.

COVID-19 Infection and Outcomes in Newborn Screening Cohorts of Sickle Cell Trait and Sickle Cell Disease in Michigan and Georgia

The sickle cell mutation increases morbidity in those with sickle cell disease (SCD) and potentially sickle cell trait, impacting pulmonary, coagulation, renal, and other systems that are implicated in COVID-19 severity. There are no population-based registries for hemoglobinopathies, and they are not tracked in COVID-19 testing. We used COVID-19 test data from 2 states linked to newborn screening data to estimate COVID outcomes in people with SCD or trait compared with normal hemoglobin. We linked historical newborn screening data to COVID-19 tests, hospitalization, and mortality data and modeled the odds of hospitalization and mortality. Georgia's cohort aged 0 to 12 years; Michigan's, 0 to 33 years. Over 8% of those in Michigan were linked to positive COVID-19 results, and 4% in Georgia. Those with SCD showed significantly higher rates of COVID-19 hospitalization than the normal hemoglobin Black cohort, and Michigan had higher rates of mortality as well. Outcomes among those with the trait did not differ significantly from the normal hemoglobin Black group. People with SCD are at increased risk of COVID-19-related hospitalization and mortality and are encouraged to be vaccinated and avoid infection. Persons with the trait were not at higher risk of COVID-related severe outcomes.

Headache associated with COVID‐19: Epidemiology, characteristics, pathophysiology, and management

Objective

Background

Method

Results

Conclusions

Proteomic landscape of SARS-CoV-2- and MERS-CoV-infected primary human renal epithelial cells

Acute kidney injury is associated with mortality in COVID-19 patients. However, host cell changes underlying infection of renal cells with SARS-CoV-2 remain unknown and prevent understanding of the molecular mechanisms that may contribute to renal pathology. Here, we carried out quantitative translatome and whole-cell proteomics analyses of primary renal proximal and distal tubular epithelial cells derived from human donors infected with SARS-CoV-2 or MERS-CoV to disseminate virus and cell type-specific changes over time. Our findings revealed shared pathways modified upon infection with both viruses, as well as SARS-CoV-2-specific host cell modulation driving key changes in innate immune activation and cellular protein quality control. Notably, MERS-CoV infection-induced specific changes in mitochondrial biology that were not observed in response to SARS-CoV-2 infection. Furthermore, we identified extensive modulation in pathways associated with kidney failure that changed in a virus- and cell type-specific manner. In summary, we provide an overview of the effects of SARS-CoV-2 or MERS-CoV infection on primary renal epithelial cells revealing key pathways that may be essential for viral replication.

Renal involvement in COVID-19: focus on kidney transplant sector

INTRODUCTION

Kidney transplant recipients and patients on the waiting list for kidney transplant who acquire SARS-CoV-2 infection are at serious risk of developing severe COVID-19, with an increased risk of mortality for the their immunosuppressive state; other risk factors for mortality have been identified in some comorbidities such as obesity, diabetes, asthma and chronic lung disease.

MATERIALS AND METHODS

The COVID-19 pandemic has led to a sharp reduction in kidney transplants in most countries, mainly due to the concern of patients on the waiting list for their potential increased susceptibility to acquire SARS-CoV-2 infection in healthcare facilities and for the difficulties of transplant centers to ensure full activity as hospitals have had to focus most of their attention on COVID-19 patients. Indeed, while the infection curve continued its exponential rise, there was a vertical decline in kidney donation/transplant activity.

CONCLUSION

This review article focuses on the damage induced by SARS-CoV-2 infection on kidney and on the adverse effect of this pandemic on the entire kidney transplant sector.

A validation study of UCSD-Mayo risk score in predicting hospital-acquired acute kidney injury in COVID-19 patients

Introduction

Acute kidney injury (AKI) in coronavirus disease 2019 (COVID-19) patients is associated with poor prognosis. Early prediction and intervention of AKI are vital for improving clinical outcome of COVID-19 patients. As lack of tools for early AKI detection in COVID-19 patients, this study aimed to validate the USCD-Mayo risk score in predicting hospital-acquired AKI in an extended multi-center COVID-19 cohort.

Methods

Five hundred seventy-two COVID-19 patients from Wuhan Tongji Hospital Guanggu Branch, Wuhan Leishenshan Hospital, and Wuhan No. Ninth Hospital was enrolled for this study. Patients who developed AKI or reached an outcome of recovery or death during the study period were included. Predictors were evaluated according to data extracted from medical records.

Results

Of all patients, a total of 44 (8%) developed AKI. The UCSD-Mayo risk score achieved excellent discrimination in predicting AKI with the C-statistic of 0.88 (95%CI: 0.84–0.91). Next, we determined the UCSD-Mayo risk score had good overall performance (Nagelkerke R² = 0.32) and calibration in our cohort. Further analysis showed that the UCSD-Mayo risk score performed well in subgroups defined by gender, age, and several chronic comorbidities. However, the discrimination of the UCSD-Mayo risk score in ICU patients and patients with mechanical ventilation was not good which might be resulted from different risk factors of these patients.

Conclusions

We validated the performance of UCSD-Mayo risk score in predicting hospital-acquired AKI in COVID-19 patients was excellent except for patients from ICU or patients with mechanical ventilation.

Association of Clinical and Immunological Characteristics With Disease Severity and Outcomes in 211 Patients With COVID-19 in Wuhan, China

Background

Coronavirus disease 2019 (COVID-19) has posed a great threat to global public health. There remains an urgent need to address the clinical significance of laboratory finding changes in predicting disease progression in COVID-19 patients. We aimed to analyze the clinical and immunological features of severe and critically severe patients with COVID-19 in comparison with non-severe patients and identify risk factors for disease severity and clinical outcome in COVID-19 patients.

Methods

The consecutive records of 211 patients with COVID-19 who were admitted to Zhongnan Hospital of Wuhan University from December 2019 to February 2020 were retrospectively reviewed.

Results

Of the 211 patients with COVID-19 recruited, 111 patients were classified as non-severe, 59 as severe, and 41 as critically severe cases. The median age was obviously higher in severe and critically severe cases than in non-severe cases. Severe and critically severe patients showed more underlying comorbidities than non-severe patients. Fever was the predominant presenting symptom in COVID-19 patients, and the duration of fever was longer in critically severe patients. Moreover, patients with increased levels of serum aminotransferases and creatinine (CREA) were at a higher risk for severe and critical COVID-19 presentations. The serum levels of IL-6 in severe and critically severe patients were remarkably higher than in non-severe patients. Lymphopenia was more pronounced in severe and critically severe patients compared with non-severe patients. Lymphocyte subset analysis indicated that severe and critically severe patients had significantly decreased count of lymphocyte subpopulations, such as CD4+ T cells, CD8+ T cells and B cells. A multivariate logistic analysis indicated that older age, male sex, the length of hospital stay, body temperature before admission, comorbidities, higher white blood cell (WBC) counts, lower lymphocyte counts, and increased levels of IL-6 were significantly associated with predicting the progression to severe stage of COVID-19.

Conclusion

Older age, male sex, underlying illness, sustained fever status, abnormal liver and renal functions, excessive expression of IL-6, lymphopenia, and selective loss of peripheral lymphocyte subsets were related to disease deterioration and clinical outcome in COVID-19 patients. This study would provide clinicians with valuable information for risk evaluation and effective interventions for COVID-19.

Machine learning-based prognostic modeling using clinical data and quantitative radiomic features from chest CT images in COVID-19 patients

OBJECTIVE

To develop prognostic models for survival (alive or deceased status) prediction of COVID-19 patients using clinical data (demographics and history, laboratory tests, visual scoring by radiologists) and lung/lesion radiomic features extracted from chest CT images.

METHODS

Overall, 152 patients were enrolled in this study protocol. These were divided into 106 training/validation and 46 test datasets (untouched during training), respectively. Radiomic features were extracted from the segmented lungs and infectious lesions separately from chest CT images. Clinical data, including patients' history and demographics, laboratory tests and radiological scores were also collected. Univariate analysis was first performed (q-value reported after false discovery rate (FDR) correction) to determine the most predictive features among all imaging and clinical data. Prognostic modeling of survival was performed using radiomic features and clinical data, separately or in combination. Maximum relevance minimum redundancy (MRMR) and XGBoost were used for feature selection and classification. The receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC), sensitivity, specificity, and accuracy were used to assess the prognostic performance of the models on the test datasets.

RESULTS

For clinical data, cancer comorbidity (q-value < 0.01), consciousness level (q-value < 0.05) and radiological score involved zone (q-value < 0.02) were found to have high correlated features with outcome. Oxygen saturation (AUC = 0.73, q-value < 0.01) and Blood Urea Nitrogen (AUC = 0.72, q-value = 0.72) were identified as high clinical features. For lung radiomic features, SAHGLE (AUC = 0.70) and HGLZE (AUC = 0.67) from GLSZM were identified as most prognostic features. Amongst lesion radiomic features, RLNU from GLRLM (AUC = 0.73), HGLZE from GLSZM (AUC = 0.73) had the highest performance. In multivariate analysis, combining lung, lesion and clinical features was determined to provide the most accurate prognostic model (AUC = 0.95 ± 0.029 (95%CI: 0.95-0.96), accuracy = 0.88 ± 0.046 (95% CI: 0.88-0.89), sensitivity = 0.88 ± 0.066 (95% CI = 0.87-0.9) and specificity = 0.89 ± 0.07 (95% CI = 0.87-0.9)).

CONCLUSION

Combination of radiomic features and clinical data can effectively predict outcome in COVID-19 patients. The developed model has significant potential for improved management of COVID-19 patients.

COVID-19 after kidney transplantation: Early outcomes and renal function following antiviral treatment

Objectives

The lack of effective treatments for coronavirus disease 2019 (COVID-19) has mandated the repurposing of several drugs, including antiretrovirals and remdesivir (RDV). These compounds may induce acute kidney injury and are not recommended in patients with poor renal function, such as kidney transplant (KTx) recipients.

Methods

The records of 42 KTx recipients with COVID-19 were reviewed. Some of them were receiving antiretrovirals (n = 10) or RDV (n = 8) as part of COVID-19 management. Most patients were male (71%) and their median age was 52 years. The median glomerular filtration rate in these patients was 56 ml/min. Regarding disease severity, 36% had mild disease, 19% had moderate disease, 31% had severe disease, and 12% had critical disease. Subgroups, i.e., patients receiving antiretrovirals, RDV, or no antivirals, were comparable in terms of patient age, comorbidities, and immunosuppression.

Results

Seven patients (16.6%) died during hospitalization. Acute kidney injury was found in 24% of KTx recipients at admission. Upon discharge, estimated glomerular filtration rate (eGFR) increased in 32% and decreased in 39% of the KTx recipients compared with the admission rate. The decrease was more prevalent in the RDV group (80%) compared with KTx recipients without any antiviral treatment (29%) (p <  0.05). Most patients (62%) returned to baseline eGFR values within 1 month of discharge. The proportion was similar between the patients receiving antiviral treatment and those not receiving this treatment.

Conclusions

KTx recipients run a high risk of COVID-19-related renal impairment. Antivirals appear to be safe for use without major risks for kidney injury.