Serum cystatin C and inflammatory factors related to COVID-19 consequences

Research on the global trends of COVID-19 associated acute kidney injury: a bibliometric analysis

Critically ill COVID-19 patients may exhibit various clinical symptoms of renal dysfunction including severe Acute Kidney Injury (AKI). Currently, there is a lack of bibliometric analyses on COVID-19-related AKI. The aim of this study is to provide an overview of the current research status and hot topics regarding COVID-19 AKI. The literature was retrieved from the Web of Science Core Collection (WoSCC) database. Subsequently, we utilized Microsoft Excel, VOSviewer, Citespace, and Pajek software to revealed the current research status, emerging topics, and developmental trends pertaining to COVID-19 AKI. This study encompassed a total of 1507 studies on COVID-19 AKI. The United States, China, and Italy emerged as the leading three countries in terms of publication numbers, contributing 498 (33.05%), 229 (15.20%), and 140 (9.29%) studies, respectively. The three most active and influential institutions include Huazhong University of Science and Technology, Wuhan University and Harvard Medical School. Ronco C from Italy, holds the record for the highest number of publications, with a total of 15 papers authored. Cheng YC's work from China has garnered the highest number of citations, totaling 470 citations. The co-occurrence analysis of author keywords reveals that 'mortality', 'intensive care units', 'chronic kidney disease', 'nephrology', 'renal transplantation', 'acute respiratory distress syndrome', and 'risk factors' emerge as the primary areas of focus within the realm of COVID-19 AKI. In summary, this study analyzes the research trends in the field of COVID-19 AKI, providing a reference for further exploration and research on COVID-19 AKI mechanisms and treatment.

Predicting COVID-19 Re-Positive Cases in Malnourished Older Adults: A Clinical Model Development and Validation

Purpose

Building and validating a clinical prediction model for novel coronavirus (COVID-19) re-positive cases in malnourished older adults.

Patients and Methods

Malnourished older adults from January to May 2023 were retrospectively collected from the Department of Geriatrics of the Affiliated Hospital of Chengdu University of Traditional Chinese Medicine. They were divided into a "non-re-positive" group and a "re-positive" group based on the number of COVID-19 infections, and into a training set and a validation set at a 7:3 ratio. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to identify predictive factors for COVID-19 re-positivity in malnourished older adults, and a nomogram was constructed. Independent influencing factors were screened by multivariate logistic regression. The model's goodness-of-fit, discrimination, calibration, and clinical impact were assessed by Hosmer-Lemeshow test, area under the curve (AUC), calibration curve, decision curve analysis (DCA), and clinical impact curve analysis (CIC), respectively.

Results

We included 347 cases, 243 in the training set, and 104 in the validation set. We screened 10 variables as factors influencing the outcome. By multivariate logistic regression analysis, preliminary identified protective factors, risk factors, and independent influencing factors that affect the re-positive outcome. We constructed a clinical prediction model for COVID-19 re-positivity in malnourished older adults. The Hosmer-Lemeshow test yielded χ2 =5.916, P =0.657; the AUC was 0.881; when the threshold probability was >8%, using this model to predict whether malnourished older adults were re-positive for COVID-19 was more beneficial than implementing intervention programs for all patients; when the threshold was >80%, the positive estimated value was closer to the actual number of cases.

Conclusion

This model can help identify the risk of COVID-19 re-positivity in malnourished older adults early, facilitate early clinical decision-making and intervention, and have important implications for improving patient outcomes. We also expect more large-scale, multicenter studies to further validate, refine, and update this model.

Genome-wide association analysis of cystatin-C kidney function in continental Africa

BACKGROUND

Chronic kidney disease is becoming more prevalent in Africa, and its genetic determinants are poorly understood. Creatinine-based estimated glomerular filtration rate (eGFR) is commonly used to estimate kidney function, modelling the excretion of the endogenous biomarker (creatinine). However, eGFR based on creatinine has been shown to inadequately detect individuals with low kidney function in Sub-Saharan Africa, with eGFR based on cystatin-C (eGFRcys) exhibiting significantly superior performance. Therefore, we opted to conduct a GWAS for eGFRcys.

METHODS

Using the Uganda Genomic Resource, we performed a genome-wide association study (GWAS) of eGFRcys in 5877 Ugandans and evaluated replication in independent studies. Subsequently, putative causal variants were screened through Bayesian fine-mapping. Functional annotation of the GWAS loci was performed using Functional Mapping and Annotation (FUMA).

FINDINGS

Three independent lead single nucleotide polymorphisms (SNPs) (P-value <5 × 10-8 (based on likelihood ratio test (LRT))) were identified; rs59288815 (ANK3), rs4277141 (OR51B5) and rs911119 (CST3). From fine-mapping, rs59288815 and rs911119 each had a posterior probability of causality of >99%. The rs911119 SNP maps to the cystatin C gene and has been previously associated with eGFRcys among Europeans. With gene-set enrichment analyses of the olfactory receptor family 51 overlapping genes, we identified an association with the G-alpha-S signalling events.

INTERPRETATION

Our study found two previously unreported associated SNPs for eGFRcys in continental Africans (rs59288815 and rs4277141) and validated a previously well-established SNP (rs911119) for eGFRcys. The identified gene-set enrichment for the G-protein signalling pathways relates to the capacity of the kidney to readily adapt to an ever-changing environment. Additional GWASs are required to represent the diverse regions in Africa.

FUNDING

Wellcome (220740/Z/20/Z).