ArticleJournal of clinical medicine2021
Low eGFR Is a Strong Predictor of Worse Outcome in Hospitalized COVID-19 Patients.
Article in Journal of clinical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 26 citations in OpenAlex.
- The influence of hypoxia in predicting COVID-19 mortality in patients with kidney dysfunction on admission in 2 centers in sub-Saharan Africa.Renal failure · 2026Article
- Post-nephrectomy outcomes in COVID-19 and non-COVID-19 Patients using ACEi, ARB and SGLT2i: a N3C database study.International urology and nephrology · 2026Article
- Estimated glomerular filtration rate in post COVID-19 patients at 3-6 months and 12-18 months after infection.Renal failure · 2025Article
- The Role of Kidney Function in Predicting COVID-19 Severity and Clinical Outcomes: A Retrospective Analysis.Infectious disease reports · 2025Article
- Impact of estimated glomerular filtration rate (eGFR) on in-hospital mortality: an age- and HIV status-specific retrospective cohort study in Uganda.BMC nephrology · 2025Observational
- Unveiling sub-populations in critical care settings: a real-world data approach in COVID-19.Frontiers in public health · 2025Article
- Predicting Intensive Care Unit Admission in COVID-19-Infected Pregnant Women Using Machine Learning.Journal of clinical medicine · 2024Article
- Type 2 diabetes and susceptibility to COVID-19: a machine learning analysis.BMC endocrine disorders · 2024Article
- Lithium in the time of COVID: forever vigilant.International journal of bipolar disorders · 2024Article
- COVID-19 Infection in Autosomal Dominant Polycystic Kidney Disease and Chronic Kidney Disease Patients: Progression of Kidney Disease.Biomedicines · 2024Article
- Efficacy and safety of MP1032 plus standard-of-care compared to standard-of-care in hospitalised patients with COVID-19: a multicentre, randomised double-blind, placebo-controlled phase 2a trial.The Lancet regional health. Europe · 2024Article
- Increased Estimated GFR Is Negatively Associated With the Risk of SARS-CoV-2 Infection and Severe COVID-19 Within Normal to Mildly Decreased Levels: Nested Case-Control Study.Journal of Korean medical science · 2023Article
- Impact of prediabetes with a high risk of diabetes stratified by glycated hemoglobin level on the severity of coronavirus disease 2019 during admission.Diabetology international · 2023Article
- The prognostic value of estimated glomerular filtration rate on admission for death within 30 days among COVID-19 inpatients using fractional polynomial and spline smoothing.International urology and nephrology · 2023Article
- Prognostic Value of Creatinine Levels at Admission on Disease Progression and Mortality in Patients with COVID-19-An Observational Retrospective Study.Pathogens (Basel, Switzerland) · 2023Article
- How to use COVID-19 antiviral drugs in patients with chronic kidney disease.Frontiers in pharmacology · 2023Review
- Differential Bias for Creatinine- and Cystatin C- Derived Estimated Glomerular Filtration Rate in Critical COVID-19.Biomedicines · 2022Article
- Early reduction of estimated Glomerular Filtration Rate (eGFR) predicts poor outcome in acutely ill hospitalized COVID-19 patients firstly admitted to medical regular wards (eGFR-COV19 study).Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2022Article
- Long-short-term memory machine learning of longitudinal clinical data accurately predicts acute kidney injury onset in COVID-19: a two-center study.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe clinical course of COVID-19 is more severe in elderly patients with cardio-metabolic co-morbidities. Chronic kidney disease is considered an independent cardiovascular risk factor. We aimed to evaluate the impact of reduced eGFR on the composite outcome of admission to ICU and death in a sample of consecutive COVID-19 hospitalized patients.
methodsWe retrospectively evaluated clinical records of a consecutive sample of hospitalized COVID-19 patients. A total of 231 patients were considered for statistical analysis. The whole sample was divided in two groups on the basis of eGFR value, e.g., ≥ or <60 mL/min/1.73 m
resultsSeventy-nine (34.2%) patients reached the composite outcome. A total of 64 patients (27.7%) died during hospitalization, and 41 (17.7%) were admitted to the ICU. A significantly higher number of events was present among patients with low eGFR (
conclusionsPatients with reduced eGFR at admission should be considered at high risk for clinical deterioration and death, requiring the best supportive treatment in order to prevent the worst outcome.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.