Observational studyNutrition, metabolism, and cardiovascular diseases : NMCD2020
Common cardiovascular risk factors and in-hospital mortality in 3,894 patients with COVID-19: survival analysis and machine learning-based findings from the multicentre Italian CORIST Study.
Observational study in Nutrition, metabolism, and cardiovascular diseases : NMCD, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04907890 (Long Term Outcomes in COVID-19 Patients Recruited in the CORIST Project), which is not on this map. Cited by 110 papers, 8 of them syntheses that pooled it.
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.
Long Term Outcomes in COVID-19 Patients Recruited in the CORIST Project: Longitudinal Data and Case-control Study
Who cites it
110 citing papers in PubMed, 8 syntheses or guidelines pooled it, 189 citations in OpenAlex.
- Barriers and Facilitators to Patient Acceptance of Artificial Intelligence in Health Care: Systematic Review.Journal of medical Internet research · 2026Pooled it
- Association of Obesity With COVID-19 Severity and Mortality: An Updated Systemic Review, Meta-Analysis, and Meta-Regression.Frontiers in endocrinology · 2022Pooled it
- The isolated effect of age on the risk of COVID-19 severe outcomes: a systematic review with meta-analysis.BMJ global health · 2021Pooled it
- Pooled it
- The effect of cardiovascular disease and acute cardiac injury on fatal COVID-19: a meta-analysis.The American journal of emergency medicine · 2021Pooled it
- Pre-existing health conditions and severe COVID-19 outcomes: an umbrella review approach and meta-analysis of global evidence.BMC medicine · 2021Pooled it
- Chronic Diseases as a Predictor for Severity and Mortality of COVID-19: A Systematic Review With Cumulative Meta-Analysis.Frontiers in medicine · 2021Pooled it
- RAAS inhibitors are not associated with mortality in COVID-19 patients: Findings from an observational multicenter study in Italy and a meta-analysis of 19 studies.Vascular pharmacology · 2020Pooled it
- Death by SARS-CoV 2: a Romanian COVID-19 multi-centre comorbidity study.Scientific reports · 2020Trial
- Article
- Sex-Specific Risk Factors and Predictors of Major Adverse Cardiac and Cerebrovascular Events in Heart Failure with Preserved Ejection Fraction with SARS-CoV-2 Infection: A Nationwide Analysis.Journal of clinical medicine · 2025Article
- Surfactant-derived protein type B: a new biomarker linked to respiratory failure and lung damage in mild to moderate SARS-CoV-2 pneumonia.ERJ open research · 2024Article
- The predictive power of data: machine learning analysis for Covid-19 mortality based on personal, clinical, preclinical, and laboratory variables in a case-control study.BMC infectious diseases · 2024Article
- Assessing the impact of vaccines on COVID-19 efficacy in survival rates: a survival analysis approach for clinical decision support.Frontiers in public health · 2024Article
- Phenotype clustering of hospitalized high-risk patients with COVID-19 - a machine learning approach within the multicentre, multinational PCHF-COVICAV registry.Cardiology journal · 2024Article
- Factors associated with the worsening of COVID-19 symptoms among cohorts in community- or home-isolation care in southern Thailand.Frontiers in public health · 2024Article
- Making the Improbable Possible: Generalizing Models Designed for a Syndrome-Based, Heterogeneous Patient Landscape.Critical care clinics · 2023Review
- Risk Factors Associated with COVID-19 Lethality: A Machine Learning Approach Using Mexico Database.Journal of medical systems · 2023Article
- Hyperparameter optimization for cardiovascular disease data-driven prognostic system.Visual computing for industry, biomedicine, and art · 2023Article
- Real-life comparison of mortality in patients with SARS-CoV-2 infection at risk for clinical progression treated with molnupiravir or nirmatrelvir plus ritonavir during the Omicron era in Italy: a nationwide, cohort study.The Lancet regional health. Europe · 2023Article
50 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
107 authors at 20 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
aimsThere is poor knowledge on characteristics, comorbidities and laboratory measures associated with risk for adverse outcomes and in-hospital mortality in European Countries. We aimed at identifying baseline characteristics predisposing COVID-19 patients to in-hospital death. METHODS AND
resultsRetrospective observational study on 3894 patients with SARS-CoV-2 infection hospitalized from February 19th to May 23rd, 2020 and recruited in 30 clinical centres distributed throughout Italy. Machine learning (random forest)-based and Cox survival analysis. 61.7% of participants were men (median age 67 years), followed up for a median of 13 days. In-hospital mortality exhibited a geographical gradient, Northern Italian regions featuring more than twofold higher death rates as compared to Central/Southern areas (15.6% vs 6.4%, respectively). Machine learning analysis revealed that the most important features in death classification were impaired renal function, elevated C reactive protein and advanced age. These findings were confirmed by multivariable Cox survival analysis (hazard ratio (HR): 8.2; 95% confidence interval (CI) 4.6-14.7 for age ≥85 vs 18-44 y); HR = 4.7; 2.9-7.7 for estimated glomerular filtration rate levels <15 vs ≥ 90 mL/min/1.73 m
conclusionsImpaired renal function, elevated C-reactive protein and advanced age were major predictors of in-hospital death in a large cohort of unselected patients with COVID-19, admitted to 30 different clinical centres all over Italy.
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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.