SynthesisClinical infectious diseases : an official publication of the Infectious Diseases Society of America2024
A Systematic Review of Predictor Composition, Outcomes, Risk of Bias, and Validation of COVID-19 Prognostic Scores.
Synthesis in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Development and External Validation of a Prognostic Prediction Model for Hospitalization in SARS-CoV-2-Infected Ambulatory Patients.Open forum infectious diseases · 2026Article
- Development and validation of a model for early prediction of severe/critical COVID-19 in elderly patients.PeerJ · 2026Article
- Rethinking emergency risk assessment: A single-center look at shock index and its variants in COVID-19.PloS one · 2026Observational
- Validation of CURB-65, CRB-65, NEWS2, qSOFA, and 4C scores for predicting mortality in COVID-19 patients across seven emergency Departments in Colombia.Frontiers in medicine · 2026Article
- Leveraging near-real-time patient and population data to incorporate fluctuating risk of severe COVID-19: development and prospective validation of a personalised risk prediction tool.EClinicalMedicine · 2025Article
- Article
- Using machine learning methods to investigate the impact of comorbidities and clinical indicators on the mortality rate of COVID-19.Frontiers in medical technology · 2025Article
- Persistent disabilities 28 months after COVID-19 hospitalisation, a prospective cohort study.ERJ open research · 2024Article
- Article
- Impact of Surge Strain and Pandemic Progression on Prognostication by an Established COVID-19-Specific Severity Score.Critical care explorations · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundNumerous prognostic scores have been published to support risk stratification for patients with coronavirus disease 2019 (COVID-19).
methodsWe performed a systematic review to identify the scores for confirmed or clinically assumed COVID-19 cases. An in-depth assessment and risk of bias (ROB) analysis (Prediction model Risk Of Bias ASsessment Tool [PROBAST]) was conducted for scores fulfilling predefined criteria ([I] area under the curve [AUC)] ≥ 0.75; [II] a separate validation cohort present; [III] training data from a multicenter setting [≥2 centers]; [IV] point-scale scoring system).
resultsOut of 1522 studies extracted from MEDLINE/Web of Science (20/02/2023), we identified 242 scores for COVID-19 outcome prognosis (mortality 109, severity 116, hospitalization 14, long-term sequelae 3). Most scores were developed using retrospective (75.2%) or single-center (57.1%) cohorts. Predictor analysis revealed the primary use of laboratory data and sociodemographic information in mortality and severity scores. Forty-nine scores were included in the in-depth analysis. The results indicated heterogeneous quality and predictor selection, with only five scores featuring low ROB. Among those, based on the number and heterogeneity of validation studies, only the 4C Mortality Score can be recommended for clinical application so far.
conclusionsThe application and translation of most existing COVID scores appear unreliable. Guided development and predictor selection would have improved the generalizability of the scores and may enhance pandemic preparedness in the future.
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