Observational studyThorax2022
Prospective validation of the 4C prognostic models for adults hospitalised with COVID-19 using the ISARIC WHO Clinical Characterisation Protocol.
Observational study in Thorax, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05498324 (External Validation of the 4C Mortality Score for Hospitalised Patients With COVID-19 in a Tunisian Cohort), which is not on this map. Cited by 20 papers, 2 of them syntheses that pooled it.
What it found
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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.
External Validation of the 4C Mortality Score for Hospitalised Patients With COVID-19 in a Tunisian Cohort
Who cites it
20 citing papers in PubMed, 2 syntheses or guidelines pooled it, 35 citations in OpenAlex.
- Pooled it
- Prognostic models in COVID-19 infection that predict severity: a systematic review.European journal of epidemiology · 2023Pooled it
- Cardiorespiratory impact of COVID-19 in young adults: A propensity score-weighted cohort study.New microbes and new infections · 2025Article
- At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods.Scientific reports · 2024Article
- Development and Validation of a Robust and Interpretable Early Triaging Support System for Patients Hospitalized With COVID-19: Predictive Algorithm Modeling and Interpretation Study.Journal of medical Internet research · 2024Article
- Development and external validation of a prediction model for the transition from mild to moderate or severe form of COVID-19.European radiology · 2023Article
- Impact of Surge Strain and Pandemic Progression on Prognostication by an Established COVID-19-Specific Severity Score.Critical care explorations · 2023Article
- Head-to-head comparison of six warning scores to predict mortality and clinical impairment in COVID-19 patients in emergency department.Internal and emergency medicine · 2023Observational
- Article
- ANCOC Score to Predict Mortality in Different SARS-CoV-2 Variants and Vaccination Status.Journal of clinical medicine · 2023Article
- An artificial intelligence approach for predicting death or organ failure after hospitalization for COVID-19: development of a novel risk prediction tool and comparisons with ISARIC-4C, CURB-65, qSOFA, and MEWS scoring systems.Respiratory research · 2023Article
- Review
- Article
- Utility of the 4C ISARIC mortality score in hospitalized COVID-19 patients at a large tertiary Saudi Arabian center.Multidisciplinary respiratory medicine · 2023Article
- Assess and validate predictive performance of models for in-hospital mortality in COVID-19 patients: A retrospective cohort study in the Netherlands comparing the value of registry data with high-granular electronic health records.International journal of medical informatics · 2022Observational
- Respiratory support in patients with severe COVID-19 in the International Severe Acute Respiratory and Emerging Infection (ISARIC) COVID-19 study: a prospective, multinational, observational study.Critical care (London, England) · 2022Observational
- Article
- Comparison of prognostic scores for inpatients with COVID-19: a retrospective monocentric cohort study.BMJ open respiratory research · 2022Article
- ISARIC-COVID-19 dataset: A Prospective, Standardized, Global Dataset of Patients Hospitalized with COVID-19.Scientific data · 2022Article
- Course of disease and risk factors for hospitalization in outpatients with a SARS-CoV-2 infection.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
37 authors at 15 institutions in 9 countries.
Funding
Abstract
purposeTo prospectively validate two risk scores to predict mortality (4C Mortality) and in-hospital deterioration (4C Deterioration) among adults hospitalised with COVID-19.
methodsProspective observational cohort study of adults (age ≥18 years) with confirmed or highly suspected COVID-19 recruited into the International Severe Acute Respiratory and emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study in 306 hospitals across England, Scotland and Wales. Patients were recruited between 27 August 2020 and 17 February 2021, with at least 4 weeks follow-up before final data extraction. The main outcome measures were discrimination and calibration of models for in-hospital deterioration (defined as any requirement of ventilatory support or critical care, or death) and mortality, incorporating predefined subgroups.
results76 588 participants were included, of whom 27 352 (37.4%) deteriorated and 12 581 (17.4%) died. Both the 4C Mortality (0.78 (0.77 to 0.78)) and 4C Deterioration scores (pooled C-statistic 0.76 (95% CI 0.75 to 0.77)) demonstrated consistent discrimination across all nine National Health Service regions, with similar performance metrics to the original validation cohorts. Calibration remained stable (4C Mortality: pooled slope 1.09, pooled calibration-in-the-large 0.12; 4C Deterioration: 1.00, -0.04), with no need for temporal recalibration during the second UK pandemic wave of hospital admissions.
conclusionBoth 4C risk stratification models demonstrate consistent performance to predict clinical deterioration and mortality in a large prospective second wave validation cohort of UK patients. Despite recent advances in the treatment and management of adults hospitalised with COVID-19, both scores can continue to inform clinical decision making. TRIAL REGISTRATION NUMBER: ISRCTN66726260.
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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.