ArticleBMJ open2022
Development and external validation of prognostic models for COVID-19 to support risk stratification in secondary care.
Article in BMJ open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Prognostic models in COVID-19 infection that predict severity: a systematic review.European journal of epidemiology · 2023Pooled it
- Observational
- External Validation of Mortality Scores among High-Risk COVID-19 Patients: A Romanian Retrospective Study in the First Pandemic Year.Journal of clinical medicine · 2022Article
- External Validation of the Modified 4C Deterioration Model and 4C Mortality Score for COVID-19 Patients in a Swiss Tertiary Hospital.Diagnostics (Basel, Switzerland) · 2022Article
- Diabetes and SARS-CoV-2-Is There a Mutual Connection?Frontiers in cell and developmental biology · 2022Review
- Oxidative stress markers-driven prognostic model to predict post-discharge mortality in heart failure with reduced ejection fraction.Frontiers in cardiovascular medicine · 2022Article
Corrections and comments
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Authors and funding
16 authors.
Funding
Abstract
objectivesExisting UK prognostic models for patients admitted to the hospital with COVID-19 are limited by reliance on comorbidities, which are under-recorded in secondary care, and lack of imaging data among the candidate predictors. Our aims were to develop and externally validate novel prognostic models for adverse outcomes (death and intensive therapy unit (ITU) admission) in UK secondary care and externally validate the existing 4C score.
designCandidate predictors included demographic variables, symptoms, physiological measures, imaging and laboratory tests. Final models used logistic regression with stepwise selection.
settingModel development was performed in data from University Hospitals Birmingham (UHB). External validation was performed in the CovidCollab dataset.
participantsPatients with COVID-19 admitted to UHB January-August 2020 were included.
main outcome measuresDeath and ITU admission within 28 days of admission.
results1040 patients with COVID-19 were included in the derivation cohort; 288 (28%) died and 183 (18%) were admitted to ITU within 28 days of admission. Area under the receiver operating characteristic curve (AUROC) for mortality was 0.791 (95% CI 0.761 to 0.822) in UHB and 0.767 (95% CI 0.754 to 0.780) in CovidCollab; AUROC for ITU admission was 0.906 (95% CI 0.883 to 0.929) in UHB and 0.811 (95% CI 0.795 to 0.828) in CovidCollab. Models showed good calibration. Addition of comorbidities to candidate predictors did not improve model performance. AUROC for the International Severe Acute Respiratory and Emerging Infection Consortium 4C score in the UHB dataset was 0.753 (95% CI 0.720 to 0.785).
conclusionsThe novel prognostic models showed good discrimination and calibration in derivation and external validation datasets, and performed at least as well as the existing 4C score using only routinely collected patient information. The models can be integrated into electronic medical records systems to calculate each individual patient's probability of death or ITU admission at the time of hospital admission. Implementation of the models and clinical utility should be evaluated.
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