ArticleOpen forum infectious diseases2020
Derivation and Validation of Clinical Prediction Rules for COVID-19 Mortality in Ontario, Canada.
Article in Open forum infectious diseases, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Prevalence of comorbid tuberculosis amongst COVID-19 patients: A rapid review and meta-analysis.International journal of clinical practice · 2021Pooled it
- The association of smoking status with SARS-CoV-2 infection, hospitalization and mortality from COVID-19: a living rapid evidence review with Bayesian meta-analyses (version 7).Addiction (Abingdon, England) · 2021Pooled it
- Healthcare-associated COVID-19 in Ontario, Canada: case classification and relative mortality.BMC infectious diseases · 2026Article
- Impact of community mask mandates on SARS-CoV-2 transmission in Ontario after adjustment for differential testing by age and sex.PNAS nexus · 2024Article
- Development and Validation of an Acute Respiratory Distress Syndrome Prediction Model in Coronavirus Disease 2019: Updated Lung Injury Prediction Score.Mayo Clinic proceedings · 2023Article
- Relative Virulence of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Among Vaccinated and Unvaccinated Individuals Hospitalized With SARS-CoV-2.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2023Article
- Model-agnostic explainable artificial intelligence tools for severity prediction and symptom analysis on Indian COVID-19 data.Frontiers in artificial intelligence · 2023Article
- The PaCO2/FiO2 ratio as outcome predictor in SARS-COV-2 related pneumonia: a retrospective study.Acta bio-medica : Atenei Parmensis · 2022Article
- Clinical Outcomes of Individuals with COVID-19 and Tuberculosis during the Pre-Vaccination Period of the Pandemic: A Systematic Review.Journal of clinical medicine · 2022Review
- Simple scoring tool to estimate risk of hospitalization and mortality in ambulatory and emergency department patients with COVID-19.PloS one · 2022Article
- Leveraging the Electronic Health Record to Address the COVID-19 Pandemic.Mayo Clinic proceedings · 2021Review
- Decision-making in Surgery or Active Surveillance for Low Risk Papillary Thyroid Cancer During the COVID-19 Pandemic.Cancers · 2021Article
- Insights Into Co-Morbidity and Other Risk Factors Related to COVID-19 Within Ontario, Canada.Frontiers in artificial intelligence · 2021Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently causing a high-mortality global pandemic. The clinical spectrum of disease caused by this virus is broad, ranging from asymptomatic infection to organ failure and death. Risk stratification of individuals with coronavirus disease 2019 (COVID-19) is desirable for management, and prioritization for trial enrollment. We developed a prediction rule for COVID-19 mortality in a population-based cohort in Ontario, Canada.
methodsData from Ontario's provincial iPHIS system were extracted for the period from January 23 to May 15, 2020. Logistic regression-based prediction rules and a rule derived using a Cox proportional hazards model were developed and validated using split-halves validation. Sensitivity analyses were performed, with varying approaches to missing data.
resultsOf 21 922 COVID-19 cases, 1734 with complete data were included in the derivation set; 1796 were included in the validation set. Age and comorbidities (notably diabetes, renal disease, and immune compromise) were strong predictors of mortality. Four point-based prediction rules were derived (base case, smoking excluded, long-term care excluded, and Cox model-based). All displayed excellent discrimination (area under the curve for all rules > 0.92) and calibration (
conclusionsWe used a public health case management data system to build and validate 4 accurate, well-calibrated, robust clinical prediction rules for COVID-19 mortality in Ontario, Canada. While these rules need external validation, they may be useful tools for management, risk stratification, and clinical trials.
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