ArticleScientific reports2021
SARS2 simplified scores to estimate risk of hospitalization and death among patients with COVID-19.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
16 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- A Systematic Review of Predictor Composition, Outcomes, Risk of Bias, and Validation of COVID-19 Prognostic Scores.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2024Pooled it
- Racial disparities in COVID-19 pandemic cases, hospitalisations, and deaths: A systematic review and meta-analysis.Journal of global health · 2021Pooled it
- Refining the role of behavioural and social sciences in pandemic response post-COVID-19.Nature human behaviour · 2026Review
- Impact of Risk Factor Combinations on Severe COVID-19 Outcomes Among Outpatients.Infectious diseases and therapy · 2026Article
- Article
- Observational
- Cost-effectiveness of casirivimab/imdevimab in patients with COVID-19 in the ambulatory setting.Journal of managed care & specialty pharmacy · 2022Article
- MS-based targeted profiling of oxylipins in COVID-19: A new insight into inflammation regulation.Free radical biology & medicine · 2022Observational
- The new normal: Covid-19 risk perceptions and support for continuing restrictions past vaccinations.PloS one · 2022Article
- Simple scoring tool to estimate risk of hospitalization and mortality in ambulatory and emergency department patients with COVID-19.PloS one · 2022Article
- Early Adoption of Longitudinal Surveillance for SARS-CoV-2 among Staff in Long-Term Care Facilities: Prevalence, Virologic and Sequence Analysis.Microbiology spectrum · 2021Article
- A hitchhiker's guide through the COVID-19 galaxy.Clinical immunology (Orlando, Fla.) · 2021Review
- Uncovering Clinical Risk Factors and Predicting Severe COVID-19 Cases Using UK Biobank Data: Machine Learning Approach.JMIR public health and surveillance · 2021Article
- Smoking and risk of negative outcomes among COVID-19 patients: A systematic review and meta-analysis.Tobacco induced diseases · 2021Article
- Utilization of an Electronic Health Record Integrated Risk Score to Predict Hospitalization Among COVID-19 Patients.Journal of primary care & community healthObservational
- COVID-19 Booster Vaccine Equity for Patients With Cancer.Advances in radiation oncologyArticle
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5 authors.
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Abstract
Although models have been developed for predicting severity of COVID-19 from the medical history of patients, simplified models with good accuracy could be more practical. In this study, we examined utility of simpler models for estimating risk of hospitalization of patients with COVID-19 and mortality of these patients based on demographic characteristics (sex, age, race, median household income based on zip code) and smoking status of 12,347 patients who tested positive at Mass General Brigham centers. The corresponding electronic records were queried (02/26-07/14/2020) to construct derivation and validation cohorts. The derivation cohort was used to fit generalized linear models for estimating risk of hospitalization within 30 days of COVID-19 diagnosis and mortality within approximately 3 months for the hospitalized patients. In the validation cohort, the model resulted in c-statistics of 0.77 [95% CI 0.73-0.80] for hospitalization, and 0.84 [95% CI 0.74-0.94] for mortality among hospitalized patients. Higher risk was associated with older age, male sex, Black ethnicity, lower socioeconomic status, and current/past smoking status. The models can be applied to predict the absolute risks of hospitalization and mortality, and could aid in individualizing the decision making when detailed medical history of patients is not readily available.
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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.