ArticleThorax2022
External validation of the QCovid risk prediction algorithm for risk of COVID-19 hospitalisation and mortality in adults: national validation cohort study in Scotland.
Article in Thorax, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 21 citations in OpenAlex.
- Development and validation of a risk prediction model for hospital admission in COVID-19 patients presenting to primary care.The European journal of general practice · 2024Article
- Real-world severe COVID-19 outcomes associated with use of antivirals and neutralising monoclonal antibodies in Scotland.NPJ primary care respiratory medicine · 2024Article
- Risk of COVID-19 death in adults who received booster COVID-19 vaccinations in England.Nature communications · 2024Article
- Article
- Risk prediction of covid-19 related death or hospital admission in adults testing positive for SARS-CoV-2 infection during the omicron wave in England (QCOVID4): cohort study.BMJ (Clinical research ed.) · 2023Article
- Accelerated waning of the humoral response to COVID-19 vaccines in obesity.Nature medicine · 2023Article
- Article
- Observational
- Article
- COVID-19 vaccine effectiveness against symptomatic SARS-CoV-2 infection and severe COVID-19 outcomes from Delta AY.4.2: Cohort and test-negative study of 5.4 million individuals in Scotland.Journal of global health · 2022Article
- CALMS: Modelling the long-term health and economic impact of Covid-19 using agent-based simulation.PloS one · 2022Article
- BNT162b2 and ChAdOx1 nCoV-19 vaccinations, incidence of SARS-CoV-2 infections and COVID-19 hospitalisations in Scotland in the Delta era.Journal of global health · 2022Article
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15 authors at 8 institutions in 2 countries.
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Abstract
backgroundThe QCovid algorithm is a risk prediction tool that can be used to stratify individuals by risk of COVID-19 hospitalisation and mortality. Version 1 of the algorithm was trained using data covering 10.5 million patients in England in the period 24 January 2020 to 30 April 2020. We carried out an external validation of version 1 of the QCovid algorithm in Scotland.
methodsWe established a national COVID-19 data platform using individual level data for the population of Scotland (5.4 million residents). Primary care data were linked to reverse-transcription PCR (RT-PCR) virology testing, hospitalisation and mortality data. We assessed the performance of the QCovid algorithm in predicting COVID-19 hospitalisations and deaths in our dataset for two time periods matching the original study: 1 March 2020 to 30 April 2020, and 1 May 2020 to 30 June 2020.
resultsOur dataset comprised 5 384 819 individuals, representing 99% of the estimated population (5 463 300) resident in Scotland in 2020. The algorithm showed good calibration in the first period, but systematic overestimation of risk in the second period, prior to temporal recalibration. Harrell's C for deaths in females and males in the first period was 0.95 (95% CI 0.94 to 0.95) and 0.93 (95% CI 0.92 to 0.93), respectively. Harrell's C for hospitalisations in females and males in the first period was 0.81 (95% CI 0.80 to 0.82) and 0.82 (95% CI 0.81 to 0.82), respectively.
conclusionsVersion 1 of the QCovid algorithm showed high levels of discrimination in predicting the risk of COVID-19 hospitalisations and deaths in adults resident in Scotland for the original two time periods studied, but is likely to need ongoing recalibration prospectively.
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