five

WP2 Maastricht

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DataCite Commons2025-07-03 更新2025-04-09 收录
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https://dataverse.nl/citation?persistentId=doi:10.34894/ZGU9EO
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Aim: to propose a model to estimate the risk of hospital admission due to COVID-19. Study design: a cohort study of suspected and confirmed COVID-19 patients presenting in 14 general practices (GP) in and 8 out-of-hours services in the Netherlands, merged with hospital admission records. The development cohort spanned 01/03/2020 to 15/06/2020, the validation cohort 13/03/2021 to 19/06/2021. Methods: Adult patients with suspected or confirmed COVID-19 who contacted their GP or out-of-hours service for a face-to-face consultation were included. Data on patient characteristics and physical examination were recorded retrospectively in a case report form (CRF ). A logistic regression model was developed to predict hospital admission with COVID-19 within 14 days. Candidate predictors included demographic data, comorbidities, and symptoms. Model performance was evaluated using the C-statistic, calibration plots, and net benefit. Regional internal-external validation was used, in addition to a temporal external validation. 4806 patients were included in the development cohort and dataset. Their median age was 56 (IQR 40 to 70), 56.4% were female. The median duration of complaints at the first visit was 7 days (IQR 2.5 to 14 days). The majority of patients presented with dyspnoea (64.4%) or a cough (63.8%). Being male, auscultation abnormalities, confusion, cough, haemoptysis, stomach complaints, headache, chronic kidney disease, lower oxygen saturation and higher body temperature increase the probability of hospital admission.
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DataverseNL
创建时间:
2022-08-24
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