Development and validation of a risk prediction model for hospital admission in COVID-19 patients presenting to primary care
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| Názov: | Development and validation of a risk prediction model for hospital admission in COVID-19 patients presenting to primary care |
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| Autori: | Laure Wynants, Natascha JH. Broers, Tamara N. Platteel, Roderick P. Venekamp, Dennis G. Barten, Mathie PG. Leers, Theo JM. Verheij, Patricia M. Stassen, Jochen WL. Cals, Eefje GPM de Bont |
| Prispievatelia: | HAG Infectieziekten, Infection & Immunity, HAG Onderzoek, Child Health |
| Zdroj: | Eur J Gen Pract European Journal of General Practice, Vol 30, Iss 1 (2024) Wynants, L, Broers, N JH, Platteel, T N, Venekamp, R P, Barten, D G, Leers, M P G, Verheij, T JM, Stassen, P M, Cals, J WL & Bont, E GPM D 2024, 'Development and validation of a risk prediction model for hospital admission in COVID-19 patients presenting to primary care', European Journal of General Practice, vol. 30, no. 1, 2339488. https://doi.org/10.1080/13814788.2024.2339488 |
| Informácie o vydavateľovi: | Informa UK Limited, 2024. |
| Rok vydania: | 2024 |
| Predmety: | Male, Adult, EXTERNAL VALIDATION, Medicine (General), General Practice, Risk Assessment, 1117 Public Health and Health Services, Cohort Studies, 03 medical and health sciences, Medicine, General & Internal, R5-920, 0302 clinical medicine, Risk Factors, General & Internal Medicine, Journal Article, Humans, Primary Health Care/statistics & numerical data, COHORT, Validation Studies, ALGORITHM, Risk Assessment/methods, POPULATION, COVID-19/epidemiology, Hospitalization/statistics & numerical data, Retrospective Studies, Netherlands, Aged, general practice, Science & Technology, Primary Health Care, MORTALITY, COVID-19, 4203 Health services and systems, Middle Aged, Prognosis, PROGNOSTIC MODEL, 3. Good health, Hospitalization, General Practice/statistics & numerical data, Logistic Models, clinical risk prediction model, Female, prognosis, Covid-19, Life Sciences & Biomedicine, Research Article |
| Popis: | There is a paucity of prognostic models for COVID-19 that are usable for in-office patient assessment in general practice (GP).To develop and validate a risk prediction model for hospital admission with readily available predictors.A retrospective cohort study linking GP records from 8 COVID-19 centres and 55 general practices in the Netherlands to hospital admission records. The development cohort spanned March to June 2020, the validation cohort March to June 2021. The primary outcome was hospital admission within 14 days. We used geographic leave-region-out cross-validation in the development cohort and temporal validation in the validation cohort.In the development cohort, 4,806 adult patients with COVID-19 consulted their GP (median age 56, 56% female); in the validation cohort 830 patients did (median age 56, 52% female). In the development and validation cohort respectively, 292 (6.1%) and 126 (15.2%) were admitted to the hospital within 14 days, respectively. A logistic regression model based on sex, smoking, symptoms, vital signs and comorbidities predicted hospital admission with a c-index of 0.84 (95% CI 0.83 to 0.86) at geographic cross-validation and 0.79 (95% CI 0.74 to 0.83) at temporal validation, and was reasonably well calibrated (intercept -0.08, 95% CI -0.98 to 0.52, slope 0.89, 95% CI 0.71 to 1.07 at geographic cross-validation and intercept 0.02, 95% CI -0.21 to 0.24, slope 0.82, 95% CI 0.64 to 1.00 at temporal validation).We derived a risk model using readily available variables at GP assessment to predict hospital admission for COVID-19. It performed accurately across regions and waves. Further validation on cohorts with acquired immunity and newer SARS-CoV-2 variants is recommended. |
| Druh dokumentu: | Article Other literature type |
| Popis súboru: | application/pdf |
| Jazyk: | English |
| ISSN: | 1751-1402 1381-4788 |
| DOI: | 10.1080/13814788.2024.2339488 |
| Prístupová URL adresa: | https://pubmed.ncbi.nlm.nih.gov/38682305 https://doaj.org/article/95290ebe63e64a74a171072a06ab0e31 https://dspace.library.uu.nl/handle/1874/451923 |
| Rights: | CC BY URL: http://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (http://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. |
| Prístupové číslo: | edsair.doi.dedup.....df4f1c5c0424806bba1684cfae12eac6 |
| Databáza: | OpenAIRE |
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Nájsť tento článok vo Web of Science | Abstrakt: | There is a paucity of prognostic models for COVID-19 that are usable for in-office patient assessment in general practice (GP).To develop and validate a risk prediction model for hospital admission with readily available predictors.A retrospective cohort study linking GP records from 8 COVID-19 centres and 55 general practices in the Netherlands to hospital admission records. The development cohort spanned March to June 2020, the validation cohort March to June 2021. The primary outcome was hospital admission within 14 days. We used geographic leave-region-out cross-validation in the development cohort and temporal validation in the validation cohort.In the development cohort, 4,806 adult patients with COVID-19 consulted their GP (median age 56, 56% female); in the validation cohort 830 patients did (median age 56, 52% female). In the development and validation cohort respectively, 292 (6.1%) and 126 (15.2%) were admitted to the hospital within 14 days, respectively. A logistic regression model based on sex, smoking, symptoms, vital signs and comorbidities predicted hospital admission with a c-index of 0.84 (95% CI 0.83 to 0.86) at geographic cross-validation and 0.79 (95% CI 0.74 to 0.83) at temporal validation, and was reasonably well calibrated (intercept -0.08, 95% CI -0.98 to 0.52, slope 0.89, 95% CI 0.71 to 1.07 at geographic cross-validation and intercept 0.02, 95% CI -0.21 to 0.24, slope 0.82, 95% CI 0.64 to 1.00 at temporal validation).We derived a risk model using readily available variables at GP assessment to predict hospital admission for COVID-19. It performed accurately across regions and waves. Further validation on cohorts with acquired immunity and newer SARS-CoV-2 variants is recommended. |
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| ISSN: | 17511402 13814788 |
| DOI: | 10.1080/13814788.2024.2339488 |