In:
BMJ Open, BMJ, Vol. 12, No. 9 ( 2022-09), p. e060026-
Abstract:
To develop a disease stratification model for COVID-19 that updates according to changes in a patient’s condition while in hospital to facilitate patient management and resource allocation. Design In this retrospective cohort study, we adopted a landmarking approach to dynamic prediction of all-cause in-hospital mortality over the next 48 hours. We accounted for informative predictor missingness and selected predictors using penalised regression. Setting All data used in this study were obtained from a single UK teaching hospital. Participants We developed the model using 473 consecutive patients with COVID-19 presenting to a UK hospital between 1 March 2020 and 12 September 2020; and temporally validated using data on 1119 patients presenting between 13 September 2020 and 17 March 2021. Primary and secondary outcome measures The primary outcome is all-cause in-hospital mortality within 48 hours of the prediction time. We accounted for the competing risks of discharge from hospital alive and transfer to a tertiary intensive care unit for extracorporeal membrane oxygenation. Results Our final model includes age, Clinical Frailty Scale score, heart rate, respiratory rate, oxygen saturation/fractional inspired oxygen ratio, white cell count, presence of acidosis (pH 〈 7.35) and interleukin-6. Internal validation achieved an area under the receiver operating characteristic (AUROC) of 0.90 (95% CI 0.87 to 0.93) and temporal validation gave an AUROC of 0.86 (95% CI 0.83 to 0.88). Conclusions Our model incorporates both static risk factors (eg, age) and evolving clinical and laboratory data, to provide a dynamic risk prediction model that adapts to both sudden and gradual changes in an individual patient’s clinical condition. On successful external validation, the model has the potential to be a powerful clinical risk assessment tool. Trial registration The study is registered as ‘researchregistry5464’ on the Research Registry ( www.researchregistry.com ).
Type of Medium:
Online Resource
ISSN:
2044-6055
,
2044-6055
DOI:
10.1136/bmjopen-2021-060026
DOI:
10.1136/bmjopen-2021-060026.supp1
Language:
English
Publisher:
BMJ
Publication Date:
2022
detail.hit.zdb_id:
2599832-8
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