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Abstract
Objectives: Early Warning Scores (EWS) alerting for in-hospital deterioration are commonly developed using routinely collected vital-sign data from the whole in-hospital population. As these in-hospital populations are dominated by those over the age of 45 years, resultant scores may perform less well in younger age groups. We developed and validated an Age-specific Early Warning Score (ASEWS) derived from statistical distributions of vital signs.
Design: Observational Cohort Study
Setting: Oxford University Hospitals (OUH) July 2013 – March 2018 and Portsmouth Hospitals (PH) NHS Trust January 2010 – March 2017 within the HAVEN database
Participants: Hospitalised patients with electronically documented vital-sign observations
Outcome: Composite outcome of unplanned intensive care unit (ICU) admission, mortality, and cardiac arrest.
Methods and Results: Statistical distributions of vital signs were used to develop an age-specific early warning score to predict the composite outcome within 24 hours. The OUH development set consisted of 2,538,099 vital-sign observation sets from 142,806 admissions (mean age (std): 59.8 (20.3)). We compared the performance of ASEWS to the National Early Warning Score (NEWS) and our previous EWS (MCEWS) on an OUH validation set consisting of 581,571 observation sets from 25,407 emergency admissions (mean age (std): 63.0 (21.4)) and a PH validation set consisting of 5,865,997 observation sets from 233,632 emergency admissions (mean age (std): 64.3 (21.1)). ASEWS performed better in the 16-45 years age group in the OUH validation set (AUROC 0.820 [95% CI 0.815-0.824]) and PH validation set (AUROC 0.840 [95% CI 0.839-0.841]) than NEWS (AUROC 0.763 [95% CI 0.758-0.768] and AUROC 0.836 [95% CI 0.835 0 0.838] respectively) and MCEWS (AUROC 0.808 [95% CI 0.803-0.812] and AUROC 0.833 [95% CI 0.831 - 0.834] respectively). Differences in performance were not consistent in the elder age group.
Conclusions: Accounting for age- related vital sign changes can more accurately detect deterioration in younger patients.
Design: Observational Cohort Study
Setting: Oxford University Hospitals (OUH) July 2013 – March 2018 and Portsmouth Hospitals (PH) NHS Trust January 2010 – March 2017 within the HAVEN database
Participants: Hospitalised patients with electronically documented vital-sign observations
Outcome: Composite outcome of unplanned intensive care unit (ICU) admission, mortality, and cardiac arrest.
Methods and Results: Statistical distributions of vital signs were used to develop an age-specific early warning score to predict the composite outcome within 24 hours. The OUH development set consisted of 2,538,099 vital-sign observation sets from 142,806 admissions (mean age (std): 59.8 (20.3)). We compared the performance of ASEWS to the National Early Warning Score (NEWS) and our previous EWS (MCEWS) on an OUH validation set consisting of 581,571 observation sets from 25,407 emergency admissions (mean age (std): 63.0 (21.4)) and a PH validation set consisting of 5,865,997 observation sets from 233,632 emergency admissions (mean age (std): 64.3 (21.1)). ASEWS performed better in the 16-45 years age group in the OUH validation set (AUROC 0.820 [95% CI 0.815-0.824]) and PH validation set (AUROC 0.840 [95% CI 0.839-0.841]) than NEWS (AUROC 0.763 [95% CI 0.758-0.768] and AUROC 0.836 [95% CI 0.835 0 0.838] respectively) and MCEWS (AUROC 0.808 [95% CI 0.803-0.812] and AUROC 0.833 [95% CI 0.831 - 0.834] respectively). Differences in performance were not consistent in the elder age group.
Conclusions: Accounting for age- related vital sign changes can more accurately detect deterioration in younger patients.
Original language | English |
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Journal | BMJ Open |
DOIs | |
Publication status | Published - 19 Nov 2019 |
Keywords
- Health informatics
- Quality in health care
- Adverse events
- Wellcome Trust
- WT-103703/Z/14/Z
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Dive into the research topics of 'Early warning score adjusted for age to predict the composite outcome of mortality, cardiac arrest or unplanned intensive care unit admission using observational vital-sign data: a multicentre development and validation'. Together they form a unique fingerprint.Projects
- 1 Finished
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HAVEN: Hospital Alerting via Electronic Noticeboard
Briggs, J. (PI) & Prytherch, D. (CoI)
University of Oxford, Health Innovation Challenge Fund
3/08/15 → 2/08/18
Project: Research