Risk Prediction Models for Out-of-Hospital Cardiac Arrest Outcomes in England.

Ji, Chen and Brown, Terry P and Booth, Scott J and Hawkes, Claire and Nolan, Jerry P and Mapstone, James and Fothergill, Rachael T and Spaight, Robert and Black, Sarah and Perkins, Gavin D (2020) Risk Prediction Models for Out-of-Hospital Cardiac Arrest Outcomes in England. European heart journal. Quality of care & clinical outcomes. ISSN 2058-1742.

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Abstract

INTRODUCTION

The Out-of-Hospital Cardiac Arrest (OHCA) Outcomes project is a national research registry. One of its aims is to explore sources of variation in OHCA survival outcomes. This study reports the development and validation of risk prediction models for return of spontaneous circulation (ROSC) at hospital handover and survival to hospital discharge.

METHODS AND RESULTS

The study included OHCA patients who were treated during 2014 and 2015 by emergency medical services (EMS) from 7 English National Health Service ambulance services. The 2014 data were used to identify important variables and to develop the risk prediction models, which were validated using the 2015 data. Model prediction was measured by area under the curve (AUC), Hosmer-Lemeshow test, Cox calibration regression and Brier score. All analyses were conducted using mixed effects logistic regression models. Important factors included age, gender, witness/bystander cardiopulmonary resuscitation (CPR) combined, aetiology and initial rhythm. Interaction effects between witness/bystander CPR with gender, aetiology and initial rhythm and between aetiology and initial rhythm were significant in both models. The survival model achieved better discrimination and overall accuracy compared with the ROSC model (AUC=0.86 vs 0.67, Brier score=0.072 vs 0.194, respectively). Calibration tests showed over- and under-estimation for the ROSC and survival models, respectively. A sensitivity analysis individually assessing Index of Multiple Deprivation scores and location in the final models substantially improved overall accuracy with inconsistent impact on discrimination.

CONCLUSION

Our risk prediction models identified and quantified important pre-EMS intervention factors determining survival outcomes in England. The survival model had excellent discrimination.

Item Type: Article
Subjects: WB Practice of medicine > WB400 Intensive care
WG Cardiovascular system. Cardiology
Divisions: Clinical Support > Critical Care
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Depositing User: Mrs Yolande Brookes
Date Deposited: 13 Mar 2020 13:50
Last Modified: 13 Mar 2020 13:50
URI: http://www.repository.uhblibrary.co.uk/id/eprint/2925

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