Risk prediction models for out-of-hospital cardiac arrest outcomes in England.

AIMS: 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 seven 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.

Data quality and 30-day survival for out-of-hospital cardiac arrest in the UK out-of-hospital cardiac arrest registry: a data linkage study.

OBJECTIVES: The Out-of-Hospital Cardiac Arrest Outcomes (OHCAO) project aims to understand the epidemiology and outcomes of out-of-hospital cardiac arrest (OHCA) across the UK. This data linkage study is a subproject of OHCAO. The aim was to establish the feasibility of linking OHCAO data to National Health Service (NHS) patient demographic data and Office for National Statistics (ONS) date of death data held on the NHS Personal Demographics Service (PDS) database to improve OHCAO demographic data quality and enable analysis of 30-day survival from OHCA. DESIGN AND SETTING: Data were collected from 1 January 2014 to 31 December 2014 as part of a prospective, observational study of OHCA attended by 10 English NHS Ambulance Services. 28 729 OHCA cases had resuscitation attempted by Emergency Medical Services and were included in the study. Data linkage was carried out using a data linkage service provided by NHS Digital, a national provider of health-related data. To assess data linkage feasibility a random sample of 3120 cases was selected. The sample was securely transferred to NHS Digital to be matched using OHCAO patient demographic data to return previously missing demographic data and provide ONS date of death data. RESULTS: A total of 2513 (80.5%) OHCAO cases were matched to patients in the NHS PDS database. Using the linkage process, missing demographic data were retrieved for 1636 (72.7%) out of 2249 OHCAO cases that had previously incomplete demographic data. Returned ONS date of death data allowed analysis of 30-day survival status. The results showed a 30-day survival rate of 9.3%, reducing unknown survival status from 46.1% to 8.5%. CONCLUSIONS: In this sample, data linkage between the OHCAO registry and NHS PDS database was shown to be feasible, improving demographic data quality and allowing analysis of 30-day survival status.