Title: Why do outcomes of hospitalised patients with first out of hospital cardiac arrest from Acute Coronary Syndrome (ACS) vary in England and Wales?
Funder: Department of Health (England)

Abstract: Study design: Retrospective analysis of an existing multi-centre prospective observational cohort study. Data source: We will use the NHS national heart attack registry the Myocardial Ischaemic National audit Project (MINAP) to identify a subset of patients (about 1.8% estimated n = 15000) who had a cardiac arrest recorded out of hospital and were admitted to hospital. Inclusion criteria: •Adults (aged >18 years)•Out of hospital cardiac arrest (OHCA) due to an acute coronary syndrome (ACS)•Initial resuscitation attempts successful leading to admission to an NHS hospital Exclusion criteria:•2nd or subsequent cardiac arrests•In-hospital cardiac arrest onlyCase identification: Cardiac arrest is defined as an “absence of signs of circulation and/or considered for resuscitation” (1). Careful scrutiny of MINAP definitions (2) shows that ‘first cardiac arrest’ in patients with ACS may be identified using a number of variables and/or combinations of variables. The optimal approach for case identification of OHCA will be ascertained and sensitivity and specificity reported. Primary outcome: All-cause in-hospital mortality.Secondary outcomes: Time to all-cause mortality and/or neurological outcome.Impact of potentially modifiable predictor variables: •Emergency Medical Services (EMS) transport time (3 4)•Use of an electrocardiogram (ECG) in ambulance/hospital•The use of an early invasive strategy (including coronary angiography and / or percutaneous coronary intervention)(5)•Time from first collapse to reperfusion •Hospital volume of cases of ACS over study period (6-9)Impact of potentially non-modifiable predictor variables (i.e. a subset of the confounding variables):•OHCA occurring in presence of a trained health professional (including paramedic)•EMS response time (10)•Presence of a trained medic/paramedic during OHCA•Location of OHCA •History of diabetes mellitus•Ethnicity (11)Other potential confounders: co-morbidity background risk variables process variablesUsing the rich data from MINAP we will adjust for important confounders of survival from OHCA. These will include: age gender ethnicity and urban/rural domicile (from postcode) co-morbidity variables (e.g. previous acute myocardial infarction chronic renal failure chronic heart failure diabetes) lifestyle variables (e.g. smoking status) results of investigations (systolic blood pressure heart rate raised cardiac troponin concentration) process variables (such as admitting consultant status etc.) core variables known to be important for surviving a cardiac arrest out of hospital (12 13) and explore standardisation using established MINAP risk scores for stratification of patients with ACS (14-17). Sample size: Within the complete MINAP database of just under one million events there are an estimated 15000 cases with OHCA hospitalised alive. Our initial work suggests that a sample of this size has adequate power to detect meaningful differences in the primary outcome and will allow a detailed investigation of factors which may impact upon survival after OHCA (18).Statistical analysis: We will impute values for the missing observations using multiple imputation via chained equations (14 19) as has been suggested in the MINAP dataset (14). Sensitivity analyses will be performed to assess the robustness . We will fit multilevel models with a random effect term to test the hypothesis that the key explanatory variables and confounders explain the variability in outcomes. Time schedule: The total time schedule of this study from setup to dissemination of results with 60% FTE statastician is 18 months. Outputs and knowledge generation: The project will produce four main outputs linked to the study objectives.1) Define the epidemiology and outcome of patients who are admitted to NHS hospitals following successful resuscitation from out of hospital cardiac arrest that has been caused by an acute coronary syndrome2) Report the relative contribution of potentially modifiable factors linked to the in-hospital pathway for these patients 3) Synthesise of the research findings from our team of experienced clinicians those with responsibility for healthcare policy patient and public representatives and expert methodologists to produce key recommendations for service organisation. If the data allow we will evaluate potential modifications to health care system design and estimate the likely impact on health outcomes. 4) Prioritised summary of future research needs


Research activity codes: 7.1 INDIVIDUAL CARE NEEDS;8.1 ORGANISATION AND DELIVERY OF SERVICES
Health categories: CARDIOVASCULAR