Journal Article
Observational Study
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Recurrent out-of-hospital cardiac arrest.

Resuscitation 2017 December
BACKGROUND: Little is known about the burden of recurrent out-of-hospital cardiac arrest (OHCA) episodes in initial survivors of OHCA. We sought to investigate the frequency of recurrent OHCA, describe time-to-event trends, and establish baseline predictors of occurrence.

METHODS: Between January 2000 and June 2015, we included consecutive OHCA survivors to hospital discharge from the Victorian Ambulance Cardiac Arrest Registry. Patient identifiers were used to match index and recurrent episodes of OHCA, and death records from a government database. Kaplan-Meier curves and a Cox proportional-hazards model were used to estimate the long-term risk of recurrent OHCA and identify index characteristics associated with their occurrence.

RESULTS: Among 3581 survivors, 214 (6.0%) experienced a recurrent OHCA over a median time-at-risk of 5.0 years (interquartile range [IQR]: 2.0, 8.1). The median age at recurrent OHCA was 69 years, 72.9% were male, and 92.0% of events were fatal. Fatal recurrent OHCA episodes accounted for more than one-quarter of all deaths at follow-up. The probability of recurrent OHCA at 1, 5, 10 and 15 years was 2.4% (95% CI: 2.0%, 3.0%), 6.0% (95% CI: 5.2%, 6.9%), 8.4% (95% CI: 7.3%, 9.8%), and 11.2% (95% CI: 9.1%, 13.8%), respectively. In the multivariable model, the following baseline predictors were significantly associated with recurrent OHCA: respiratory (HR 1.88, 95% CI: 1.02, 3.47; p=0.045) or overdose/poisoning aetiology (HR 2.47, 95% CI: 1.08, 5.62; p=0.03), diabetes (HR 1.92, 95% CI: 1.17, 3.14, p=0.01), heart failure (HR 2.22, 95% CI: 1.28, 3.85; p=0.005), and renal insufficiency (HR 2.43, 95% CI: 1.23, 4.82; p=0.01). The risk of recurrent OHCA did not decline over the study period (per year increase: HR 0.97, 95% CI: 0.93, 1.01; p=0.13).

CONCLUSION: Recurrent OHCA episodes occur frequently in OHCA survivors, and could account for as many as one-quarter of all deaths at follow-up. Index characteristics may help to identify at-risk patients.

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