Mapping drug-class associations with sudden cardiac arrest in the outpatient setting: an exploratory population-based...

To map the risk profile of drug classes at the population level by identifying associations between newly prescribed reimbursed drugs and sudden cardiac arrest (SCA), thereby providing a systematic basis for assessing individual drug effects.

Population-based, matched case-control study.

Greater Vienna area, Austria, using linked data from the Austrian Healthcare Reimbursement Database and the Vienna Ambulance Service between 2013 and 2020.

A total of 31 330 insured individuals were included from an estimated 14 448 612 person-years at risk. Cases (n=6266) were patients with SCA, each matched 1:4 to controls (n=25 064) without SCA by age, sex and event date. The estimated absolute case risk equals 43.4 per 100 000 person-years.

Newly prescribed reimbursed drugs within 4 weeks before the SCA event, classified according to four-digit Anatomical Therapeutic Chemical (ATC) codes.

Associations between newly prescribed drug classes and SCA, estimated using conditional logistic regression and expressed as ORs with 95% CIs, adjusted for comorbidities and concomitant medications prescribed 120-29 days before the event.

Among 322 relevant ATC drug classes, 245 were newly prescribed within 28 days prior to the SCA event. Of these, 57 (23%) were significantly associated with SCA. Eight drug classes demonstrated a markedly elevated risk (OR≥10), including oripavine derivatives (OR 64, 95% CI 8 to 486), other cardiac preparations (OR 22, 95% CI 2 to 204), plain antiandrogens (OR 18, 95% CI 1.2 to 275) and phenylpiperidine derivatives (OR 16, 95% CI 7 to 38). The most frequently prescribed associated drug classes were penicillins with beta-lactamase inhibitors (179 cases; OR 2.17, 95% CI 1.8 to 2.7), pyrazolones (167 cases; OR 2.14, 95% CI 1.7 to 2.7) and adrenergics combined with anticholinergics (130 cases; OR 2.94, 95% CI 2.2 to 3.9).

Numerous outpatient-prescribed drug classes were associated with SCA. This exploratory, population-based analysis provides a systematic map of potential safety signals to inform more detailed pharmaco-epidemiological investigations, in which confounding and causality can be examined more rigorously.