Abstract
Idiopathic ventricular fibrillation (IVF) is diagnosed in patients with apparently unexplained cardiac arrest (UCA) after varying degrees of evaluation. This is largely due to the lack of a standardized approach to UCA.
We sought to develop an evidence-based diagnostic algorithm for IVF by systematically examining the yield of diagnostic testing in UCA probands.
Studies reporting the yield of diagnostic testing in UCA were identified in MEDLINE, EMBASE, Cochrane Central Register of Controlled Trials, and conference abstracts. Their methodological quality was assessed by the National Institutes of Health quality assessment tool. Meta-analyses were performed using the random effects model.
A total of 21 studies were included. The pooled comprehensive diagnostic testing yield was 43% (95% confidence interval 39%–48%). A lower yield was seen when only definite diagnoses based on the prespecified criteria were used (32% vs 47%; P = .15). Epinephrine challenge, Holter monitoring, and family screening were associated with low yield (<5%), whereas cardiac magnetic resonance imaging, exercise treadmill test, and sodium-channel blocker challenge were associated with high yield (≥5%). Coronary spasm provocation, electrophysiology study, and systematic genetic testing were reported to be abnormal in a high proportion of UCA probands (>10%).
We developed a stepwise algorithm for UCA evaluation and criteria to assess the strength of IVF diagnosis on the basis of the diagnostic yield of UCA testing.