Background: Arrhythmias and heart failure in form of left ventricular systolic dysfunction (LVSD) frequently coexist. Arrhythmia-induced cardiomyopathy (AIC) by definition is a state of reversible LVSD caused by supraventricular or ventricular arrhythmia. Diagnosis of AIC only can be made retrospectively ex juvantibus, and thus deserves consideration. Our aim is to determine prevalence and time course of AIC in patients presenting with tachycardia and newly diagnosed, unexplained LVSD.

Methods: In this prospective, observational, investigator-initiated, multi-center trial, we screen for patients with LVSD (left ventricular ejection fraction (LVEF) <50%) and tachyarrhythmia (HR > 100/min). After effective rhythm restoration, they are followed-up at 2, 4 and 6 months to evaluate clinical characteristics, biomarkers and cardiac imaging. Left ventricular morphology and function are assessed with transthoracic echocardiography, and left ventricular scar is quantified with cardia magnetic resonance imaging. Additionally, quality of life is measured with a questionnaire (Minnesota Living with Heart Failure). Unconventionally, the group assignment was done after the last follow-up visit (diagnosis ex juvantibus). Patients, whose LVEF recovered from LVSD, i.e. increases by ≥15% vs. baseline or increases to ≥50% with an absolute increase of ≥10% were assigned to the AIC group (arm 1). All other patients serve as comparator (arm 2, non-AIC group). Next, prevalence (equals the number of patients in arm 1 divided by the total number of patients) and time to recovery from AIC (time of follow-up visit, in which the LVEF recovered) were calculated and initial morphologic and functional parameters analyzed for predictive power of an AIC.

Discussion: We investigate the prevalence of and the time to recovery from AIC in a clinically relevant cohort of patients with newly diagnosed and otherwise unexplainable LVSD and coexisting tachyarrhythmia. Results will help to establish correct diagnoses, describe the frequency of this disease, and possibly identify predictors for AIC.