Association of reduced peak left atrial strain with supraventricular arrhythmia in adults with congenital heart disease.
Clément NussbaumerMarkus SchwerzmannElena ElchinovaEleni GouloutiDaniel ToblerMatthias GreutmannKerstin WustmannAndrea PapaFabienne SchwitzPublished in: The international journal of cardiovascular imaging (2024)
Atrial arrhythmias are an important cause of morbidity and mortality in adults with congenital heart disease (ACHD). In acquired heart disease, the left atrial (LA) strain has been shown to predict supraventricular tachyarrhythmias (SVT). This study aimed to investigate whether reduced LA strain is associated with SVT in ACHD patients. This retrospective, single-center cohort study collected baseline clinical and echocardiographic data of 206 ACHD patients (157 left heart defect, 49 right heart defect). Patients with sinus rhythm at baseline and a 5-year follow-up (median age 29, IQR 22-41 years) were included. Diagnosis of sustained SVT was determined from clinical reports during the follow-up period. New or recurrent sustained SVT occurred in 16 patients (7.8%, median follow-up of 6.2 years). Patients who developed SVT were older, more likely to have diastolic dysfunction, and had larger LA dimensions, left ventricular mass, and a lower peak LA longitudinal strain (PALS). Lower PALS was associated with higher risk of SVT in patients with left and right heart defects. Patients in the lowest quartile for PALS had a 15.9-fold higher hazard ratio of SVT (95% confidence interval, 4.5 to 56.0, p < 0.001) in comparison with the top three quartiles. PALS provides information about the occurrence of SVT in the ACHD population. Including measurement of LA strain in the follow-up of these patients may allow to better identify patients at risk of future atrial arrhythmias.
Keyphrases
- end stage renal disease
- left atrial
- left ventricular
- ejection fraction
- newly diagnosed
- atrial fibrillation
- chronic kidney disease
- heart failure
- peritoneal dialysis
- mitral valve
- prognostic factors
- risk assessment
- patient reported outcomes
- machine learning
- big data
- heart rate
- patient reported
- acute myocardial infarction
- percutaneous coronary intervention
- artificial intelligence
- middle aged