Left ventricular ejection time is an independent predictor of incident heart failure in a community‐based cohort. (4th September 2017) - Biering‐Sørensen, Tor; Querejeta Roca, Gabriela; Hegde, Sheila M.; Shah, Amil M.; Claggett, Brian; Mosley, Thomas H.; Butler, Kenneth R.; Solomon, Scott D.
Abstract : Aims: Systolic time intervals change in the progress of cardiac dysfunction. The usefulness of left ventricular ejection time (LVET) to predict cardiovascular morbidity, however, is unknown. Methods and results: We studied middle‐aged African‐Americans from one of four cohorts of the Atherosclerosis Risk in Communities study (Jackson cohort, n =1980) who underwent echocardiography between 1993 and 1995. Left ventricular ejection time was measured by pulsed‐wave Doppler of the left ventricular outflow tract and related to outcomes. A shorter LVET was associated with younger age, male sex, higher diastolic blood pressure, higher proportion of diabetes, higher heart rate, higher blood glucose levels and worse fractional shortening. During a median follow‐up of 17.6 years, 384 (19%) had incident heart failure (HF), 158 (8%) had a myocardial infarction, and 587 (30%) died. In univariable analysis, a lower LVET was significantly associated with increased risk of all events ( P <0.05 for all). However, after multivariable adjustment for age, sex, hypertension, diabetes, body mass index, heart rate, systolic and diastolic blood pressure, fractional shortening and left atrial diameter, LVET remained an independent predictor only of incident HF [hazard ratio 1.07 (1.02–1.14), P =0.010 per 10 ms decrease]. In addition, LVET provided incremental prognostic information to the known risk factors included in the Framingham risk score, in regard to predicting all outcomes except for myocardial infarction. Conclusion: Left ventricular ejection time is an independent predictor of incident HF in a community‐based cohort and provides incremental prognostic information on the risk of future HF and death when added to known risk prediction models.