Survival after Aortic Valve Replacement for Aortic Regurgitation: Prediction from Preoperative Contractility Measurement.
Academic Article
Overview
abstract
BACKGROUND: Noninvasive measurement of myocardial contractility (end-systolic wall stress-adjusted change in left ventricular ejection fraction from rest to exercise [ΔLVEF - ΔESS]) predicts heart failure, subnormal LVEFrest, and sudden death in asymptomatic patients with chronic severe aortic regurgitation (AR). Here we assess the relation of preoperative ΔLVEF - ΔESS to survival after aortic valve replacement (AVR). METHODS: Patients who underwent AVR for chronic, isolated, pure severe AR (n = 66) were followed for 13.0 ± 6.4 event-free years. Preoperative ΔLVEF - ΔESS (from combined echocardiographic and radionuclide cineangiographic data) enabled cohort stratification into 3 terciles (-1 to -11% [normal or mild] contractility deficit, -12 to -16% [moderate], and ≤-17% [severe], identical with segregation in our earlier study) to relate preoperative contractility to postoperative survival and to age- and gender-matched US census data. RESULTS: Since AVR, 22 patients died (average annual risk [AAR] for all-cause mortality for the entire co hort = 3.15%). Preoperative ΔLVEF - ΔESS predicted postoperative survival (p = 0.009, log rank test). By contractility terciles, all-cause AARs were 1.44, 2.58, and 6.40%. Survival was lower than among US census comparators (p < 0.02), but the "mild" tercile was indistinguishable from census data (p = ns). By multivariable Cox regression, survival prediction by pre-AVR ΔLVEF - ΔESS was independent of, and superior to, prediction by age at surgery, gender, preoperative functional class, LVEFrest, LVEFexercise, change in LVEFrest to exercise, and LV diastolic or systolic dimensions (p ≤ 0.01, pre-AVR ΔLVEF - ΔESS vs. other covariates). CONCLUSION: In severe AR, preoperative contractility predicts post-AVR survival and may be prognostically superior to clinical, geometric and performance descriptors, potentially impacting on patient selection for surgery.
