Abstract 13392: Impaired Oxygen Uptake Efficiency Slope (OUES) Predicts Mortality in Wild-Type Transthyretin Amyloid Cardiomyopathy (ATTRwt-CM)

Abstract

Introduction: Cardiopulmonary exercise testing (CPET) is a prognostic tool for advanced heart failure. Whether exercise metrics can provide incremental mortality prediction in ATTRwt-CM has not been well-studied. Hypothesis: We hypothesize CPET metrics improve mortality prediction in ATTRwt-CM. Methods: A retrospective review was conducted in ATTRwt-CM patients evaluated at the BU Amyloidosis Center between 2009-2019 who underwent CPET testing. Baseline demographic, clinical, and mortality data was collected. Continuous and categorical variables were compared using paired t-testing and chi-square testing, respectively. Baseline variable association with mortality was evaluated using logistic regression. Kaplan-Meier curves were used for survival estimation and Hazard ratios (HR) were estimated using Cox proportional hazards regression analysis. Results: A total of 136 patients with ATTRwt-CM were analyzed with median follow-up of 4 years (IQR 2.4, 5.6) with 43% deaths (n=59) during follow-up. Differences in baseline characteristics and metrics between individuals with and without mortality are shown in the table. Peak VO 2 , V E /VCO 2 , ventilatory threshold, heart rate recovery, and OUES were significantly associated with mortality. Using backwards stepwise regression, only OUES remained significantly associated with mortality among CPET variables. Using multivariable Cox survival analysis (adjusting for age, NYHA, eGFR, LVEF, troponin I, and BNP), OUES remained significantly associated with mortality (HR 0.25, 95% CI 0.08 - 0.77; p=0.02). The addition of OUES to troponin I, BNP, GLS, and eGFR increased the Wald chi-square statistic from 22.5 to 26.5 (p=0.01). Conclusions: The addition of OUES in ATTRwt-CM improves mortality prediction when added to current disease staging biomarkers: troponin I, BNP, GLS, and eGFR. This study highlights the incremental strength in outcome prediction using an exercise parameter, OUES, in ATTRwt-CM.