A Simple Score to Identify Super-Responders to Sacubitril/Valsartan in Ambulatory Patients With Heart Failure

Electrocardiographic predictors of response to sacubitril/valsartan therapy in heart failure with reduced ejection fraction

BACKGROUND

Sacubitril/valsartan (SV) is currently recommended as a first-line therapy in patients with heart failure and reduced ejection fraction (HFrEF) due to its significant clinical and prognostic benefit; however, not all patients respond to therapy and predictors of clinical response to SV remain under-studied.

AIMS

To identify electrocardiographic (ECG) predictors of response to SV therapy in HFrEF patients.

METHODS

A retrospective analysis of a hospital heart failure registry was undertaken. Consecutive HFrEF patients (New York Heart Association class II-III) on maximal-dose SV were studied. Response to SV was defined as ≥10% relative improvement in left ventricular ejection fraction (LVEF) at 3-months post-maximal-dose therapy. Pre-therapy ECGs were retrospectively analyzed for axes and standard wave and interval durations. Logistic regression was used to estimate odds ratios and 95% confidence intervals for associations between predictors and therapeutic response. Backward stepwise regression was employed to develop a parsimonious model.

RESULTS

P-wave duration (PWD) 100-120 ms, PWD >120 ms, and QTc >460 ms were associated with response to SV on univariate analysis: OR 18.00 (4.45-122.90), 5.00 (1.47-20.42), and 3.10 (1.18-9.22), respectively. The preferred model that included the former two predictors in combination with pre-therapy creatinine, mineralocorticoid receptor antagonist use, and LVEF was highly selective (area under the ROC curve = 0.868).

CONCLUSIONS

Prolongation of both PWD and QTc interval on baseline ECG in HFrEF patients is predictive of therapeutic response to maximal-dose SV therapy and may indicate early cardiac remodeling that is highly amenable to reversal.

Haemodynamic forces predicting remodelling and outcome in patients with heart failure treated with sacubitril/valsartan

AIMS

A novel tool for the evaluation of left ventricular (LV) systo-diastolic function through echo-derived haemodynamic forces (HDFs) has been recently proposed. The present study aimed to assess the predictive value of HDFs on (i) 6 month treatment response to sacubitril/valsartan in heart failure with reduced ejection fraction (HFrEF) patients and (ii) cardiovascular events.

METHODS AND RESULTS

Eighty-nine consecutive HFrEF patients [70% males, 65 ± 9 years, LV ejection fraction (LVEF) 27 ± 7%] initiating sacubitril/valsartan underwent clinical, laboratory, ultrasound and cardiopulmonary exercise testing evaluations. Patients experiencing no adverse events and showing ≥50% reduction in plasma N-terminal pro-B-type natriuretic peptide and/or ≥10% LVEF increase over 6 months were considered responders. Patients were followed up for the composite endpoint of HF-related hospitalisation, atrial fibrillation and cardiovascular death. Forty-five (51%) patients were responders. Among baseline variables, only HDF-derived whole cardiac cycle LV strength (wLVS) was higher in responders (4.4 ± 1.3 vs. 3.6 ± 1.2; p = 0.01). wLVS was also the only independent predictor of sacubitril/valsartan response at multivariable logistic regression analysis [odds ratio 1.36; 95% confidence interval (CI) 1.10-1.67], with good accuracy at receiver operating characteristic (ROC) analysis [optimal cutpoint: ≥3.7%; area under the curve (AUC) = 0.736]. During a 33 month (23-41) median follow-up, a wLVS increase after 6 months (ΔwLVS) showed a high discrimination ability at time-dependent ROC analysis (optimal cut-off: ≥0.5%; AUC = 0.811), stratified prognosis (log-rank p < 0.0001) and remained an independent predictor for the composite endpoint (hazard ratio 0.76; 95% CI 0.61-0.95; p < 0.01), after adjusting for clinical and instrumental variables.

CONCLUSIONS

HDF analysis predicts sacubitril/valsartan response and might optimise decision-making in HFrEF patients.

Early Prediction of Left Ventricular Reverse Remodeling in First-Diagnosed Idiopathic Dilated Cardiomyopathy: A Comparison of Linear Model, Random Forest, and Extreme Gradient Boosting

Introduction: Left ventricular reverse remodeling (LVRR) is associated with decreased cardiovascular mortality and improved cardiac survival and also crucial for therapeutic options. However, there is a lack of an early prediction model of LVRR in first-diagnosed dilated cardiomyopathy.

Methods: This single-center study included 104 patients with idiopathic DCM. We defined LVRR as an absolute increase in left ventricular ejection fraction (LVEF) from >10% to a final value >35% and a decrease in left ventricular end-diastolic diameter (LVDd) >10%. Analysis features included demographic characteristics, comorbidities, physical sign, biochemistry data, echocardiography, electrocardiogram, Holter monitoring, and medication. Logistic regression, random forests, and extreme gradient boosting (XGBoost) were, respectively, implemented in a 10-fold cross-validated model to discriminate LVRR and non-LVRR, with receiver operating characteristic (ROC) curves and calibration plot for performance evaluation.

Results: LVRR occurred in 47 (45.2%) patients after optimal medical treatment. Cystatin C, right ventricular end-diastolic dimension, high-density lipoprotein cholesterol (HDL-C), left atrial dimension, left ventricular posterior wall dimension, systolic blood pressure, severe mitral regurgitation, eGFR, and NYHA classification were included in XGBoost, which reached higher AU-ROC compared with logistic regression (AU-ROC, 0.8205 vs. 0.5909, p = 0.0119). Ablation analysis revealed that cystatin C, right ventricular end-diastolic dimension, and HDL-C made the largest contributions to the model.

Conclusion: Tree-based models like XGBoost were able to early differentiate LVRR and non-LVRR in patients with first-diagnosed DCM before drug therapy, facilitating disease management and invasive therapy selection. A multicenter prospective study is necessary for further validation.

Clinical Trial Registration:http://www.chictr.org.cn/usercenter.aspx (ChiCTR2000034128).