Haemodynamic Forces Predicting Remodelling and Outcome in Patients with Heart Failure Treated with Sacubitril/Valsartan
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".