Right ventricular deformation and right ventricular-arterial coupling in patients with heart failure due to severe aortic stenosis undergoing TAVI: long-term results.
Bibliographic record
Abstract
AIM: To evaluate the long-term prognostic significance of right ventricular (RV) deformation and RV-arterial coupling in a cohort of patients with heart failure (HF) due to severe aortic stenosis (AS) candidate for trans-catheter aortic valve implantation (TAVI). METHODS: The study is a retrospective analysis of 56 patients undergoing echocardiography before TAVI execution. RV function was defined by tricuspid annular plane systolic excursion (TAPSE), fractional area change (FAC), peak systolic myocardial velocity by tissue Doppler imaging (RVSm) and RV longitudinal strain (RVLS). RV-arterial coupling were defined as TAPSE and RVLS normalized for systolic pulmonary artery pressure (sPAP) to obtain afterload-independent parameters: TAPSE/sPAP and RVLS/sPAP, respectively. All-cause mortality was the primary endpoint of survival analysis; composite of death and hospitalization for HF was the secondary endpoint. RESULTS: All patients underwent TAVI from femoral access. Mean age was 81.6±6.3 years and left ventricular ejection fraction was preserved in most patients (51±15%). At 10 years, using Cox regression analysis adjusted for the parameters related to prognosis at univariate analysis, we found that only pre-procedural RVLS was independently associated with all-cause mortality (aHR 1.53, 95% CI 1.10-2.12, P=0.011). RVLS (aHR 7.542, 95% CI 1.325-42.921, P=0.023), sPAP (aHR 1.421, 95% CI 1.045-1.932, P=0.025), TAPSE/sPAP (aHR 4.977, 95% CI 5.425-21.99, P=0.044) and RVLS/sPAP (aHR 2.333, 95% CI 3.9677-12.999, P=0.046) were independently associated with the secondary endpoint. CONCLUSIONS: Among patients with HF due to severe AS undergoing TAVI, deformation imaging (i.e., RVLS) and RV-arterial coupling (i.e., TAPSE/sPAP and RVLS/sPAP) provide better risk stratification at long-term follow up of 10 years than other RV echocardiographic parameters.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".