Diastolic Dysfunction and Health Status Outcomes After Transcatheter Aortic Valve Replacement
Bibliographic record
Abstract
Background Baseline left ventricular diastolic dysfunction (LVDD) is associated with poor health status in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement (TAVR), but health status improvement after TAVR appears similar across all grades of LVDD. Here, we aim to examine the relationship between changes in LVDD severity and health status outcomes following TAVR. Methods Patients who underwent TAVR and had evaluable LVDD at both baseline and 1 year in the PARTNER (Placement of Aortic Transcatheter Valves) 2 SAPIEN 3 registries and PARTNER 3 trial were analyzed. LVDD grade was evaluated using echocardiography core lab data and an adapted definition of American Society of Echocardiography guidelines. Health status was assessed using the Kansas City Cardiomyopathy Questionnaire Overall Summary (KCCQ-OS) score. The association between ΔLVDD severity and ΔKCCQ-OS was examined using linear regression models adjusted for baseline KCCQ-OS. Results Of 1100 patients, 724 (65.8%), 283 (25.7%), and 93 (8.5%) had grade 0/1, 2, and 3 LVDD at baseline, respectively. At 1 year, LVDD severity was unchanged in 790 (71.8%) patients, improved in 189 (17.2%), and worsened in 121 (11.0%). Among 376 patients with baseline grade 2 or 3 LVDD, 50.3% had improvement in LVDD. In the overall cohort, KCCQ-OS score improved by 21.9 points at 1 year. There was a statistically significant association between change in LVDD severity (improved, unchanged, and worsened) and ΔKCCQ-OS at 1 year ( p = 0.007). Conclusions Change in LVDD grade was associated with change in health status 1 year following TAVR.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".