Quality of Life after Transcatheter Aortic Valve Replacement in Sarcopenic Patients Using the Toronto Aortic Stenosis Quality of Life Questionnaire
Bibliographic record
Abstract
Background: Sarcopenia is the core component of frailty; however, its role in patients undergoing transcatheter aortic valve replacement (TAVR) is a matter of debate. The Toronto Aortic Stenosis Quality of Life Questionnaire (TASQ) is a validated instrument for assessing quality of life (QoL) in patients with severe aortic stenosis (AS). Aims: We aim to evaluate the QoL of sarcopenic and non-sarcopenic patients with severe AS undergoing TAVR. Methods: TASQ was prospectively administered to patients undergoing TAVR. All patients completed the TASQ before TAVR and at a 3-month follow-up. The study population was divided in two groups according to sarcopenic status. The primary endpoint was the TASQ score in the sarcopenic and non-sarcopenic cohorts. Results: In total, 99 patients were eligible for the analysis. In both sarcopenic (n = 56) and non-sarcopenic (n = 43) cohorts, significant changes were observed in the overall TASQ score and in all but one (i.e., health expectations) of the individual domains (p < 0.01). Sarcopenic and non-sarcopenic patients showed substantial improvements across TASQ subscores. The mean change in overall TASQ score at three months revealed a significant improvement in both cohorts (p < 0.01). Health expectations worsened in sarcopenic patients at the 3-month follow-up (p = 0.06). Conclusions: The TASQ questionnaire revealed changes in QoL after TAVR, regardless of patients’ sarcopenic status. Health status improved substantially in both sarcopenic and non-sarcopenic patients following TAVR. Lack of improvement in health expectations seems to depend on patients’ expectations regarding the procedure and specific aspects in the evaluation of the outcome.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".