Toronto aortic stenosis quality of life questionnaire (TASQ): validation in TAVI patients
Bibliographic record
Abstract
BACKGROUND: Aortic stenosis (AS) is a common cardiac condition whose prevalence increases with age. The symptom burden associated with severe aortic stenosis (AS) can introduce significant lifestyle disruptions and if left untreated can lead to a poor prognosis. Quality of life (QoL) is an important consideration in these patients. The TASQ is a QoL tool that was developed for aortic stenosis patients. We evaluated the psychometric properties of this specific questionnaire in patients who underwent transcatheter aortic valve implantation (TAVI), which is a therapeutic option for patients with severe aortic stenosis (AS). METHODS: The properties of the TASQ in measuring QoL were evaluated in AS patients undergoing TAVI. Patients presenting for the TAVI procedure (N = 62) were evaluated pre-TAVI, at discharge, 1-month, and 3-month follow-ups. Demographic information as well as caregiver status, and daily activities were recorded. In addition to the TASQ, they completed the KCCQ (Kansas City Cardiomyopathy Questionnaire) and the IIRS (Illness Intrusiveness Rating Scale). RESULTS: The TASQ is a 16-item self-administered questionnaire that assesses AS-specific QoL across five domains: physical symptoms; physical limitations; emotional impact; social limitations, and health expectations. TASQ subscales are internally consistent (α = 0.74-0.96) and showed significant improvements from baseline across assessments (p < 0.001). Construct validity evidence was demonstrated by correlations consistent with theoretically derived hypotheses across time points. CONCLUSIONS: The TASQ is a brief measure of AS-specific QoL that is sensitive to change in patients undergoing TAVI. Items on the TASQ capture important QoL concerns reported by AS patients, suggesting this is a measure of relevant and meaningful outcomes for this patient population. Detection of early improvements in QoL by the TASQ is promising, with important implications for the evaluation of procedural outcomes in this population.
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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 | 0.002 | 0.005 |
| 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".