Toronto Aortic Stenosis Quality of Life Questionnaire (TASQ): Validation in Polish Patients with Aortic Stenosis
Bibliographic record
Abstract
Background/Objectives: Quality of life (QoL) is recognized as a clinically significant outcome measure among patients with aortic stenosis (AS). However, there is no validated, AS-specific questionnaire available in Poland for assessing the QoL in AS patients. The aim of the study was to determine the psychometric properties of the Polish version of the Toronto Aortic Stenosis Quality of Life Questionnaire (the TASQ). Methods: The study involved 113 patients with severe AS (including 59 women), aged 74 to 82 years [mean age 77 years], hospitalized at the department of cardiology in 2024. The standardized questionnaires were used to assess the level of QoL, the TASQ, and the Minnesota Living with Heart Failure Questionnaire (the MLHFQ). Results: The mean QoL level assessed by the TASQ was 60.72 ± 22.82. The Cronbach’s alpha for the entire TASQ was 0.919, for the emotional impact subscale 0.873, and for the physical limitation subscale 0.861. Satisfactory values of fit measures were obtained for a five-factor structure (RMSEA < 0.01; CFI > 0.99). The loadings of each item were statistically significant (p < 0.001). The MLHFQ score correlated significantly (p < 0.001) and positively (r > 0) with the score on the scales of physical symptoms (r = 0.479), physical limitations (r = 0.662), social limitations (r = 0.597), emotional impact (r = 0.638), and overall QoL (r = 0.712). Conclusions: Patients with severe AS exhibit low QoL. The TASQ has very good psychometric properties and can be used to assess the QoL in the population of Polish patients with AS.
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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 | 0.004 |
| 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".