Psychometric Properties of the Kansas City Cardiomyopathy Questionnaire in a Surgical Population of Patients With Aortic Valve Stenosis
Bibliographic record
Abstract
The 12-item version of the Kansas City Cardiomyopathy Questionnaire (KCCQ-12) was originally developed for patients with heart failure but has been used and tested among patients with severe aortic stenosis (AS) who underwent transcatheter aortic valve implantation. Whether the instrument is suitable for patients with AS who underwent surgical aortic valve replacement (SAVR) is currently unknown. Thus, we aimed to investigate the psychometric properties of the KCCQ-12 before and after SAVR among patients with severe AS. We conducted a prospective cohort of 184 patients with AS who completed the KCCQ-12 and the EuroQol 5 Dimension 5 Levels before and 4 weeks after surgery. Construct validity was investigated with hypothesis testing and an analysis of Spearman's correlation between the two instruments. Structural validity was investigated with explorative and confirmatory factor analyses and reliability with Cronbach's α. All analyses were conducted on data from the two time points (preoperatively and four weeks after surgery). The hypothesis testing revealed how the New York Heart Association class was significantly correlated with the preoperative KCCQ-12 total score (higher New York Heart Association class, worse score). A longer length of hospital stay and living alone were significantly associated with poorer postoperative KCCQ-12 total score. KCCQ-12 and EuroQol 5 Dimension 5 Levels were moderately correlated in most domains/the total score/Visual Analogue Scale score. Principal component analyses revealed two 3-factor structures. The confirmatory factor analyses did not support the original model at any time point. Cronbach's α ranged from 0.22 to 0.84 in three preoperative factors and from 0.39 to 0.76 in the postoperative factors. The total Cronbach's α was 0.83 for the suggested preoperative 3-factor model and 0.83 for the postoperative model. In conclusion, the Danish version of the KCCQ-12 tested in a population of patients with AS who underwent SAVR appears to have acceptable construct validity, whereas structural validity cannot be confirmed for the original four-factor model. Overall reliability is good.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.011 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".