Cardiac rehabilitation to improve health-related quality of life following trans-catheter aortic valve implantation: a randomised controlled feasibility study
Bibliographic record
Abstract
Abstract Objectives Transcatheter aortic valve implantation (TAVI) is often undertaken in the oldest frailest cohort of patients undergoing cardiac interventions. We plan to investigate the potential benefit of cardiac rehabilitation (CR) in this vulnerable population. Design We undertook a pilot randomised trial of CR following TAVI to inform the feasibility and design of a future randomised clinical trial (RCT). Participants We screened patients undergoing TAVI at a single institution between June 2016 and February 2017. Interventions Participants were randomised post-TAVI to standard of care (control group) or standard of care plus exercise-based CR (intervention group). Outcomes We assessed recruitment and attrition rates, uptake of CR, and explored changes in 6-min walk test, Nottingham Activities of Daily Living, Fried and Edmonton Frailty scores and Hospital Anxiety and Depression Score, from baseline (30 days post TAVI) to 3 and 6 months post randomisation. We also undertook a parallel study to assess the use of the Kansas City Cardiomyopathy Questionnaire (KCCQ) in the post-TAVI population. Results Of 82 patients screened, 52 met the inclusion criteria and 27 were recruited (3 patients/month). In the intervention group, 10/13 (77%) completed the prescribed course of 6 sessions of CR (mean number of sessions attended 7.5, SD 4.25) over 6 weeks. At 6 months, all participants were retained for follow-up. There was apparent improvement in outcome scores at 3 and 6 months in control and CR groups. There were no recorded adverse events associated with the intervention of CR. The KCCQ was well accepted in 38 post-TAVI patients: mean summary score 72.6 (SD 22.6). Conclusions We have demonstrated the feasibility of recruiting post-TAVI patients into a randomised trial of CR. We will use the findings of this pilot trial to design a fully powered multicentre RCT to inform the provision of CR and support guideline development to optimise health-related quality of life outcomes in this vulnerable population. Retrospectively registered 3rd October 2016 clinicaltrials.gov NCT02921880 . Trial registration Clinicaltrials.Gov identifier NCT02921880
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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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".