Patient values and preferences on valve replacement for aortic stenosis: a systematic review
Bibliographic record
Abstract
The review aims to summarise evidence addressing patients' values, preferences and practical issues on deciding between transcatheter aortic valve insertion (TAVI) and surgical aortic valve replacement (SAVR) for aortic stenosis. We searched databases and grey literature until June 2020. We included studies of adults with aortic stenosis eliciting values and preferences about treatment, excluding medical management or palliative care. Qualitative findings were synthesised using thematic analysis, and quantitative findings were narratively described. Evidence certainty was assessed using CERQual (Confidence in the Evidence from Reviews of Qualitative Research) and GRADE (Grading of Recommendations Assessment, Development and Evaluation). We included eight studies. Findings ranged from low to very low certainty. Most studies only addressed TAVI. Studies addressing both TAVI and SAVR reported on factors affecting patients' decision-making along with treatment effectiveness, instead of trade-offs between procedures. Willingness to accept risk varied considerably. To improve their health status, participants were willing to accept higher mortality risk than current evidence suggests for either procedure. No study explicitly addressed valve reintervention, and one study reported variability in willingness to accept shorter duration of known effectiveness of TAVI compared with SAVR. The most common themes were desire for symptom relief and improved function. Participants preferred minimally invasive procedures with shorter hospital stay and recovery. The current body of evidence on patients' values, preferences and practical issues related to aortic stenosis management is of suboptimal rigour and reports widely disparate results regarding patients' perceptions. These findings emphasise the need for higher quality studies to inform clinical practice guidelines and the central importance of shared decision-making to individualise care fitted to each patient.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".