Preoperative visit-care for transcatheter aortic valve replacement: a review
Bibliographic record
Abstract
AIM: The aim of this review is to evaluate and summarize the evidence for preoperative visit-care of transcatheter aortic valve replacement (TAVR) and to provide evidence-based support for clinical intervention. DESIGN: The review presents an evidence summary report, following the standard of the Fudan University Center for Evidence-based Nursing. METHODS: Literature related to preoperative visit-care for transcatheter aortic valve replacement have been retrieved based on the "6S" pyramid model of evidence. The types of literature included systematic reviews, expert consensus, evidence summary, and guidelines. DATA SOURCES: Up To Date, Cochrane Library, Joanna Briggs Institute, National Institute for Health and Care Excellence, Medlive, American Heart Association, Registered Nurses Association of Ontario, Scottish Intercollegiate Guidelines Network, European Society of Cardiology, American College of Cardiology, PubMed, CINAHL, Wanfang database, VIP database, Chinese biomedical literature database, CNKI. The search period is limited to the time when each database was established until February 2024. RESULTS: A total of 18 articles were included in this review, consisting of 1 systematic review, 1 evidence summary, 3 guidelines and 13 expert consensuses. This review summarized 30 pieces of the best evidence for preoperative visit-care for transcatheter aortic valve replacement, encompassing three evidence themes: multidisciplinary team collaboration, preoperative assessment, and preoperative education. CONCLUSION: The study has established an ideal foundation of evidence for preoperative visit-care in TAVR. However, throughout the particular application process, it was crucial to assess the feasibility and relevance of the evidence in clinical practice by taking into account elements such as the application setting, recommendations from experts with diverse expertise, and the preferences of the patients.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.099 |
| 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".