Structural valve deterioration after transcatheter aortic valve implantation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Transcatheter aortic valve implantation (TAVI), widely used to treat high-risk patients with severe symptomatic aortic stenosis, has recently been extended to younger patients at lower operative risk in whom long-term durability of TAVI devices is an important concern. Therefore, we conducted a systematic review and meta-analysis of observational studies addressing the frequency of structural valve deterioration (SVD) after TAVI. METHODS: We searched Medline, Embase, Cochrane Database of Systematic Reviews, and Cochrane CENTRAL from 2002 to September 2016. We included observational studies following patients with TAVI for at least 2 years. Independently and in duplicate, we evaluated study eligibility, extracted data, and assessed risk of bias for SVD post-TAVI. Our review used the GRADE system to assess quality of evidence. We pooled incidence rates using a random effects model. RESULTS: Thirteen studies including 8914 patients, with a median follow-up between 1.6 and 5 years, reported an incidence of SVD post-TAVI between 0 to 1.34 per 100 patient years. The pooled incidence of SVD was 28.08 per 10 000 patients/year (95% CI 2.46 to 73.44 per 100 patient years). Of those who developed SVD, 12% underwent valve re-intervention. Confidence in the evidence was moderate due to inconsistency among studies. CONCLUSION: Structural valve deterioration is probably an infrequent event within the first 5 years after TAVI. Ascertaining the impact of SVD and the need for valve-related re-interventions to inform recommendations for patients with a longer life-expectancy will require studies including a large number of patients with longer follow-up (>10 years).
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.
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) | 0.001 | 0.008 |
| 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 it