Cognitive Outcomes After Transcatheter Aortic Valve Implantation: A Metaanalysis
Bibliographic record
Abstract
OBJECTIVES: To quantitatively summarize changes in cognitive performance in individuals with severe aortic stenosis undergoing transcatheter aortic valve implantation (TAVI). DESIGN: Metaanalysis. PARTICIPANTS: Individuals undergoing TAVI (N = 1,065 (48.5% male) from 18 studies, average age ≥80). MEASUREMENTS: The MEDLINE, EMBASE, and Cochrane Central databases were searched for original peer-reviewed reports assessing cognitive performance using standardized cognitive tests before and after TAVI. Data were extracted for cognitive scores before TAVI; perioperatively (within 7 days after TAVI); 1, 3, and 6 months after TAVI, and 12 to 34 months after TAVI (over the long term). Standardized mean differences (SMDs) were generated using random-effects models for changes in cognition at each time point. Metaregression analyses were conducted to assess the association between population and procedural characteristics and cognitive outcomes. Risk of bias was assessed. RESULTS: There were no significant changes from baseline in perioperative cognitive performance (SMD = 0.05, 95% confidence interval (CI) = -0.08-0.18; z = 0.75, P = .46), although overall cognitive performance had improved significantly 1 month after TAVI (SMD = -0.33, 95% CI = -0.50 to -0.16; z = 3.83, P < .001). There were no differences in cognitive performance 3 and 6 months after TAVI or over the long term. Cognitive outcomes were not associated with any covariates in regression analyses. CONCLUSION: Cognitive performance is preserved after TAVI, suggesting TAVI is not detrimental to cognition.
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 | 0.013 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.046 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".