Prospective Evaluation of Neurocognition in Patients Following Transcatheter Aortic Valve Replacement
Bibliographic record
Abstract
Background Data regarding change in neurocognitive function after transcatheter aortic valve replacement (TAVR) are conflicting. We sought to investigate the change in cognition up to 6 months post-TAVR in patients with mild cognitive impairment (MCI). Methods This is a prospective, observational, nonrandomized, cohort study of patients with MCI who underwent TAVR between February 2022 and June 2023 in a multicenter health care system. The inclusion criteria were TAVR patients with MCI, defined as a score of ≤25/30 on the Mini Montreal Cognitive Assessment (Mini MoCA) exam. The Mini MoCA exam was evaluated pre-TAVR, 30 days post-TAVR, and 6 months post-TAVR. Results Of 81 enrolled TAVR patients, 73 (90.1%) and 66 (81.5%) completed 30-day and 6-month post-TAVR MoCA exams, respectively. The median age was 81 (IQR: 75.0-86.0) years and 47.4% were male. At baseline, history of stroke, transient ischemic attack, and dementia were 17.3, 9.9%, and 9.9%, respectively. The Mini MoCA scores showed a small but significant increase from the preoperative assessment to the 30-day interval (21.0 [17.5-22.5] vs. 22.0 [18.5-24.5]; p < 0.001) and was improved in 64.4% of patients. At 6 months, the Mini MoCA scores were increased in 89.4% of patients and had an absolute and significant increase of 2.3 points compared to preoperative assessment (23.3 [20.5-25.0] vs. 21.0 [17.6-22.9], p < 0.001). Conclusions Among patients with baseline MCI undergoing TAVR, neurocognitive function as measured by the Mini MoCA exam significantly improved at 30 days and 6 months postprocedure. TAVR in the setting of MCI is a safe therapeutic option for patients with aortic valve disease.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".