Atrial Fibrillation Catheter Ablation Improves 1-Year Follow-Up Cognitive Function, Especially in Patients With Impaired Cognitive Function
Bibliographic record
Abstract
BACKGROUND: Although atrial fibrillation (AF) has a risk of cognitive dysfunction, it is not clear whether AF catheter ablation improves or worsens cognitive function. This prospective case-control study sought to assess the 1-year serial changes in the cognitive function with or without AF catheter ablation. METHODS: We evaluated the Montreal Cognitive Assessment score in 308 patients (71.4% male, 60.6±9.1 years of age, 34.1% persistent AF) who underwent AF ablation (ablation group) and 50 AF patients on medical therapy who met the same indication for AF ablation (control group), at baseline and 3 and 12 months after enrollment. Cognitive impairment was defined as a published cutoff score of <23 points. To exclude any learning effects, we used the practice-adjusted reliable change index for assessing the cognitive changes. RESULTS: Preablation cognitive impairment was detected in 18.5% (57/308). The Montreal Cognitive Assessment score significantly improved 1 year after radiofrequency catheter ablation in both overall ablation group (24.9±2.9-26.4±2.5; P<0.001) and the propensity-matched ablation group (25.4±2.4-26.5±2.3; P<0.001), but not in the control group (25.4±2.5-24.8±2.5; P=0.012). Preablation cognitive impairment (odds ratio, 13.70; 95% CI, 4.83-38.87; P<0.001) was independently associated with an improvement in the 1-year post-ablation cognitive function. In the reliable change index analyses, 94.7% of propensity-matched ablation group showed an improved/stable cognitive function at the 1-year follow-up. CONCLUSIONS: Catheter ablation of AF, at least, does not deteriorate the cognitive function, but rather improves the performance on 1-year follow-up neurocognitive tests, especially in patients with a preablation cognitive impairment.
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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 | 0.000 |
| 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) | 0.001 | 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".