Incidence, characteristics and functional implications of cerebral embolic lesions after the MitraClip procedure
Bibliographic record
Abstract
AIMS: This study aimed to assess the incidence and impact of cerebral embolic events after the MitraClip procedure. METHODS AND RESULTS: Twenty-seven high-risk patients (logistic EuroSCORE I 25±15%) underwent the MitraClip procedure and cerebral diffusion-weighted magnetic resonance imaging (MRI) in median two days before and three days after the procedure. On the same day, neurocognitive function was assessed using the Montreal Cognitive Assessment (MoCA) questionnaire and thorough clinical examination. Comparison of pre- and post-interventional MRI showed that 23 of 27 patients (85.7%) had newly acquired microembolic lesions with in median three (interquartile range 1-9) new lesions per patient. Of these, three patients (11.1%) had lesions with diameter >5 mm. Patients with >3 new cerebral embolic lesions (n=13, 48%) had a lower post-interventional MoCA score in comparison to patients with ≤3 embolic lesions (23.6±3.6 vs. 20.3±4.5; p=0.046) in univariate analysis. Multivariate stepwise regression analysis identified device time as an independent predictor of the number of post-procedural new lesions (p=0.003) and, for reduced post-interventional MoCA score, a low MoCA score at baseline (p<0.001). CONCLUSIONS: The MitraClip procedure results in new ischaemic cerebral lesions in the vast majority of patients. Preliminary data suggest that these lesions are clinically without significant impact on global cognitive function. ClinicalTrials.gov: NCT01288976.
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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 | 0.000 | 0.004 |
| 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 | 0.001 | 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".