Incidence and impact of brain lesions and cognitive impairment after CABG with moderate or severe cerebral artery stenosis seen on low-field MRI
Bibliographic record
Abstract
OBJECTIVE: The study aimed to assess the incidence and impact of brain lesions and cognitive impairment after coronary artery bypass grafting (CABG) in patients with moderate-to-severe cerebral artery stenosis using low-field MRI. METHODS: 110 patients with moderate-to-severe cerebral artery stenosis who underwent CABG between November 2023 and May 2024 were enrolled. Postoperative brain lesions were evaluated using low-field MRI. Cognitive decline was defined as a reduction of ≥3 points in the Montreal Cognitive Assessment score from baseline. Risk factors associated with postoperative brain lesions and cognitive impairment were identified in univariate and multivariate logistic regression analyses. RESULTS: A total of 110 patients were enrolled, with a mean age of 65±7 years and 22 (20.0%) were female. New brain lesions were identified in 24 patients (21.8%). Logistic regression analysis identified operation time (OR 1.014, 95% CI 1.003 to 1.025, p=0.013) to be independently associated with brain lesions. 22.2% of the patients (20/90) experienced postoperative cognitive decline. New brain lesions were independently associated with cognitive decline (OR 4.651, 95% CI 1.158 to 18.676, p=0.030), particularly the new brain lesions impairing orientation ability (OR 4.534, 95% CI 1.438 to 14.289, p=0.010). CONCLUSIONS: Low-field MRI has proven effective in detecting new brain lesions after CABG. Both postoperative new brain lesions and CABG operation were significant contributors to cognitive decline.
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How this classification was reachedexpand
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) | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".