Perioperative covert stroke in patients undergoing coronary artery bypass graft surgery
Bibliographic record
Abstract
Objectives: Covert stroke is a complication of coronary artery bypass graft surgery that is increasingly recognized as a serious problem. In noncardiac surgery settings, covert stroke is associated with the development of delirium, long-term cognitive decline, and future clinical stroke. Therefore, we sought to determine the feasibility of conducting a large, prospective cohort study of the influence of covert stroke on neurocognitive outcomes in patients undergoing coronary artery bypass graft surgery. Methods: NeuroVISION Cardiac pilot was a prospective cohort study enrolling patients aged ≥21 years undergoing isolated coronary artery bypass graft surgery to receive diffusion-weighted magnetic resonance imaging of the brain after surgery to identify patients with covert stroke. Patients were screened for postoperative delirium in-hospital and were administered questionnaires of cognitive and global function (once before and twice after surgery). Regional cerebral oxygen saturation was recorded during surgery using near-infrared spectroscopy. Results: Between March 27, 2017, and February 11, 2018, 50 of 66 patients enrolled (76%) completed the brain magnetic resonance imaging (1 patient per week). Among the 49 patients included in the analysis, 19 (39%; 95% confidence interval, 26%-53%) experienced perioperative covert stroke and 3 (6%) had a clinical stroke within 30 days of surgery. Postoperative delirium occurred in 5 (26%) patients with covert stroke and in 3 (10%) patients who did not experience covert stroke. Conclusions: The NeuroVISION Cardiac pilot study established the feasibility of conducting a large, prospective cohort study of the determinants and consequences of covert stroke in patients undergoing coronary artery bypass graft surgery.
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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 | 0.000 | 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 | 0.001 |
| 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".