Perioperative covert stroke in patients undergoing coronary artery bypass graft surgery
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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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) | 0.001 | 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 | 0.001 |
| 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 it