Cerebral Emboli Detected by Transcranial Doppler During Cardiopulmonary Bypass Are Not Correlated With Postoperative Cognitive Deficits
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: High-intensity transient signals (HITS) are the transcranial Doppler representation of both air and solid cerebral emboli. We studied the frequency of HITS associated with different surgical maneuvers during cardiopulmonary bypass for coronary artery bypass graft surgery and their association with postoperative cognitive dysfunction (POCD). METHODS: We combined 356 patients undergoing coronary artery bypass graft from 2 clinical trials who had both neuropsychological testing (before, 1 week and 3 months after surgery) and transcranial Doppler during cardiopulmonary bypass. HITS were grouped into periods that included: cannulation, cardiopulmonary bypass onset, aortic crossclamp-on, aortic crossclamp-off, side clamp-on, side clamp-off, and decannulation. POCD was defined by a decreased combined Z-score of at least 2.0 or reduction in Z-scores of at least 2.0 in 20% of the individual tests. RESULTS: Incidence of POCD was 47.3% and 6.3% at 1 week and 3 months after surgery. There was no association between cardiopulmonary bypass counts of HITS and POCD at 1 week (P=0.617) and 3 months (P=0.110). No differences in HITS counts were identified at any of the surgical periods between patients with and without POCD. Factors affecting HITS counts were surgical period (P<0.0001), blood flow velocity (P=0.012), cardiopulmonary bypass duration (P=0.040), and clinical study (P=0.048). CONCLUSIONS: Although cerebral microemboli have been implicated in the pathogenesis of POCD, in this study that included low-risk patients undergoing coronary artery bypass surgery, there was no demonstrable correlation between the counts of HITS and POCD.
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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 | 0.004 |
| 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 | 0.000 | 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".