Cerebral Emboli During Cardiopulmonary Bypass: Effect of Perfusionist Interventions and Aortic Cannulas
Bibliographic record
Abstract
Neuropsychological impairment is a very common complication of cardiopulmonary bypass (CPB). The principal cause of postoperative cognitive impairment is thought to be cerebral microemboli during CPB. We recently investigated the effects of perfusionist interventions and aortic cannulation techniques on cerebral emboli production during coronary bypass (CABG) surgery. Patients undergoing isolated CABG were monitored with continuous transcranial Doppler ultrasonography of the middle cerebral artery. Perfusionist interventions were defined as injections of drugs into the CPB circuit or acquisition of blood samples from the CPB circuit. Patients were randomized to receive either standard cannulation of the ascending aorta or cannulation of the distal aortic arch. Cerebral emboli were detected in all patients. The number of emboli per minute was markedly higher during perfusionist interventions than during other time periods. Patients with increased perfusionist interventions had worse neuropsychological outcomes. Cannulation of the distal aortic arch, with placement of the cannula tip beyond the cerebral vessels, resulted in significantly less cerebral emboli than cannulation of the ascending aorta. Perfusionist interventions are a common source of cerebral microemboli during CPB, and may contribute to postoperative neuropsychological impairment. Care should be taken to minimize the introduction of air into the bypass circuit during CPB. Provided it is performed safely, distal aortic arch cannulation is a useful technique for reducing cerebral emboli during cardiac 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 | 0.005 |
| 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) | 0.001 | 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".