Do Surface-Modifying Additive Circuits Reduce the Rate of Cerebral Microemboli During Cardiopulmonary Bypass?
Bibliographic record
Abstract
The objective of this study was to determine if surface-modifying additive (SMA) cardiopulmonary bypass (CPB) circuits are associated with a lower rate of cerebral microemboli during CPB compared with standard circuits. In a 2 x 2 factorial design, patients undergoing coronary artery bypass graft surgery were randomized to SMA or standard CPB circuits (with and without methyl-prednisolone). Transcranial Doppler was used to detect high-intensity transient signals (HITS) in both middle cerebral arteries. HITS were counted from onset to end of CPB. Intervals of interest were as follows: period 1, from CPB onset to aortic cross-clamping; period 2, from aortic cross-clamping to immediately before de-clamping; period 3, from aortic declamping to before aortic side-clamping; period 4, from the application of the aortic side clamp to immediately before the release of the side clamp; period 5, from aortic side clamp release to the end of CPB. There were 14 patients in each circuit group. No significant differences were found on the partial and total counts of HITS (medians [25th, 75th percentile]) between patients exposed to standard (total count: 228 HITS [174, 2801) and SMA circuits (total count: 156 HITS [104, 356]; p = .427). The median of the sum of HITS per patient associated with perfusionist interventions was not different between both circuit groups (standard: 17 HITS [7, 80]; SMA: 43 HITS [13, 168]; p = .085). This study, with a sample size of 28 patients, indicates that it is unlikely to find any difference in the count of HITS during CPB that is greater than 117 HITS between the two CPB circuits. Moreover, our findings emphasize the relevance of minimizing additional sources of cerebral microembolization during CPB that are not directly related to the biocompatible nature of the SMA CPB circuit.
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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 | 0.000 | 0.001 |
| 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".