Comparison of two different extracorporeal circuits on cerebral embolization during cardiopulmonary bypass in children
Bibliographic record
Abstract
OBJECTIVE: To compare the effect of two different extracorporeal circuits on the counts of high-intensity transient signals (HITS) during pediatric cardiopulmonary bypass (CPB). METHODS: Transcranial Doppler was used to detect HITS associated with extracorporeal sources during the period of aortic crossclamping in the middle cerebral artery of children undergoing CPB. Based on body size, children were assigned one of two extracorporeal circuits (A or B). Circuit A included a D-705 oxygenator and associated reservoir, and circuit B included a Lilliput oxygenator and reservoir. Patients were further classified into two groups according to the complexity of surgical repair: single simple lesions or multiple complex lesions. RESULTS: We studied 109 pediatric patients. Surgery for multiple complex lesions was associated with longer periods of aortic crossclamping and CPB (p < 0.0001). The median count of extracorporeal HITS was 12 (25th, 75th percentiles: 3, 51). The type of extracorporeal circuit (p = 0.012) and the complexity of surgical repair (p < 0.0001) had an effect on the HITS counts. The use of circuit A was associated with higher HITS counts during surgery for multiple complex lesions compared to single simple lesions (p < 0.0001). Conversely, no differences were found with the use of circuit B between these two surgical groups (p > 0.25). During surgery for multiple complex lesions, patients treated with circuit A showed higher HITS counts than those with circuit B (p < 0.01), but there were no circuit-related differences in HITS counts (p = 0.30) during single simple lesions. CONCLUSION: Variations in the design characteristics of extracorporeal circuits can increase cerebral emboli during CPB in children. This may be related to the reduced ability of some circuits to remove emboli during long periods of CPB for complex congenital heart-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) | 0.000 | 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 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".