Neurological Impact of Slower Rewarming during Bypass Surgery in Infants
Bibliographic record
Abstract
Abstract Background Hypothermia is a neuroprotective strategy during cardiopulmonary bypass. Rewarming entailing a rapid rise in cerebral metabolism might lead to secondary neurological sequelae. In this pilot study, we aimed to validate the hypothesis that a slower rewarming rate would lower the risk of cerebral hypoxia and seizures in infants. Methods This is a prospective, clinical, single-center study. Infants undergoing cardiac surgery in hypothermia were rewarmed either according to the standard (+1°C in < 5 minutes) or a slow (+1°C in > 5–8 minutes) rewarming strategy. We monitored electrocortical activity via amplitude-integrated electroencephalography (aEEG) and cerebral oxygenation by near-infrared spectroscopy during and after surgery. Results Fifteen children in the standard rewarming group (age: 13 days [5–251]) were cooled down to 26.6°C (17.2–29.8) and compared with 17 children in the slow-rewarming group (age: 9 days [4–365]) with a minimal temperature of 25.7°C (20.1–31.4). All neonates in both groups (n = 19) exhibited suppressed patterns compared with 28% of the infants > 28 days (p < 0.05). During rewarming, only 26% of the children in the slow-rewarming group revealed suppressed aEEG traces (vs. 41%; p = 0.28). Cerebral oxygenation increased by a median of 3.5% in the slow-rewarming group versus 1.5% in the standard group (p = 0.9). Our slow-rewarming group revealed no aEEG evidence of any postoperative seizures (0 vs. 20%). Conclusion These results might indicate that a slower rewarming rate after hypothermia causes less suppression of electrocortical activity and higher cerebral oxygenation during rewarming, which may imply a reduced risk of postoperative seizures.
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How this classification was reachedexpand
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| 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 teacher head, 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".