Delayed rises in serum S100B levels and adverse neurological outcome in infants and children undergoing cardiopulmonary bypass
Bibliographic record
Abstract
BACKGROUND: The protein S100B is a marker of brain injury. Early after cardiopulmonary bypass (CPB), serum S100B levels are artefactually high. We investigated whether delayed (48 h) rise in S100B levels may have a role in detecting brain injury after CPB. METHODS: Data from 43 children were analysed in this study. Samples were collected at preincision and 30 min, 24 and 48 h postbypass and then analysed by using a commercially available radioimmunoassay (Sangtec100). Charts were reviewed at 3-5 months for evidence of neurological injury. RESULTS: S100B levels were high preoperatively in neonates and universally high immediately postbypass. In 36 children, samples were available for all time points. Compared with preoperative levels, rises occurred at both 24 and 48 h in three patients, only at 24 h in four patients and only at 48 h in three patients. Two patients had evidence of neurological injury. A rise at 48 h was associated with neurological injury (odds ratio 33.9, P < 0.03, 95% CI 1.39-827). There was no association between neurological injury and S100B levels at 24 h. Both the patients with neurological injury had rises at 48 h that were significantly higher than patients with rises at 48 h without injury. CONCLUSIONS: The results of this study suggest that monitoring S100B levels in the late postoperative period may still have a role in detecting neurological injury after cardiac surgery in children. Consistent with previous observations, S100B is high preoperatively in neonates and early postbypass in all patients.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".