A pilot study of evaluation of cerebral function by S100β protein and near‐infrared spectroscopy during cold and warm cardiopulmonary bypass in infants and children undergoing open‐heart surgery*
Bibliographic record
Abstract
Cerebral injury in children undergoing cardiopulmonary bypass (CPB) remains a major source of morbidity. The effect of cardiopulmonary bypass temperature on cerebral function in terms of serum S100beta protein level and cerebral oxygenation monitored by near infrared spectroscopy (NIRO-300) in children is not known. In this study, 18 children undergoing open-heart surgery at the Hospital for Sick Children in London were equally assigned by minimisation to warm (35 +/- 1 degrees C) or cold (25 +/- 1 degrees C) CPB. Changes in S100beta protein and cerebral oxygenation were studied in both groups. S100beta protein serum level increased significantly after CPB in both groups. There was no significant difference in serum S100beta protein concentrations between the two groups. However, cerebral oxygenation in terms of tissue oxygen index (TOI) was significantly impaired during rewarming from cold CPB. Five patients were desaturated (TOI < 50%) during rewarming in the cold bypass group compared to two in the warm patients. This study supports the use of warm CPB in children undergoing open-heart surgery, although further studies recruiting more patients are warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| 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".