A comparison of three dose timings of methylprednisolone in infant cardiopulmonary bypass
Bibliographic record
Abstract
Although commonly used in pediatric cardiopulmonary bypass (CPB) optimal dose and timing of steroid administration is unclear. We hypothesized that early administration of a commonly used dose of methylprednisolone given the evening before surgery (ultra-early) would be more effective in decreasing CPB-related inflammatory response than when given at induction of anesthesia (early) or in pump prime (standard). This was a triple-arm, parallel, active control, superiority RCT including 54 infants <2 years old who were randomised to receive 30 mg/kg methylprednisolone at one of the 3 time points. Outcomes included alveolar-arterial oxygen gradient (AaDO2) during, 24, 48 and 72 hours post-CPB, IL-6, IL-8 and reduced (GSH) to oxidized (GSSG) glutathione ratio (pre-ultrafiltration on CPB, end-CPB and 24 hours), PICU length of stay (LOS) and ventilator days. Data were analysed using descriptive statistics and a random effects regression model. The ultra-early group had higher Risk Adjusted Congenital Heart Surgery Score, lower age and longer CPB times than the other groups. No significant differences in AaDO2, IL-8, PICU LOS and ventilator days were observed between groups. Compared to the ultra-early group, the overall rise in IL-6 in the early and standard groups was lower, -27.8 pg/ml (95% CI -52.7,-2.9) and -35.3 pg/ml (95% CI -64.3,-6.34), respectively. GSH:GSSG was significantly lower in the standard group (-35.9; 95% CI -63.31,-8.5) at 24 hours post-CPB. Ultra-early administration of methylprednisolone does not improve AaDO2 post-CPB, nor diminish cytokine release. Lower GSH:GSSG in the standard group suggests less oxidative stress. However despite statistical adjustments conclusions are limited by the unbalanced randomisation of the groups.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".