Impact of Methylprednisolone on Postoperative Quality of Recovery and Delirium in the Steroids in Cardiac Surgery Trial
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Bibliographic record
Abstract
BACKGROUND: Inflammation after cardiopulmonary bypass may contribute to postoperative delirium and cognitive dysfunction. The authors evaluated the effect of high-dose methylprednisolone to suppress inflammation on the incidence of delirium and postoperative quality of recovery after cardiac surgery. METHODS: Five hundred fifty-five adults from three hospitals enrolled in the randomized, double-blind Steroids in Cardiac Surgery trial were randomly allocated to placebo or 250 mg methylprednisolone at induction and 250 mg methylprednisolone before cardiopulmonary bypass. Each completed the Postoperative Quality of Recovery Scale before surgery and on days 1, 2, and 3 and 1 and 6 months after surgery and the Confusion Assessment Method scale for delirium on days 1, 2, and 3. Recovery was defined as returning to preoperative values or improvement at each time point. RESULTS: Four hundred eighty-two participants for recovery and 498 participants for delirium were available for analysis. The quality of recovery improved over time but without differences between groups in the primary endpoint of overall recovery (odds ratio range over individual time points for methylprednisolone, 0.39 to 1.45; 95% CI, 0.08-2.04 to 0.40-5.27; P = 0.943) or individual recovery domains (all P > 0.05). The incidence of delirium was 10% (control) versus 8% (methylprednisolone; P = 0.357), with no differences in delirium subdomains (all P > 0.05). In participants with normal (51%) and low baseline cognition (49%), there were no significant differences favoring methylprednisolone in any domain (all P > 0.05). Recovery was worse in patients with postoperative delirium in the cognitive (P = 0.004) and physiologic (P < 0.001) domains. CONCLUSIONS: High-dose intraoperative methylprednisolone neither reduces delirium nor improves the quality of recovery in high-risk cardiac surgical patients.
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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 | 0.001 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 it