Impact of Methylprednisolone on Postoperative Quality of Recovery and Delirium in the Steroids in Cardiac Surgery Trial
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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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".