Sevoflurane versus propofol on immediate postoperative cognitive dysfunction in patients undergoing cardiac surgery under cardiopulmonary bypass: a comparative analysis
Bibliographic record
Abstract
OBJECTIVE: This study aims to compare the effects of sevoflurane (SEV) and propofol (PRO) on postoperative cognitive dysfunction (POCD) in patients undergoing cardiac surgery (CS) under cardiopulmonary bypass (CPB), with a focus on evaluating the efficacy of these anesthetic agents in preventing POCD. METHODS: A total of 113 patients undergoing CS with CPB were grouped into two: PRO group (n = 58) and SEV group (n = 55). Baseline data, anesthesia effects (CPB duration, anesthesia time, respiratory recovery time, and anesthesia recovery time), Montreal Cognitive Assessment (MoCA) scores, POCD incidence, neurological function markers (NSE, S-100β, MMP9), and serum inflammatory markers (IL-6, IL-8, TNF-α) were analyzed. The study was conducted between March 2018 and May 2021. RESULTS: The PRO group showed significantly shorter anesthesia time (P < 0.05), respiratory recovery time (P < 0.05), and anesthesia recovery time (P < 0.05) compared to the SEV group. The postoperative MoCA score in the PRO group reduced markedly compared with the baseline, but still higher than that in the SEV group (P < 0.05). The incidence of POCD was significantly lower in the PRO group (5.17% vs. 27.27%, P = 0.001). The levels of NSE, S-100β, MMP9, IL-6, IL-8, and TNF-α were significantly elevated compared to baseline values, but still lower than those in the SEV group (P < 0.05 for all comparisons). CONCLUSION: PRO is more effective than SEV in preventing POCD in patients undergoing CS with CPB. It provides superior anesthetic effects and offers better protection against neuronal damage and serum inflammation compared to SEV. CLINICAL TRIAL NUMBER: Not applicable.
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How this classification was reachedexpand
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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".