Comparison of the Effects of Sevoflurane and Isoflurane on Postoperative Cognitive Dysfunction Following Laparoscopic Cholecystectomy: A Prospective Study
Bibliographic record
Abstract
Background Laparoscopic surgeries, including cholecystectomy, are typically conducted with intravenous induction using anaesthetics such as propofol. This study used sevoflurane and isoflurane as alternatives to propofol to minimise adverse events and compare their effectiveness. Materials and methods The research was a prospective randomised study conducted at the Department of Anaesthesiology, Rajendra Institute of Medical Sciences (RIMS), Ranchi, Jharkhand, India, for one and a half years. A total of 90 patients participated in the study, evenly split into two groups (sevoflurane and isoflurane) in a 1:1 ratio. Ethical clearance was obtained from the Institutional Ethics Committee (IEC), RIMS, Ranchi, Jharkhand, India, under letter number 131/IEC/RIMS, dated 27 June 2023. Results In terms of the American Society of Anesthesiologists (ASA) classification, more participants were categorised as grade II in the sevoflurane and isoflurane groups. Montreal Cognitive Assessment (MoCA) scores were evaluated at various time intervals. There was no significant difference between the sevoflurane and isoflurane groups after six hours of anaesthesia. Total MOCA scores were found to be significant at a p-value of 0.04 after 24 hours of anaesthesia between the sevoflurane and isoflurane groups. Conclusion The study concluded that the incidence of the MoCA score decreased in the isoflurane and sevoflurane groups at one hour and six hours postoperatively. Adverse events, such as nausea, vomiting, and shivering, also decreased over time.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".