Perioperative Cognitive Dysfunction: Comparative Evaluation of Anesthetic Agents and Neurocognitive Outcomes in Elderly Patients: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: The occurrence of perioperative cognitive dysfunction (POCD) affects many elderly surgical patients in their postoperative period, notwithstanding worries about enduring issues caused by distinct anesthetic methods. This systematic review and meta-analysis aimed to assess the effects of the various types of anesthesia agents and procedures on postoperative cognitive dysfunction among adult surgical patients. Methods: This systematic review and meta-analysis follow PRISMA 2020 guidelines. The following randomized and observational studies assessing postoperative cognitive outcomes were searched in PubMed, Scopus, Web of Science, and Google Scholar up to May 2025. To determine risk of bias, the Cochrane Risk of Bias Tool on RCTs and the Newcastle-Ottawa Scale (NOS) on observational studies were used. The degree of confidence of the included outcomes was measured with the GRADE framework. The meta-analysis was conducted using RevMan 5.4.1, and heterogeneity (I2) was also assessed. Results: Ten studies, including 1,170 participants, have been analyzed, and the majority of comparisons made are the effect of anesthetic agents on postoperative cognitive dysfunction (POCD). Other agents, such as remimazolam, scopolamine, and S-ketamine, produced better cognitive results as compared to others that did not produce significant results. Cognitive scores were found not to be statistically different between treatments (SMD: -0.57, 95% CI: -1.51 to 0.36) and had a high heterogeneity (I2 = 94%). Discussion: Some of these anesthetic agents, like remimazolam, S-ketamine, and scopolamine, have promising results in the prevention of early postoperative cognitive dysfunction, but the overall evidence is at the same time inconsistent. Meta-analysis failed to execute expressions of meaningful cognitive effects throughout habitations, stressing the importance of standard cognitive evaluations and future high-quality tests. There is a tendency towards high levels of heterogeneity and variability in cognitive outcome measures, and hence, the limited generalizability.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".