Impact of Ketamine and Propofol on Cognitive Function in Elderly Patients: A Systematic Review
Bibliographic record
Abstract
Anesthesia has been thought to impact cognitive function in the elderly, although the exact pathophysiology remains uncertain. This systematic review aimed to analyze the impact of ketamine and propofol on cognitive function in elderly patients. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a comprehensive search was conducted across PubMed/Medline, Cochrane Central Register of Controlled Trials (CENTRAL), Europe PMC, ScienceDirect, ClinicalTrials.gov, and EBSCO Open Dissertations on November 17, 2024. After screening, the methodological quality of the included studies was assessed using the Cochrane Risk-of-Bias-2 Tool and the Newcastle Ottawa Scale. Studies were included if they focused on patients aged 60 and older, encompassing 3,149 participants across 19 studies, predominantly randomized controlled trials. Key outcomes assessed included postoperative cognitive dysfunction (POCD) and postoperative delirium (POD). Results indicated that many studies found no significant differences in cognitive outcomes between certain anesthetic drugs. However, ketamine was likely associated with an increased risk of POCD, similar to propofol, when compared to remimazolam and dexmedetomidine. Notably, ketofol reduced POD incidence compared to placebo, while higher propofol doses were linked to an increased incidence, and severity of hypoactive POD. The most evident finding was that propofol attenuated POCD compared to inhaled anesthetic agents. Given this, it is crucial for clinicians to carefully consider anesthetic choices for elderly patients. Future research should focus on larger multicenter trials to further validate these results and explore the long-term cognitive effects of various anesthetic agents.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.011 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".