Effects of inhalation and propofol anaesthesia on postoperative cognitive dysfunction in elderly noncardiac surgical patients
Bibliographic record
Abstract
BACKGROUND: Postoperative cognitive dysfunction (POCD) is a very common event in elderly noncardiac surgical patients. The effects of inhalational anaesthetics and propofol on the incidence of POCD and postoperative cognitive status at different time points after surgery are currently unclear. METHODS: We searched the Embase, Medline, Cochrane Library, and Web of Science databases for randomized controlled trials (RCTs), in which inhalation anaesthesia and propofol anaesthesia were compared. The incidence of POCD or postoperative cognitive status was assessed in elderly patients undergoing noncardiac surgery. RESULTS: Fifteen RCTs with 1854 patients were included in this meta-analysis. The incidence of POCD on postoperative Days 2-6 after propofol anaesthesia was markedly lower than that after inhalation anaesthesia (risk ratio (RR): 0.37, 95% confidence interval (CI): 0.15-0.88, P = .025), and Mini-Mental State Examination (MMSE) scores after propofol anaesthesia were substantially higher than those after inhalation anaesthesia (standard mean difference (SMD): 0.59, 95% CI: 0.07-1.11, P = .026). The levels of interleukin-6 (IL-6) and tumour necrosis factor-α (TNF-α) were much lower after propofol anaesthesia than after inhalation anaesthesia (SMD: -2.027, 95% CI: -3.748- -0.307, P = .021; SMD: -0.68, 95% CI: -0.93- -0.43, P < .001). CONCLUSIONS: The moderate evidence from this meta-analysis shows that, in elderly noncardiac surgical patients, propofol anaesthesia is superior to inhalation anaesthesia for attenuating of early POCD incidence, and low-level evidence shows that cognitive status is higher and systemic inflammation is less severe after propofol anaesthesia in the early days after surgery. LIMITATIONS: The sample size was not sufficiently large for systemic inflammation, and the tools to identify POCD were not uniform in the included studies.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.013 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".