Comparative evaluation of intraoperative dexmedetomidine versus lidocaine for reducing postoperative cognitive decline in the elderly: a prospective randomized controlled trial
Bibliographic record
Abstract
INTRODUCTION: Neuroinflammation, neuronal cytotoxicity, and apoptosis due to exposure to anaesthetic agents are often implicated in postoperative cognitive dysfunction (POCD). Lidocaine and dexmedetomidine have been shown to suppress the neuron-specific markers of inflammation, and we aimed to compare their neuroprotective efficacy in elderly patients. MATERIAL AND METHODS: This prospective randomized control study compared the incidence of POCD in ASA I/II patients aged 60 to 80 years without any history of substance abuse or any disorder affecting cognition. Dexmedetomidine and lidocaine were administered intraoperatively, and their effects on POCD were correlated with serum levels of IL-1, IL-6, TNF-a, amyloid-β, and S100 on postoperative day 3. POCD was assessed by the Stroop test, Trail making test-B, Porteus Maze test, Mini-Mental State Examination (MMSE), and Montreal Cognitive Assessment (MoCA) on the day before surgery and the third postoperative day, along with blood samples. RESULTS: Demographic parameters, anaesthesia duration, exposure to anaesthetic gases, intraoperative opioid use, and blood transfusion were similar in the lidocaine ( n = 31) and dexmedetomidine ( n = 29) groups. The incidence of POCD was 29.03% in the lidocaine group and 24.1% in the dexmedetomidine group ( P = 0.77). On postoperative day 3, IL-1 levels increased by 449% with lidocaine and 202% with dexmedetomidine ( P = 0.03). TNF-a, IL-6, and S-100β levels increased similarly in both groups. There was no significant correlation between percentage changes in neuropsychological tests and biomarkers. CONCLUSIONS: There was no significant difference in the incidence of POCD, but dexmedetomidine had a better anti-inflammatory effect in terms of lesser rise of postoperative IL-1 compared to lidocaine.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".