Intraoperative dexmedetomidine infusion might help to preserve the cognitive function of geriatric patients undergoing arthroscopic shoulder surgery
Bibliographic record
Abstract
Objectives: This study tried to evaluate the impact of dexmedetomidine (DXM) infusion provided during sevoflurane (SEV) anesthesia on cognitive function (CF) of elderly patients undergoing elective arthroscopic shoulder surgeries. Patients & Methods:A total of 140 patients were randomly allocated into Groups S and D. All patients received SEV (0.5-1 MAC) with placebo or DXM (0.6 µg/kg/h) infusions, respectively.CF was evaluated preoperatively, 48-h, 1-wk, and 2-wk postoperative (PO) using the Montreal Cognitive Assessment Test and Mini-Mental State Examination (MMSE).The study outcome is the frequency and severity of PO cognitive dysfunction (POCD).Results: At 48-h PO, the frequency of normal CF and scorings were significantly decreased compared to preoperative findings, but were significantly higher in group D. At 1-wk PO, the frequency of normal CF and scores increased in both groups with significant difference in favor of group D, but differences were significantly lower than in preoperative measures.At 2-wk PO, 79.3% of patients regained their normal CF, with significantly higher frequency and score for group D, and the difference compared to preoperative data was insignificant in group D, but it was significant in group S. At 48-h, scorings were positively related to using DXM but were negatively related to age, obesity, and PO analgesia.Regression analysis defined old age as negative and the use of DXM as positive predictor for high scores.Conclusion: SEV anesthesia induced reversible short-term POCD.Coupling of DXM infusion with SEV anesthesia decreased the frequency and scores of POCF and fastened resumption of normal CF.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".