Use of a Neurometabolism-Targeting Drug in Prevention of Postoperative Cognitive Dysfunction
Bibliographic record
Abstract
Aim of the study: to evaluate the feasibility of preventing cognitive dysfunction after long-term surgery in elderly patients using an original neurometabolic succinate-containing drug. Material and methods. A multicenter, double-blind, placebo-controlled randomized trial enrolled 200 patients aged 60–80 years who underwent elective cardiac or orthopedic surgery. The patients received either the study drug (inosine + nicotinamide + riboflavin + succinate) (treatment group, n = 101) or a placebo (control group, n = 99) intravenously for 7 days then orally for 25 days. Efficacy was assessed by the change in the Montreal Cognitive Assessment Scale (MoCA) score at the end of the treatment course compared with the preoperative level. Results. Before surgery, the total MoCA score values did not differ between the groups. By the end of the treatment course (31 days after surgery), the MoCA total score was 26.4 ± 1.96 in the main group and 25.0 ± 2.83in the control group (P < 0.001). The intergroup difference in the mean change in the MoCA total score on day 31 was 1.56 points (95 % CI 1.015; 2.113; P < 0.0001) favoring the study drug in all randomized population. The lower limit of CI (1.015) exceeded the limit of superiority set by the protocol (0.97 points), which allowed acceptance of the hypothesis of superiority of the study drug over placebo with respect to the primary efficacy criterion. No significant differences in the frequency of adverse events were found between the groups. Conclusion. The succinate-containing study drug demonstrated an acceptable safety profile and helped to reduce the severity of postoperative cognitive dysfunction in elderly patients who underwent a major surgery, which allows recommending the drug for prevention of postoperative cognitive impairment in high-risk patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".