Cognitive impairment after major surgical operations
Bibliographic record
Abstract
Objective. To study the characteristics of cognitive impairment after extensive surgical operations of various profiles, to develop tactics of cerebroprotection, as well as personalized prevention of cognitive impairment (CI). Material and methods. The study included 277 patients who underwent elective extensive cardiac surgery (coronary bypass surgery, prosthetics of the aortic heart valve) and oncological (for malignant neoplasms of the thoracic or abdominal cavities) profile. All patients underwent a comprehensive clinical, laboratory, and instrumental examination (including neuropsychological testing using the MoCA, FAB scales) in the preoperative and intraoperative periods, as well as 10 days after surgery. Results. Deferred CI after cardiac surgery was diagnosed in 30—36% of patients, and after oncological surgery in 31% of patients. The incidence of acute clinical types of postoperative cerebral dysfunction also had no statistically significant differences: perioperative stroke (2—4% and 2%), symptomatic delirium of the early postoperative period (14—17% and 11%, respectively). Postoperative brain dysfunction was diagnosed after 44% of cardiac surgeries and 34% of oncosurgical operations. Risk factors for deferred CI after coronary bypass surgery: age over 65 years; stenotic atherosclerosis of the brachiocephalic arteries. During aortic valve replacement, the risk factors for deferred CI are: total cholesterol >5.1 mmol/L; very low-density lipoproteins >1.2 mmol/L; low-density lipoproteins >3.2 mmol/L; platelet count<220×109/L; hematocrit<28%. In oncosurgery, the risk factors for delayed CI are: age >70 years, lack of work in the specialty; Charlson’s index comorbidity score >5 points; ASA physical status >Class III; MoCA test scores<20 points. Conclusion. Most of the risk factors for deferred cognitive impairment are preoperative, which allows ahead additional assessment of the possibility of modifying the surgical technique and accompanying therapy, as well as designing of personalized tactics of cerebroprotection and prevention of cognitive impairment.
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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 | 0.001 | 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".