Cognitive disorders in patients after cardiac surgery
Bibliographic record
Abstract
The occurrence of cognitive disorders is a common problem after surgery. The degree of worsening of cognitive functions after surgery and anesthesia has a significant impact on the patient's health and is significantly associated with prolonged recovery in the hospital, increased morbidity and delayed functional recovery. The aim of the study was to increase the effectiveness of the diagnosis of moderate cognitive impairment and to determine its gender and age characteristics in patients before and after cardiac surgery in the early postoperative period (3 and 7 days). We examined 56 patients who underwent cardiac surgery for coronary heart disease in 37 (66.1 %) and valvular heart defects in 19 (33.9 %) patients. Assessment of cognitive functions was performed before surgery, on the 3rd and 7th day of the postoperative period. Testing was performed using the Montreal Cognitive Test. Statistical processing of the obtained data was performed on a personal computer using the statistical software package SPSS 12.0 for Windows using parametric and non-parametric methods. It was found that presence of cognitive disorders before surgery was registered in 37 (66.1 %) patients, mostly among the age of group of 60-74 years and had no gender difference. It was found that in the early postoperative period there is a significant worsening of cognitive functions in patients after cardiac surgery on 3rd day – in 45 (80.4 %), on 7th day – in 44 (78.6 %) patients, respectively.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".