THE EFFECT OF ANESTHESIA ON COGNITIVE FUNCTIONS
Bibliographic record
Abstract
Aim of the study - General anesthetics, arterial hypotension and hypoxia developing during anesthesia may result in impaired memory and a decline in other abilities (such as attention, concentration, linguistic and writing abilities). Our aim was to detect changes in cognitive functions due to surgery and anesthesia with controlled arterial hypotension. Materials and methods - We studied combined and intravenous anesthesia detecting pre-and postoperative cognitive functions, intraoperative haemodynamic parameters, demographic data, other data of case history and surgical data. The Montreal Cognitive Assessment test was applied in the randomized, prospective study. The preoperative data served as basis for comparison. The second test was performed following surgery when patients were fully awake. Both groups included 30 patients. Results and conclusion - After both narcosis methods (postoperative second hour) cognitive functions were significantly deteriorated (p<0.05). Median MoCA before sevoflurane anesthesia was 24 points (interquartile range: 22-25), postoperative value was 20 (19-21) (p<0.05). Median MoCA before propofol anesthesia was 24 points (23-26), postoperative value was 20 (18-22) (p<0.01). Intraoperative arterial blood pressure, pulse rate and oxygen saturation values did not correlate with worsening of cognitive function (Pearson correlation coefficient values between -0.19 and 0.42). Execution is influenced by age (negative correlation) and education (positive correlation).
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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 | 0.000 | 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) | 0.002 | 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".