Postoperative cognitive dysfunction: etiology, clinical features, diagnosis
Bibliographic record
Abstract
Introduction. The present study analyzed the possibility of using neuropsychological tests to assess postoperative cognitive dysfunction. New data were obtained: in the postoperative period, hippocampal memory impairments predominate in patients, which makes it expedient to use methods for diagnosing primary modal-nonspecific memory disorders in patients who are to undergo neurosurgical intervention on the spinal cord. The aim of the study to evaluate the influence of surgery with anesthesia on the cognitive functions of middle-age patients. Materials and methods. The study included 20 middle-aged patients. All patients had to undergo spinal surgery. Patients received total intravenous anesthesia with propofol induction (4–12 mg/kg/hr). Cognitive functions before and after the operation were made with the use of the MoCA, TMT A and B, FCSRT, state-trait anxiety inventory test (STAI). Results. The development of POCD was noted in 15% of cases. The patients showed a decrease in the FCSRT prompt index (1st day = 87 ± 9.0; 2nd day = 83 ± 15; p = 0,0005), while the overall severity of cognitive impairments (total score of MoCA) did not change significantly (standard deviation according to MoCA: 24.25 ± 2.86 on day 1 and 24 ± 3.24 on the second day, p = 0.61). The RT level decreased by day 2: 44.65 ± 7.4 versus 41.1 ± 8.2 (p = 0.001). Correlation analysis did not show the relationship between the age of patients, education level, comorbidity and development of POCD; however, the duration of anesthesia was associated with a decrease in MoCA scores (Pearson’s correlation coefficient r = –0.44; p = 0.050). Conclusion. Thus, our study shows that the study of hippocampal memory impairments is important in patients with POCD. These data differ from the data of researchers presented earlier, where the most important clinical manifestations of POCD are considered to be a decrease in attention and speed of mental processes. Of course, the small sample size dictates the need for additional research.
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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) | 0.002 | 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".