Success analysis of virtual reality-based cognitive training in patients after coronary artery bypass grafting
Bibliographic record
Abstract
Aim . To analyze the success of virtual reality-based multitask cognitive training (VR-MCT) in patients who underwent on-pump coronary artery bypass grafting (CABG), based on an assessment of neuropsychological and neurochemical parameters. Material and methods . This prospective study included 49 male patients aged 45 to 75 years who underwent on-pump CABG and had early postoperative cognitive dysfunction (POCD). Beginning 3-4 days after CABG, patients underwent daily VR-MCT (mean session count — 6,7). In addition to the standard perioperative examination, all patients underwent psychometric testing and determination of neurovascular unit (NVU) markers — neuron-specific enolase (NSE), S100β protein, and brain-derived neurotrophic factor (BDNF). Results . The success rate of VR-MCT course was 43%; 21 of 49 patients did not show POCD according to the established criteria at 11-12 days after CABG. Patients with successful VR-MCT showed improvements in attention (p=0,034) and short-term memory (p=0,016) compared with patients with unsuccessful training in the early postoperative period. In patients with successful VR-MCT, peripheral blood BDNF levels before surgery (p=0,029) and 1-2 days after CABG (p=0,04) were significantly higher compared to patients with unsuccessful training. We established factors specifying the complex indicator of the neurodynamics domain in VR-MCT — educational level, intima-media thickness, patient age, number of trainings and S100β protein level on day 1 after surgery (R 2 =0,38, F (5,43)=8,32, p<0,001); the attention domain — patient age, educational level, initial BDNF concentrations, both at the first day and on the first day. Peripheral blood S100β protein concentration and Montreal Cognitive Assessment (MoCA) scores were assessed (R 2 =0,52, F (6,42)=10,76, p<0,001); for the short-term memory domain, the patient's age and baseline BDNF, NSE, and glucose concentrations were assessed (R 2 =0,37, F (4,45)=10,15, p<0,001). Conclusion . The study results demonstrated that VR-MCT optimizes attention and short-term memory performance in patients with early POCD after on-pump CABG. Negative factors specifying cognitive status after VR-MCT include patient age, low education level, and baseline cognitive function, while protective factors include high perioperative BDNF concentrations and low peripheral blood concentrations of brain damage markers.
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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) | 0.001 | 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".