Neurological Complications after Coronary Artery Bypass Grafting for High-Risk Patients: Current State of the Problem
Bibliographic record
Abstract
Neurological disorders are the most serious and debilitating complications of the postoperative period in cardiac surgery. The main clinical manifestations of cerebral dysfunction are as follows: stroke, decreased cognitive function, encephalopathy and depressive disorder. The aim. To perform a literature review of neurological complications after coronary artery bypass grafting (CABG) in high-risk patients. Results. The main neurological complications after CABG in high-risk patients were considered. The main pathophysiological mechanisms of development of cerebral circulation disorders in the form of macro- and microembolization, hypoperfusion secondary to hypotension and systemic inflammatory response have been determined. According to the literature, the incidence of stroke in the postoperative period is 1.5–6%, and it increases in the elderly. It’s important to perform carotid arteries ultrasound before CABG. According to the literature, carotid stenosis greater than 60% is found, depending on the age group, in 7–12% of patients. There is an ongoing debate around the world regarding the method and time of carotid atherosclerosis surgery (before revascularization, during or after CABG). Newman and co-authors have shown that in 5 years after myocardial revascularization, 41% of patients have a decrease in cognitive function, and it is lower than it was before surgery. Opponents of on-pump CABG have hypothesized the occurrence of Alzheimer’s disease after surgery with extracorporeal circulation, but authors from Mayo Clinic have investigated this question and refuted this theory; Canadian researchers have even proved the positive effect of revascularization on prevention of Alzheimer’s disease. The main strate gy for the prevention of cerebral complications is an individual approach for each high-risk patient.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".