Applied Neuromonitoring in Cardiac Surgery: Patient Specific Management
Bibliographic record
Abstract
Various studies have demonstrated that over 50% of patients presenting for coronary revascularization surgery have evidence of extracranial or intracranial atherosclerotic disease. Although evidence is compelling that cerebral emboli are a major cause of perioperative central nervous system (CNS) morbidity in such patients, it is also apparent that alterations in cerebral perfusion pressure and blood flow can profoundly influence the extent of injury after an embolic insult. In this context, the recent studies demonstrating improved CNS outcomes with applied neuromonitoring in cardiac surgical patients can be understood as reflecting the optimization of CNS perfusion characteristics with potential amelioration of microembolic injury. This review critically evaluates and discusses the relevant characteristics of applied neuromonitoring techniques, including bispectral index (BIS), transcranial Doppler (TCD), and near infrared reflectance spectroscopy (NIRS) in the context of patients undergoing cardiac surgical procedures. Recent outcomes data regarding CNS and related morbidity and the influence of neuromonitoring in these groups are evaluated.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".