Applied Neuromonitoring in Cardiac Surgery: Patient Specific Management
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it