Cerebral oximetry and thoracic surgery
Bibliographic record
Abstract
PURPOSE OF REVIEW: Cerebral oximetry, though first described for clinical use in cardiac surgery, has been increasingly used in the setting of thoracic surgery. Research focusing on the use of cerebral oximetry in this setting is relatively sparse. This review outlines our current understanding of the use of cerebral oximetry for thoracic surgery. RECENT FINDINGS: Cerebral desaturation, though variably defined, is a relatively common occurrence during thoracic surgery. The reasons for this desaturation largely relate to perioperative hypoxemia, but may also be related to other physiologic disturbances such as lateral decubitus positioning, one-lung ventilation, as well as other nonhypoxemia-related mechanisms. It is unlikely to result from specific reductions in cardiac output. There is some preliminary data suggesting a relationship between cerebral desaturation and various adverse postoperative outcomes. SUMMARY: Although it is clear that cerebral desaturation can commonly occur during thoracic surgery, it is partly dependent upon how desaturation is defined. The relationship between cerebral desaturation and adverse outcomes after thoracic surgery, as well as the potential ability for cerebral oximetry to guide therapeutic modalities, awaits much needed additional research before being more widely accepted.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".