Combined Stump Pressure and Oximetry for Shunt Use During Carotid Endarterectomy
Bibliographic record
Abstract
BACKGROUND: Cross-clamp ischemia during carotid endarterectomy can be prevented with carotid bypass shunts in vulnerable patients identified by cerebral monitoring for ischemia. We compared transcranial cerebral oximetry (TCO) with carotid stump pressure measurements for selective shunt use. METHODS: We prospectively collected data on 300 consecutive patients operated on under general anesthesia between 2009 and 2016. Shunts were inserted for a 10% or greater drop in cerebral saturations and/or a mean stump pressure less than 40 mmHg. RESULTS: Seventy-five patients, 25% of the study population, were shunted. The indication was a combined desaturation and stump pressure in 38 (50% of the shunted group), desaturation alone in 11 patients (15%), and a low stump pressure alone in 26 patients (35%). There were no significant differences in baseline characteristics between those patients who were or were not shunted, except angiographic collateral blood supply, which was more commonly identified in patients who were not shunted. A watershed infarct occurred in just one patient with borderline TCO and stump pressure measurements in whom a shunt was not used. CONCLUSIONS: There was poor concordance between TCO and stump pressures, but using both in determining the need for shunt use almost eliminated cross-clamp ischemia in this series of 300 carotid endarterectomy patients.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".