Jugular Bulb Oximetry for Prediction of Vasospasm Following Subarachnoid Hemorrhage
Bibliographic record
Abstract
BACKGROUND: Cerebral vasospasm adversely impacts the outcome of those suffering aneurysmal subarachnoid hemorrhage (SAH). Prediction of vasospasm could improve outcomes. We hypothesized that preclinical vasospasm would be heralded by an increase in cerebral oxygen extractions (AVDO2) which could be detected by jugular bulb oximetry. A pilot study was conducted to address this hypothesis. METHODS: Fourteen consenting patients with aneurysmal SAH, undergoing early surgery, were entered into the study. Four patients were withdrawn from the study secondary to failure of catheters or religious belief. At the time of craniotomy, a jugular bulb catheter was placed. Post-operatively, arterial and jugular bulb blood samples were taken every 12 hours to calculate AVDO2. As this was an observational study, no change in management occurred based on measurements. RESULTS: Four of 10 patients had clinical vasospasm. These patients had a significant rise in AVDO2 approximately one day prior to the onset of neurologic deficits (P<0.001). Symptoms resolved along with a significant improvement in AVDO2 on instituting hypertensive, hemo-dilutional, and hypervolemic therapy in these patients. The six patients who did not exhibit clinical vasospasm did not demonstrate significant rise in AVDO2. CONCLUSIONS: Jugular bulb oximetry is simple and cost effective. Increases in AVDO2 using this technique were predictive of clinically evident vasospasm in the subsequent hours to days. This investigation supports a larger study to assess the utility of jugular bulb oximetry in predicting vasospasm in aneurysmal SAH.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".