P.020 Transcranial doppler for risk assessment of subarachnoid hemorrhage
Bibliographic record
Abstract
Background: Vasospasm is an important complication of subarachnoid hemorrhage (SAH). Attempts to identify patients at highest risk of vasospasm have not led to practice change. We sought to identify patients at lowest risk of vasospasm by testing the prognostic utility of novel low risk criteria: mean MCA velocities on TCD that peaked and remained below 120 cm/s by the 7th day. Methods: Retrospective observational study of TCD values in patients admitted to The Ottawa Hospital with SAH 2018-2023. The primary outcome was presence of moderate to severe vasospasm (MCA mean velocity >160 cm/s) by day 21. Results: Data were collected on 211 patients, of whom 197 fulfilled inclusion criteria. Only 2 of 104 patients (2%) meeting our low-risk criteria developed the primary outcome, compared to 48 of 93 patients (52%) who did not meet criteria (RR 27). The Negative Predictive Value (NPV) for vasospasm in our low-risk group was 98%. Conclusions: Our low-risk criteria based on TCD patterns in the first 7 days after SAH can identify patients at very low risk of vasospasm with great accuracy. This could inform a future prospective study.
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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 | 0.005 |
| 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) | 0.005 | 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".