Derivation of Transcranial Doppler Criteria for Angiographically Proven Middle Cerebral Artery Vasospasm after Aneurysmal Subarachnoid Hemorrhage
Bibliographic record
Abstract
BACKGROUND: Transcranial Doppler (TCD) has been subjected to criticism for detecting vasospasm (VSP). Our study's aim is to derive criteria for middle cerebral artery (MCA) vasospasm (MCA-VSP) based on cerebral angiography (CA). METHODS: A prospective data of patients with aneurysmal subarachnoid hemorrhage (aSAH) from January 2004 to August 2009. TCD was performed daily from day 2 to 14 from symptom's onset. Follow-up CA was done at day 7-9. TCD mean flow velocities (MFV) of all vessels at baseline (b), middle (m) and before CA (preangio) were recorded. Several MCA MFV ratios were computed. Moderate to severe VSP on CA was defined as >1/3 luminal narrowing. Univariate and stepwise logistic regression analysis were performed. RESULTS: One hundred sixty-nine patients (338 MCA) with aSAH were included, mean age: 54.8 ± 13, women: 103 (62%). Twenty-nine patients (8.6%) had angiographic MCA-VSP. TCD scoring system of 3 points for MCA-VSP was computed based on (a) bMCA MFV ≥ 120 cm/s (sensitivity: 59.3%, specificity: 85%, PPV: 36.4%, NPV: 93.5%, P < .001) (1 point), Preangio MCA MFV ≥ 150 cm/s (79.3%, 89.9%, 39%, 97.3%, <.001) (1 point), and affected preangio MCA/bMCA MFV ratio ≥ 1.5 (84%, 63%, 25.6%, 96.3%, .001) (1 point). The score of 3 has 96% sensitivity and 96% specificity (OR: 300) whereas the score of 1 has 12% sensitivity and 58% specificity (OR: 4.3) for identifying MCA-VSP. CONCLUSION: TCD stringent criteria for moderate to severe MCA-VSP are feasible and applicable in aSAH population.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".