Brain Stress Test for Assessing Risk for Hemodynamic Stroke
Bibliographic record
Abstract
ABSTRACT: Background: In patients with intracranial steno-occlusive disease (SOD), the risk of hemodynamic stroke depends on the poststenotic vasodilatory reserve. Cerebrovascular reactivity (CVR) is a test for vasodilatory reserve. We tested for vasodilatory reserve by using PETCO2 as the stressor, and Blood Oxygen Level Dependent (BOLD) MRI as a surrogate of blood flow. We correlate the CVR to the incidence of stroke after a 1-year follow-up in patients with symptomatic intracranial SOD. Methods: In this retrospective study, 100 consecutive patients with symptomatic intracranial SOD that had undergone CVR testing were identified. CVR was measured as % BOLD MR signal intensity/mmHg PETCO2. All patients with normal CVR were treated with optimal medical therapy; those with abnormal CVR were offered revascularization where feasible. We determined the incidence of stroke at 1 year. Results: 83 patients were included in the study. CVR was normal in 14 patients and impaired in 69 patients ipsilateral to the lesion. Of these, 53 underwent surgical revascularization. CVR and symptoms improved in 86% of the latter. The overall incidence of stroke was 4.8 % (4/83). All strokes occurred in patients with impaired CVR (4/69; 2/53 in the surgical group, all in the nonrevascularized hemisphere), and none in patients with normal CVR (0/14). Conclusion: Our study confirms that CO2-BOLD MRI CVR can be used as a brain stress test for the assessment of cerebrovascular reserve. Impaired CVR is associated with a higher incidence of stroke and normal CVR despite significant stenosis is associated with a low risk for stroke.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.002 | 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".