Abstract 137: Noninvasive Fractional Flow on MRA and Recurrent Stroke: SPS3 Trial
Bibliographic record
Abstract
Background and Purpose: Noninvasive fractional flow reserve (FFR) on time-of-flight magnetic resonance angiography (TOF-MRA) may be used to identify high-risk intracranial lesions. We tested whether FFR was associated with vascular territory of the qualifying lacunar stroke in participants of the Secondary Prevention of Small Subcortical Strokes (SPS3) trial and the utility of FFR for predicting recurrent stroke during the trial. Methods: SPS3 was a randomized trial investigating optimal blood pressure target and antiplatelet regimen in patients with recent, symptomatic, MRI-confirmed lacunar stroke patients TOF-MRA proximate to study entry was adequate and available for 2169 of 3020 study patients. Signal intensity (SI) was measured in the background, and proximal and distal aspects of 7 intracranial arteries (internal carotid, middle cerebral, basilar, and vertebral). Adjusted FFR was then calculated in each artery: FFR = [distal SI - background SI] / [proximal SI - background SI] and divided into quartiles by artery. Associations between the vascular territory of the qualifying infarct and the FFR quartile of the relevant artery were investigated using contingency tables and chi-square tests. Risks for recurrent stroke associated with FFR quartiles were evaluated using Cox Proportional Hazards models (model adjusted for assigned treatment groups). Results: Mean age of the 2169 patients included was 63 yr with 63% male; hypertension, diabetes, and prior lacunar stroke were present in 75%, 36%, and 10% respectively. Median FFRs varied by artery with the lowest in the basilar (0.793) and highest in the middle cerebral arteries (left 1.154; right 1.176). A recurrent stroke occurred in 195 patients during a mean follow-up of 3.5 years (annualized rate 2.5% per patient-year).No significant association was found between the FFR tertiles and the vascular territory of the qualifying infarct. Quartiles of adjusted FFR in any of the 7 arteries were not found to be predictive of recurrent stroke. Conclusion: In this large well-characterized cohort of lacunar stroke patients, FFR was not associated with the location of the qualifying subcortical infarct and did not predict the risk of recurrent 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) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".