Associations between fluid-attenuated inversion recovery vessel hyperintensities and Alberta stroke program early CT score and clinical outcomes in stroke patients with unknown time of onset: A sub-analysis from a randomized controlled trial
Bibliographic record
Abstract
BACKGROUND AND AIMS: FLAIR vessel hyperintensities (FVH)-Alberta Stroke Program Early CT Score (ASPECTS) is an imaging marker but its clinical implications remain unclear. We estimated the correlation between FVH-ASPECTS and clinical outcomes in patients with wake-up stroke or unknown time of stroke onset. METHODS: The THrombolysis for Acute Wake-up and Unclear-onset Strokes with Alteplase at 0.6 mg/kg (THAWS) trial was a multicenter, randomized controlled trial conducted at 40 sites in Japan between 2014 and 2018. Patients with unknown stroke onset and diffusion-weighted imaging (DWI)-FLAIR mismatch were randomly assigned to receive either intravenous alteplase (0.6 mg/kg) or standard medical treatment. FVH-ASPECTS, a semiquantitative scoring system assessing FVH prominence in the seven cortical ASPECTS regions, was evaluated for its association with favorable outcomes (modified Rankin Scale 0-2 at 90 days). The optimal FVH-ASPECTS threshold was determined using receiver operating characteristic (ROC) analysis and its correlation with favorable outcomes was assessed. RESULTS: Among 131 patients (mean age, 76 ± 13 years; 42% women), 71 received alteplase and 60 did not. Median NIHSS score was 7 (interquartile range [IQR] 4-13), and median FVH-ASPECTS was 4 (IQR 2-4). ROC analysis identified FVH-ASPECTS 3 or more as predictive of favorable outcomes (sensitivity 80%, specificity 51%, area under the ROC curve [AUC] 0.717). A significant correlation was observed between FVH-ASPECTS 3 or more and favorable outcomes (adjusted odds ratio [OR] 4.50, 95% confidence interval [CI] 1.89-10.75; p < 0.001). CONCLUSION: FVH-ASPECTS could offer an indicator for achieving favorable clinical outcomes among stroke patients with unknown time of onset, with a threshold of 3 or more.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".