Use of cerebral hemorrhage volume calculation methods in patients with ASPECTS <6
Bibliographic record
Abstract
Objective: We aimed to determine whether the ABC/2 can be used as an infarct volume measurement tool for Mechanical thrombectomy (MT) in patients with Alberta Stroke Program Early CT Scores (ASPECTS) < 6. Methods: Patients with stroke with ASPECTS <6 within 24 h were included in this study, and infarct volume was measured using the ABC/2. The patients were categorized into MT and standard drug groups. They were assessed based on a modified Rankin Scale (mRS) ≤3 at 3 months, intracranial hemorrhage within 48 h, and mortality at 3 months. Results: ASPECTS <6 showed a significant negative correlation with infarct volume measured using the ABC/2. Compared to drug therapy, the patients who received MT treatment had a higher proportion of achieving an mRS score of ≤3 (OR, 2.60; 95 % confidence interval [CI], 1.04-6.50; P = 0.040), a lower death rate (OR, 0.37; 95 % CI, 0.15-0.92; P = 0.031), and a reduced decompressive craniectomy (OR, 0.10; 95 % CI, 0.01-0.83; P = 0.033); however, intracranial hemorrhage risk significantly increased (OR, 4.35; 95 % CI, 1.12-17.0; P = 0.034). Conclusion: In the absence of advanced imaging, the ABC/2 can be a useful tool for measuring volume in anterior circulation in patients with ASPECTS <6.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".