The Capillary Index Score as a Marker of Viable Cerebral Tissue
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The capillary index score (CIS) is based on the hypothesis that areas lacking capillary blush on pretreatment cerebral digital subtraction angiograms correspond to nonviable cerebral tissue. METHODS: Pretreatment digital subtraction angiograms and post-treatment noncontrast enhanced computed tomographic scans from the MR CLEAN (Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands) trial were evaluated for areas lacking capillary blush and with tissue hypodensity, respectively. Because the superior and middle zones of the CIS correspond to the 7 cerebral cortex regions of the Alberta Stroke Program Early CT (ASPECT) score, capillary blush was scored in these 2 zones (0-2), called sub-CIS, and compared with the ASPECT score in these 7 regions (0-7), called hypodensity score. The presence and extent of hypodensity were compared between sub-CIS zones with contingency tables and nonparametric comparisons between groups, respectively. RESULTS: On the basis of a sample size of 50 subjects, 100% with sub-CIS <2 had the presence of hypodensity (hypodensity score ≥1) versus 57% for sub-CIS=2 (P=0.004). The extent of hypodensity (numeric hypodensity score) was significantly lower for sub-CIS=2 than 0 or 1 (P=0.02). For 42 subjects with revascularization data, the presence and extent of hypodensity were significantly lower for sub-CIS=2 plus good revascularization than for other combinations of sub-CIS and revascularization (P=0.02 and 0.01, respectively). CONCLUSIONS: The absence of capillary blush on pretreatment digital subtraction angiogram seems to correspond to nonviable cerebral tissue. Successful revascularization reduces the chance of tissue hypodensity (infarction), when capillary blush is present. CLINICAL TRIAL REGISTRATION: URL: http://www.trialregister.nl. Unique identifier: NTR number 1804. URL: http://www.isrctn.com. Unique identifier: ISRCTN10888758.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".