Internal Borderzone Infarction
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Among subcortical infarctions, internal borderzone infarcts (IBI) are considered to be separate entities from perforating artery infarcts (PAI). The purpose of the present study is to examine the relationship between the presence of IBI and the degree of angiographically defined internal carotid artery (ICA) stenosis in symptomatic patients. METHODS: A review of 1253 brain CTs from patients recruited by the North American Symptomatic Carotid Endarterectomy Trial was performed, using templates for the identification of subcortical and cortical vascular territories. RESULTS: A total of 413 patients had visible ischemic lesions on the side ipsilateral to their symptomatic ICA. Of these, 138 had PAI, 108 had IBI, 122 had cortical infarcts, and 45 had a combination of different lesions. Mean (+/-SD) lesion diameter was larger for IBI (11.0+/-5.9 mm) than for PAI (7.1+/-4.7 mm) (P<0.001 for comparing 2 means). IBI was associated with higher degrees of ICA stenosis (P<0. 001). Sixty-three percent of the patients with IBI had severe (70% to 99%) ICA stenosis compared with 42% of patients with PAI; 18% of the IBI patients had stenosis of 90% or more compared with 8% of the patients with PAI. Multiple logistic regression did not identify any patient characteristics as confounders. CONCLUSIONS: Among subcortical infarctions, IBI are associated with higher degrees of ICA stenosis in symptomatic patients. Differentiating between internal borderzone and perforating artery infarcts is important, because each may arise from different mechanisms, namely, carotid disease and small-vessel disease, respectively.
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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 | 0.000 | 0.001 |
| 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) | 0.003 | 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".