Topographic Assessment of Acute Ischemic Changes for Prognostication of Anterior Circulation Stroke
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Bibliographic record
Abstract
BACKGROUND: The location of acute ischemic infarct can affect the clinical outcome of stroke patients. We aimed to develop a prognostic tool based on the topographic distribution of early ischemic changes on admission computed tomography (CT) scans. METHODS: Using the albumin in acute stroke (ALIAS) trials dataset, patients with anterior circulation stroke were included for analysis. A 3-month modified Rankin scale (mRs) score > 2 defined disability/death; and ≤2 defined favorable outcome. A penalized logistic regression determined independent predictors of disability/death among components of admission CT scan Alberta Stroke Program Early CT score (ASPECTS). Follow-up 24-hour CT/MRI scans were reviewed for intracranial hemorrhage (ICH). RESULTS: A simplified ASPECTS (sASPECTS) was developed including the caudate, lentiform nucleus, insula, and M5 components of ASPECTS-which were independent predictors of disability/death on multivariate analysis. There was no significant difference between ASPECTS and sASPECTS in prediction of disability/death (P = .738). Among patients with sASPECTS ≥ 1, the rate of favorable outcome was higher in those with intravenous (IV) thrombolytic therapy (501/837, 59.9%) versus those without treatment (91/183, 49.7%, P = .013); whereas among patients with sASPECTS of 0, IV thrombolysis was not associated with improved outcome. Also, patients with sASPECTS of 0 were more likely to develop symptomatic ICH (odds ratio = 2.62, 95% confidence interval: 1.49-4.62), compared to those with sASPECTS ≥ 1 (P = .004). CONCLUSIONS: Topographic assessment of acute ischemic changes using the sASPECTS (including caudate, lentiform nucleus, insula, and M5) can predict disability/death in anterior circulation stroke as accurately as the ASPECTS; and may help predict response to treatment and risk of developing symptomatic ICH.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 it