Acute Ischemic Stroke Infarct Topology: Association with Lesion Volume and Severity of Symptoms at Admission and Discharge
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Acute stroke presentation and outcome depend on both ischemic infarct volume and location. We aimed to determine the association between acute ischemic infarct topology and lesion volume and stroke severity at presentation and discharge. MATERIALS AND METHODS: Patients with acute ischemic stroke who underwent MR imaging within 24 hours of symptom onset or last seen well were included. Infarcts were segmented and coregistered on the Montreal Neurological Institute-152 brain map. Voxel-based analyses were performed to determine the distribution of infarct lesions associated with larger volumes, higher NIHSS scores at admission and discharge, and greater NIHSS/volume ratios. RESULTS: A total of 238 patients were included. Ischemic infarcts involving the bilateral lentiform nuclei, insular ribbons, middle corona radiata, and right precentral gyrus were associated with larger infarct volumes (average, 76.7 ± 125.6 mL versus 16.4 ± 24.0 mL, P < .001) and higher admission NIHSS scores. Meanwhile, brain stem and thalami infarctions were associated with higher admission NIHSS/volume ratios. The discharge NIHSS scores were available in 218 patients, in whom voxel-based analysis demonstrated that ischemic infarcts of the bilateral posterior insular ribbons, middle corona radiata, and right precentral gyrus were associated with more severe symptoms at discharge, whereas ischemic lesions of the brain stem, bilateral thalami, and, to a lesser extent, the middle corona radiata were associated with higher ratios of discharge NIHSS score/infarct volume. CONCLUSIONS: Acute ischemic infarcts of the insulae, lentiform nuclei, and middle corona radiata tend to have larger volumes, more severe presentations, and worse outcomes, whereas brain stem and thalamic infarcts have greater symptom severity relative to smaller lesion volumes.
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 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) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".