MRI-Based Neuroanatomical Predictors of Dysphagia, Dysarthria, and Aphasia in Patients with First Acute Ischemic Stroke
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Due to the high post-stroke frequency of dysphagia, dysarthria, and aphasia, we developed comprehensive neuroanatomical, clinical, and demographic models to predict their presence after acute ischemic stroke. METHODS: The sample included 160 randomly selected first-ever stroke patients with confirmed infarction on magnetic resonance imaging from 1 tertiary stroke center. We documented acute lesions within 12 neuroanatomical regions and their associated volumes. Further, we identified concomitant chronic brain disease, including atrophy, white matter hyperintensities, and covert strokes. We developed predictive models using logistic regression with odds ratios (OR) and their 95% confidence intervals (95% CI) including demographic, clinical, and acute and chronic neuroanatomical factors. RESULTS: Predictors of dysphagia included medullary (OR 6.2, 95% CI 1.5-25.8), insular (OR 4.8, 95% CI 2.0-11.8), and pontine (OR 3.6, 95% CI 1.2-10.1) lesions, followed by brain atrophy (OR 3.0, 95% CI 1.04-8.6), internal capsular lesions (OR 2.9, 95% CI 1.2-6.6), and increasing age (OR 1.4, 95% CI 1.1-1.8). Predictors of dysarthria included pontine (OR 7.8, 95% CI 2.7-22.9), insular (OR 4.5, 95% CI 1.8-11.4), and internal capsular (OR 3.6, 95% CI 1.6-7.9) lesions. Predictors of aphasia included left hemisphere insular (OR 34.4, 95% CI 4.2-283.4), thalamic (OR 6.2, 95% CI 1.6-24.4), and cortical middle cerebral artery (OR 4.7, 95% CI 1.5-14.2) lesions. CONCLUSION: Predicting outcomes following acute stroke is important for treatment decisions. Determining the risk of major post-stroke impairments requires consideration of factors beyond lesion localization. Accordingly, we demonstrated interactions between localized and global brain function for dysphagia and elucidated common lesion locations across 3 debilitating impairments. .
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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 | 0.001 | 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