Thalamic Diaschisis in Acute Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Ipsilateral thalamic diaschisis (ITD) describes the reduction of thalamic function, metabolism, and perfusion resulting from a distant lesion of the ipsilateral hemisphere. Our aim was to evaluate the perfusion characteristics and clinical impact of ITD in acute middle cerebral artery stroke, which does not directly affect the thalamus. METHODS: One hundred twenty-four patients with middle cerebral artery infarction were selected from a prospectively acquired cohort of 1644 patients who underwent multiparametric computed tomography (CT), including CT perfusion for suspected stroke. Two blinded readers evaluated the occurrence of ITD, defined as ipsilateral thalamic hypoperfusion present on ≥2 CT perfusion maps. Perfusion alterations were defined according to the Alberta Stroke Program Early CT Score regions. Final infarction volume and subacute complications were assessed on follow-up imaging. Clinical outcome was quantified using the modified Rankin Scale. Multivariable linear and ordinal logistic regression analysis were applied to identify independent associations. RESULTS: >0.05). ITD had no influence on the development of subacute stroke complications. CONCLUSIONS: ITD in the form of thalamic hypoperfusion is a frequent CT perfusion finding in the acute phase in middle cerebral artery stroke patients with marked involvement of subcortical areas. ITD does not result in thalamic infarction and had no independent impact on patient outcome. Notably, ITD was misclassified as part of the ischemic core by automated software, which might affect patient selection in CT perfusion-based trials.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".