Impact of infarct location on functional outcome following endovascular therapy for stroke
Bibliographic record
Abstract
OBJECTIVES: The relationship between stroke topography (ie, the regions damaged by the infarct) and functional outcome can aid clinicians in their decision-making at the acute and later stages. However, the side (left or right) of the stroke may also influence the identification of clinically relevant regions. We sought to determine which brain regions are associated with good functional outcome at 3 months in patients with left-sided and right-sided stroke treated by endovascular treatment using the diffusion-weighted imaging-Alberta Stroke Program Early CT Score (DWI-ASPECTS). METHODS: Patients with ischaemic stroke (n = 405) were included from the ASTER trial and Pitié-Salpêtrière registry. Blinded readers rated ASPECTS on day 1 DWI. Stepwise logistic regression analyses were performed to identify the regions related to 3-month outcome in left (n = 190) and right (n = 215) sided strokes with the modified Rankin scale (0-2) as a binary independent variable and with the 10 regions-of-interest of the DWI-ASPECTS as independent variables. RESULTS: Median National Institute of Health Stroke Scale (NIHSS) at baseline was 17 (IQR: 12-20), median age was 70 years (IQR: 58-80) and median day-one NIHSS 9 (IQR: 4-18). Not all brain regions have the same weight in predicting good outcome at 3 months; moreover, these regions depend on the affected hemisphere. In left-sided strokes, the multivariate analysis revealed that preservation of the caudate nucleus, the internal capsule and the cortical M5 region were independent predictors of good outcome. In right-sided strokes, the cortical M3 and M6 regions were found to be clinically relevant. CONCLUSION: Cortical non-motors areas related to outcome differed between left-sided and right-sided strokes. This difference might reflect the specialisation of the dominant and non-dominant hemispheres for language and attention, respectively. These results may influence decision-making at the acute and later stages. TRIAL REGISTRATION NUMBER: NCT02523261.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".