Association of clinical outcome and imaging endpoints in extensive ischemic stroke—comparing measures of cerebral edema
Bibliographic record
Abstract
OBJECTIVES: Ischemic edema is associated with worse clinical outcomes, especially in large infarcts. Computed tomography (CT)-based densitometry allows direct quantification of absolute edema volume (EV), which challenges indirect biomarkers like midline shift (MLS). We compared EV and MLS as imaging biomarkers of ischemic edema and predictors of malignant infarction (MI) and very poor clinical outcome (VPCO) in early follow-up CT of patients with large infarcts. MATERIALS AND METHODS: Patients with anterior circulation stroke, large vessel occlusion, and Alberta Stroke Program Early CT Score (ASPECTS) ≤ 5 were included. VPCO was defined as modified Rankin scale (mRS) ≥ 5 at discharge. MLS and EV were quantified at admission and in follow-up CT 24 h after admission. Correlation was analyzed between MLS, EV, and total infarct volume (TIV). Multivariable logistic regression and receiver operating characteristics curve analyses were performed to compare MLS and EV as predictors of MI and VPCO. RESULTS: Seventy patients (median TIV 110 mL) were analyzed. EV showed strong correlation to TIV (r = 0.91, p < 0.001) and good diagnostic accuracy to classify MI (EV AUC 0.74 [95%CI 0.61-0.88] vs. MLS AUC 0.82 [95%CI 0.71-0.94]; p = 0.48) and VPCO (EV AUC 0.72 [95%CI 0.60-0.84] vs. MLS AUC 0.69 [95%CI 0.57-0.81]; p = 0.5) with no significant difference compared to MLS, which did not correlate with TIV < 110 mL (r = 0.17, p = 0.33). CONCLUSION: EV might serve as an imaging biomarker of ischemic edema in future studies, as it is applicable to infarcts of all volumes and predicts MI and VPCO in patients with large infarcts with the same accuracy as MLS. CLINICAL RELEVANCE STATEMENT: Utilization of edema volume instead of midline shift as an edema parameter would allow differentiation of patients with large and small infarcts based on the extent of edema, with possible advantages in the prediction of treatment effects, complications, and outcome. KEY POINTS: • CT densitometry-based absolute edema volume challenges midline shift as current gold standard measure of ischemic edema. • Edema volume predicts malignant infarction and poor clinical outcome in patients with large infarcts with similar accuracy compared to MLS irrespective of the lesion extent. • Edema volume might serve as a reliable quantitative imaging biomarker of ischemic edema in acute stroke triage independent of lesion size.
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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 | 0.002 | 0.001 |
| 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".