Abstract 58: Prediction of Malignant Edema Formation After Endovascular Treatment for Middle Cerebral Artery Infarction: The Added Value of Intracranial Cerebrospinal Fluid Volume
Bibliographic record
Abstract
Introduction: Prediction models may guide decisions in the management of patients at risk for malignant middle cerebral artery infarction. The ratio of intracranial cerebrospinal fluid (CSF) volume to intracranial volume (ICV) has been identified as a predictor of malignant edema in ischemic stroke patients treated with intravenous thrombolysis. The added predictive value in stroke patients who received endovascular treatment is unknown. Methods: Patients with available thin-slice non-contrast CT data on admission were selected from the MR CLEAN Registry, which is a prospective national multicenter registry of patients with large vessel occlusion who were treated with endovascular treatment between 2014 and 2017. Baseline characteristics and CT imaging data were collected. The CSF/ICV ratio was automatically measured on baseline thin-slice non-contrast CT. The primary outcome was the formation of malignant edema based on clinical and imaging features on follow-up. A previously built logistic regression model was fitted and included the following baseline predictors: age, National Institutes of Health Stroke Scale, Alberta Stroke Program Early CT score, poor collateral filling and reperfusion. An extended model with the CSF/ICV ratio was compared to the previous model by using the likelihood ratio test. Odds ratios (OR), areas under the receiver operating characteristic curve (AUROC) and 95% confidence intervals (CI) were reported. Results: Of the included 683 patients 40 (6%) developed malignant edema. The CSF/ICV ratio of the group with malignant edema (mean 9±5%) was lower than the group without malignant edema (mean 14±6%, P<0.001). In the extended model, the CSF/ICV ratio was associated with the formation of malignant edema (per one percent decrease OR 1.2, 95% CI 1.1-1.3, P<0.001). In addition, the discriminative performance of the model with the CSF/ICV ratio (AUROC 0.87, 95% CI 0.82-0.91) was higher than that of the model without the CSF/ICV ratio (AUROC 0.84, 0.78-0.89, P<0.001). Conclusions: The CSF/ICV ratio improves the prediction of malignant edema formation in ischemic stroke patients who received endovascular treatment.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".