Predictors of Malignant Cerebral Edema Following Mechanical Thrombectomy in Acute Ischemic Stroke: A Retrospective Study and Nomogram Development
Bibliographic record
Abstract
OBJECTIVE: To study the risk factors of malignant cerebral edema (MCE) after mechanical thrombectomy (MT) in patients with acute ischemic stroke (AIS) and middle cerebral artery/internal carotid artery occlusion, and to establish a clinical prediction nomogram. METHODS: We retrospectively analyzed patients with AIS who achieved successful recanalization after MT at our hospital from March 2019 to December 2024. These patients were randomly divided into a training cohort (80%) and an internal validation cohort (20%). Independent risk factors associated with MCE were determined using logistic regression analysis, and a nomogram was created on the basis of these factors. The discriminative performance was quantified by the area under the receiver operating characteristic curve (AUC). RESULTS: Among the 284 enrolled patients, 49 (17%) developed MCE. Patients in the MCE group had a significantly higher percentage of a poor functional outcome at 90 days than those in the non-MCE group (88% vs. 45%, P<0.001). Predictors of MCE after MT in patients with AIS included the Alberta Stroke Project Early CT Score, Hyperdensity on CT Score, baseline National Institutes of Health Stroke Scale score, neutrophil-lymphocyte ratio, and puncture-to-reperfusion time >120 min. The nomogram showed excellent discrimination, with an area under the curve of 0.941 (95% CI: 0.909-0.972) in the training cohort and 0.964 (95% CI: 0.921-1.000) in the validation cohort. CONCLUSIONS: We developed a nomogram incorporating 5 readily available clinical and imaging variables that predicts the risk of MCE after MT, which may assist in early clinical decision-making.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".