Predictive Value of Plasma D-Dimer for Cerebral Herniation Post-Thrombectomy in Acute Ischemic Stroke Patients
Bibliographic record
Abstract
Background: Cerebral hernia is a serious complication after thrombectomy in patients with acute ischemic stroke (AIS). This study aims to explore the predictive value of emergency preoperative plasma D-dimer levels in cerebral herniation after successful thrombectomy. Methods: Between January 2019 and December 2023, patients with AIS who received a successful thrombectomy in our single comprehensive stroke center were retrospectively enrolled. We conducted a statistical analysis on the data using SPSS 26.0. Receiver operating characteristic curve (ROC) was used to evaluate the predictive value of D-dimer level for cerebral herniation. Results: Among 278 enrolled patients, 20 cases (7.19%) experienced cerebral herniation. In patients with cerebral hernia, the score of the National Institutes of Health Stroke Scale was higher (16.5 vs 12.0, P < 0.001), the Alberta Stroke Plan early CT score was lower (6.5 vs 8.0, P < 0.001), the score of collateral circulation was lower (2.0 vs 3.0, P < 0.001), the proportion of eTICI blood flow grading of 3 of the occluded vessel was less (35% vs 75.19%), the proportion of pathogenesis of large atherosclerosis was less (5.00% vs 46.51%, P < 0.001), and the level of plasma D-dimer was higher (2.61 vs 0.82). After adjusting for potential confounders, the level of D-dimer (adjusted OR = 1.131, 95% CI 1.022-1.250, P = 0.017) was significantly correlated with cerebral hernia. Based on the ROC curve, the sensitivity and specificity of D-dimer in predicting cerebral herniation were 75.0% and 73.3%, respectively, and the area under the curve was 0.766. Conclusion: Although our study had certain limitations, we found that elevated emergency preoperative plasma D-dimer level is an independent predictive factor for the cerebral herniation after successful thrombectomy in patients with AIS, which is of great clinical significance.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".