Emergency admission plasma D-dimer: a novel predictor for symptomatic intracranial hemorrhage after thrombectomy in acute ischemic stroke
Bibliographic record
Abstract
BACKGROUND: Symptomatic intracranial hemorrhage (sICH) is a common and severe complication in patients with acute ischemic stroke (AIS) after treatment with thrombectomy. OBJECTIVE: To explore the ability of admission plasma D-dimer levels to predict sICH after thrombectomy. METHODS: Between February 2018 and August 2021, consecutive patients with AIS who underwent thrombectomy at our single comprehensive stroke center were retrospectively enrolled. sICH was defined according to the criterion of the Heidelberg Bleeding Classification. Logistic regression analysis was performed to determine the risk factors of sICH. The overall discriminative ability of D-dimer levels in predicting sICH was evaluated by adopting a receiver operating characteristic (ROC) curve. RESULTS: Of the 395 enrolled patients, 48 (12.2%) had sICH. Patients with sICH were older (72.9 vs 69.3 years, P=0.037), more often female (62.5% vs 45.5%, P=0.027), had higher D-dimer levels (2.70 vs 0.74 mg/L, P<0.001), higher National Institutes of Health Stroke Scale score (20 vs 15, P<0.001), lower Alberta Stroke Program Early CT Score (8 vs 9, P<0.001), a higher proportion of internal carotid artery occlusions (56.2% vs 30.3%, P<0.001), and less commonly had large-artery atherosclerosis stroke etiology (12.5% vs 32.3%, P=0.010) than patients without sICH. After adjustment for potential confounders, D-dimer levels (adjusted OR=2.45, 95% CI 1.75 to 3.43, P<0.001) remained significantly associated with sICH. Based on the ROC, the D-dimer as a predictor for predicting sICH, presented with a specificity of 86.2%, a negative predictive value of 94.6%, and an area under the curve of 0.774. CONCLUSION: Elevated admission D-dimer levels are an independent predictor of sICH in patients with AIS after thrombectomy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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 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".