ArticleAmerican journal of translational research2023
Analysis of influencing factors of hemorrhagic transformation in patients with large vessel occlusion stroke after mechanical thrombectomy.
Article in American journal of translational research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Early Predictive Accuracy of Machine Learning for Hemorrhagic Transformation in Acute Ischemic Stroke: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Machine learning-enabled prediction of hemorrhagic transformation post-thrombectomy using quantitative DSA.Scientific reports · 2026Article
- Predictive value of CT imaging features on the risk of hemorrhagic transformation after mechanical thrombectomy for acute ischemic stroke with large vessel obstruction.Biomedical engineering online · 2025Article
- Development of a novel nomogram to predict hemorrhagic transformation following endovascular treatment in patients with acute ischemic stroke.Frontiers in neurology · 2025Article
- Evaluating the interaction between hemorrhagic transformation and cerebral edema on functional outcome after ischemic stroke.Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association · 2024Article
- The differences of fibrinogen levels in various types of hemorrhagic transformations.Frontiers in neurology · 2024Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
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Abstract
objectiveTo investigate the influencing factors of hemorrhagic transformation (HT) after mechanical thrombectomy (MT) in patients with large vessel occlusion (LVO) stroke.
methodsFrom September 2018 to December 2022, 270 eligible patients with LVO who underwent MT in the First Affiliated Hospital of Nanjing medical University were selected for this retrospective study, and the patients were divided into an occurrence group and a non-occurrence group based on the immediate and 24 h postoperative head CT results. The influencing factors of postoperative HT after MT were identified using univariate and logistic regression analyses. A Nomogram was constructed using logistic variables of significance. Then, area under the ROC curve (AUC) was used to verify the predictive efficacy of the Nomogram, and decision curve analysis (DCA) was used to test the clinical validity of the Nomogram.
resultsHT occurred in 60 patients (23.70%) after MT. Logistic regression analysis showed that, male (OR=2.099, 95% CI: 1.051-4.193), age ≥71.5 years (OR=3.780, 95% CI: 1.836-7.782), preoperative NIHSS score ≥16.5 (OR=2.328, 95% CI: 1.112-4.873), operation time ≥58.5 min (OR=2.930, 95% CI: 1.294-6.634), and admission blood glucose ≥7.65 mmol/L (OR=4.915, 95% CI: 2.373-10.178) were risk factors for the occurrence of HT in patients with LVO stroke after MT. Admission serum magnesium ≥0.845 mmol/L (OR=0.225, 95% CI: 0.127-0.513) was a protective factor for the occurrence of HT in the patients after MT. The ROC curve showed that the AUC of the nomogram in the training set and test set were 0.849 (95% CI: 0.787-0.910) and 0.754 (95% CI: 0.634-0.874), respectively. DCA suggested that the nomogram revealed good clinical validity in the training and test sets.
conclusionSex, age, preoperative NIHSS score, operation time, blood glucose and serum magnesium levels at admission are influencing factors for the occurrence of HT in patients with LVO stroke after MT. The nomogram in this study has a good predictive efficiency, which can improve the diagnostic efficiency of HT after MT in patients with LVO stroke. Therefore, male patients with age ≥71.5 years, preoperative NIHSS score ≥16.5, operation time ≥58.5 min, admission blood glucose ≥7.65 mmol/L, and admission serum magnesium ≤0.845 mmol/L should raise awareness about the risk of HT after MT.
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37969192PMC10641364W4388737130What OpenQuestion holds
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