4.6 Article

A visualized nomogram to online predict futile recanalization after endovascular thrombectomy in basilar artery occlusion stroke

期刊

FRONTIERS IN NEUROLOGY
卷 13, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fneur.2022.968037

关键词

basilar artery occlusion; futile recanalization; endovascular thrombectomy; nomogram model; predictive model

资金

  1. National Natural Science Foundation of China
  2. Jiangsu Pharmaceutical Association
  3. Hunan Natural Science Foundation
  4. Hunan innovation guidance grant of clinical medical technology
  5. [82173899]
  6. [H202108]
  7. [A2021024]
  8. [2021JJ70021]
  9. [2020SK50920]

向作者/读者索取更多资源

By developing a visualized nomogram model, we can early identify patients with basilar artery occlusion who would be at high risk of futile recanalization and assist neurologists in selecting appropriate candidates for endovascular thrombectomy.
Background and purpose: Futile recanalization occurs in a significant proportion of patients with basilar artery occlusion (BAO) after endovascular thrombectomy (EVT). Therefore, our goal was to develop a visualized nomogram model to early identify patients with BAO who would be at high risk of futile recanalization, more importantly, to aid neurologists in selecting the most appropriate candidates for EVT. Methods: Patients with BAO with EVT and the Thrombolysis in Cerebral Infarction score of & GE;2b were included in the National Advanced Stroke Center of Nanjing First Hospital (China) from October 2016 to June 2021. The exclusion criteria were lacking the 3-month Modified Rankin Scale (mRS), age < 18 years, the premorbid mRS score > 2, and unavailable baseline CT imaging. Potential predictors were selected for the construction of the nomogram model and the predictive and calibration capabilities of the model were assessed. Results: A total of 84 patients with BAO were finally enrolled in this study, and patients with futile recanalization accounted for 50.0% (42). The area under the curve (AUC) of the nomogram model was 0.866 (95% CI, 0.786-0.946). The mean squared error, an indicator of the calibration ability of our prediction model, was 0.025. A web-based nomogram model for broader and easier access by clinicians is available online at . Conclusion: We constructed a visualized nomogram model to accurately and online predict the risk of futile recanalization for patients with BAO, as well as assist in the selection of appropriate candidates for EVT.

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