What will you do with those patients you determine are futile? Leave them to rot? Figure out how to recover on their own with no help from medical 'professionals'?
A visualized nomogram to online predict futile recanalization after endovascular thrombectomy in basilar artery occlusion stroke
ShiTeng Lin1,2†, 
XinPing Lin1,2†, Juan Zhang3†, Meng Wan2,4, Chen Chen2,4, Qiong Jie2,4, YueZhang Wu2,4, 
RunZe Qiu2,4, XiaoLi Cui3, ChunLian Jiang5*, 
JianJun Zou2,4* and ZhiHong Zhao6*- 1School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China
- 2Department of Clinical Pharmacology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
- 3Department of Neurology, Nanjing Yuhua Hospital, Yuhua Branch of Nanjing First Hospital, Nanjing Medical University, Nanjing, China
- 4Department of Pharmacy, Nanjing First Hospital, China Pharmaceutical University, Nanjing, China
- 5Department of Pathology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China
- 6Department of Neurology, The First Affiliated Hospital (People's Hospital of Hunan), Hunan Normal University, Changsha, China
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 ≥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 https://trend.shinyapps.io/DynNomapp/.
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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