Development and Validation of a Novel Scoring Model for Predicting Underlying Intracranial Atherosclerosis Prior to Endovascular Treatment in Acute Posterior Circulation Large-Vessel Occlusion

Chuwei Cai^1*Guoyi Peng²Chuming Huang¹Jiaqi Huang³Qiuhui Shi⁴Wei Xu⁵Shiwei Luo⁶Jiong Yang⁷Shouxing Wu⁸Qiao Wu¹Hao Long²

• ¹Shantou Central Hospital, Shantou, China
• ²Southern Medical University, Guangzhou, Guangdong, China
• ³College of Medicine, Shantou University, Shantou, Guangdong Province, China
• ⁴Pengpai Memorial Hospital, Shanwei, China
• ⁵Chaozhou Central Hospital, Chaozhou, Guangdong Province, China
• ⁶Jieyang Medical Research Center, Jieyang People's Hospital, Sun Yat-sen University, Jieyang, Guangdong, China
• ⁷Shanwei Second People's Hospital, Shanwei, Guangdong Province, China
• ⁸Dafeng District People's Hospital, Yancheng, China

Background and Objective Determining the cause of occlusion prior to endovascular treatment (EVT) for acute ischemic stroke caused by large-vessel occlusion (LVO) is helpful for developing a procedure strategy. The aim of this study was to develop and validate a novel scoring model to predict intracranial atherosclerosis-related large-vessel occlusion (ICAS-LVO) in patients with acute vertebrobasilar artery occlusion.The derivation cohort comprised 170 patients who received EVT between January 2018 and June 2024 at multiple centers. The validation cohort comprised 63 patients treated at other centers between June 2019 and December 2024. ICAS-LVO was defined as stenosis >70% or >50% accompanied by hemodynamic disturbances. The relationships between risk factors and ICAS-LVO were assessed via univariate and multivariate logistic regression analyses. The risk factors were used to develop a predictive model. The accuracy of the predictive model was then assessed by the area under the receiver operating characteristic curve (AUROC) in both the derivation and validation cohorts.Results ICAS-LVO was found in 106 (62.4%) and 41 (65.1%) patients in the derivation and validation cohorts, respectively. After binary logistic regression, 5 items were associated with ICAS-LVO, including male sex [odds ratio (OR), 1.05; 95% confidence interval (CI), 1.02-8.09] (P=0.047), history of hypertension [OR, 1.62; 95% CI, 1.72-14.91] (P=0.003), atrial fibrillation (AF) [OR, 0.08; 95% CI, 0.03-0.25] (P=0.001), mydriasis [OR, 0.22; 95% CI, 0.07-0.71] (P<0.011) and terminal basilar artery involvement [OR, 0.12; 95% CI, 0.05-0.30] (P=0.001). A scoring model was created on the basis of the β coefficients of these 5 factors, which demonstrated good calibration ability (Hosmer-Lemeshow test, P = 0.814) and discrimination power (AUROC: 0.898; 95% CI, 0.847-0.950). In the validation cohort, the AUROC, sensitivity and specificity were 0.895 (95% CI, 0.813-0.977), 85.4% and 81.8%, 4 respectively.The scoring model, which was constructed on the basis of male sex, history of hypertension, AF, mydriasis and terminal basilar artery involvement, is a simple and accurate tool for predicting ICAS-LVO before EVT.