Development and internal-external validation of the ATHE Scale: predicting acute large vessel occlusion due to underlying intracranial atherosclerosis prior to endovascular treatment

Author:

Chen Wang1,Liu Ji2,Yang Lei1,Sun Hongyang2,Yang Shuna1,Wang Mengen2,Qin Wei1,Wang Yang3,Wang Xianjun2,Hu Wenli1

Affiliation:

1. Departments of Neurology and

2. Department of Neurology, Linyi People’s Hospital, Linyi, Shandong, China

3. Neurosurgery, Beijing Chaoyang Hospital, Capital Medical University, Chaoyang, Beijing, China; and

Abstract

OBJECTIVE The diagnosis of intracranial atherosclerosis (ICAS) associated with large vessel occlusion (LVO) before endovascular treatment (EVT) remains a clinical challenge. This study was aimed at developing a predictive model for ICAS-LVO in the anterior circulation preceding EVT. METHODS Patients from two national stroke centers who had undergone EVT for acute ischemic stroke in the anterior circulation were evaluated. Those from one center served as the derivation cohort, whereas patients from another center functioned as the external validation cohort. ICAS-LVO was characterized as stenosis exceeding 70% or stenosis surpassing 50% accompanied by distal blood flow disruption or recurrent occlusion evidence during the intervention. A random forest algorithm helped to identify key predictors within the derivation cohort. Utilizing these predictors, the authors formulated a logistic regression model from the derivation cohort data, and the model was then internally validated through a bootstrapping method. Subsequently, a predictive score based on this model was constructed and evaluated in both cohorts. RESULTS Among all the patients, 470 from the derivation cohort and 147 from the external validation cohort met the inclusion criteria. After random forest regression, the key predictors of ICAS-LVO included the absence of atrial fibrillation, the presence of truncal-type occlusion, the absence of a hyperdense artery sign, and a lower baseline examination National Institutes of Health Stroke Scale (NIHSS) score (ATHE Scale). Incorporating these variables into the logistic regression model yielded an area under the curve (AUC) of 0.920 (95% CI 0.894–0.947) for ICAS-LVO prediction. After bootstrapping validation, the model produced a mean AUC of 0.915. Subsequently, the ATHE score, derived from these predictors, registered an AUC of 0.916 (95% CI 0.887–0.939, p < 0.001) in the derivation cohort and 0.890 (95% CI 0.828–0.936, p < 0.001) in the external validation cohort. CONCLUSIONS The ATHE Scale, incorporating atrial fibrillation, truncal-type occlusion, hyperdense artery sign, and baseline examination NIHSS score, is an accurate, objective tool for predicting ICAS-LVO prior to EVT.

Publisher

Journal of Neurosurgery Publishing Group (JNSPG)

Reference40 articles.

1. Guidelines for the early management of patients with acute ischemic stroke: 2019 update to the 2018 Guidelines for the Early Management of Acute Ischemic Stroke: a guideline for healthcare professionals from the American Heart Association/American Stroke Association;Powers WJ,2019

2. Indications for thrombectomy in acute ischemic stroke from emergent large vessel occlusion (ELVO): report of the SNIS Standards and Guidelines Committee;Mokin M,2019

3. European Stroke Organisation (ESO)- European Society for Minimally Invasive Neurological Therapy (ESMINT) guidelines on mechanical thrombectomy in acute ischemic stroke;Turc G,2019

4. Chinese guideline of endovascular treatment for acute ischemic stroke 2023,2023

5. Current status of endovascular treatment for acute large vessel occlusion in china: a real-world nationwide registry;Jia B,2021

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