Evidence map›Paper›PMID 42909771›Full record

ArticleLa Radiologia medica2026

Predictive value of combined cerebral blood volume index and systemic inflammation indices for 90-day functional outcomes following endovascular treatment in patients with acute ischemic stroke and proximal large vessel occlusion: machine learning model construction and population attributable fraction analysis.

Jiaxin Liu, Xue Chen, Xueliang Tian, Chao Wang, Reziya Abuduxukuer, Yitong Wang, Tiefeng Ji, Zhen-Ni Guo, Hongwei Zhou

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Article in La Radiologia medica, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

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9 authors.

Jiaxin Liu *Department of Radiology, The First Hospital of Jilin University, Changchun, Jilin, China.
Xue Chen *Department of Radiology, The First Hospital of Jilin University, Changchun, Jilin, China.
Xueliang TianDepartment of Breast Surgery, General Surgery Center, The First Hospital of Jilin University, No. 1 Xinmin Street, Changchun, Jilin Province, China.
Chao WangDepartment of Neurology, Stroke Center, The First Hospital of Jilin University, Changchun, Jilin, China.
Reziya AbuduxukuerDepartment of Neurology, Stroke Center, The First Hospital of Jilin University, Changchun, Jilin, China.
Yitong WangDepartment of Radiology, The First Hospital of Jilin University, Changchun, Jilin, China.
Tiefeng JiDepartment of Radiology, The First Hospital of Jilin University, Changchun, Jilin, China. pygcnm@jlu.edu.cn.
Zhen-Ni GuoDepartment of Neurology, Stroke Center, The First Hospital of Jilin University, Changchun, Jilin, China. zhen1ni2@jlu.edu.cn.
Hongwei ZhouDepartment of Radiology, The First Hospital of Jilin University, Changchun, Jilin, China. hwzhou@jlu.edu.cn.ORCID http://orcid.org/0000-0003-1771-6905

Funding

Radiology and Technology Innovation Center of Jilin Province YDZJ202402029CXJDScience and Technology Department of Jilin Province YDZJ202301ZYTS027
6 · The paper itself

Abstract

backgroundWe investigated whether the cerebral blood volume (CBV) index and pretreatment systemic inflammatory indices (SIIs) provide complementary prognostic information for 90-day functional outcomes after successful endovascular therapy (EVT) for anterior circulation large vessel occlusion and evaluated the advantages of machine learning models in terms of prognostic outcomes and quantified adverse outcomes using the population attributable fraction (PAF).

methodsThis retrospective analysis of a prospective registry included 474 patients who were treated between November 2020 and June 2024. An independent 53-patient multicenter cohort was used for external validation. SIIs were calculated from the first venous sample obtained at presentation, before intravenous thrombolysis, and before arterial puncture for EVT. Multivariate logistic regression and eight predictive algorithms were evaluated. PAF estimates were considered exploratory.

resultsAmong 474 patients, 41.6% and 28.5% achieved favorable and excellent outcomes, respectively. Higher CBV indices were more frequent among patients with favorable outcomes, whereas higher inflammatory indices were associated with worse outcomes. Logistic regression showed the highest AUC for mRS 0-2 (0.868, 95% CI 0.806-0.929), while SVM had the highest AUC for mRS 0-1 (0.839, 95% CI 0.764-0.915). The external validation AUCs were 0.816 and 0.802. PAF analysis indicated that improving the CBV index increased favorable and excellent outcomes by 97.2% and 74.8%, respectively, whereas reducing inflammatory overactivation improved them by 22.4%-39.7% and 51.2%-59.5%, respectively.

conclusionBaseline CBV index and pretreatment SII values provided complementary prognostic information after successful EVT. However, prospective validation in a broader population is required before clinical implementation.

Indexed as

Acute ischemic strokeCerebral blood volume indexMachine learningPrognostic modelingSystemic inflammation indices

Identifiers

PMID42909771

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