Evidence map›Paper›PMID 41522282›Full record

ArticleTherapeutic advances in neurological disorders2026

Comprehensive versus thrombectomy-capable stroke centers: a web-based model to predict outcomes after mechanical thrombectomy.

Shujuan Gan, Weifeng Huang, Tingyu Yi, Wenli Zhang, Xiongwei Lu, Zhiting Chen, Jinfeng Miao, Yanmin Wu, Meihua Wu, Caixia Li and 8 more

Abstract read
In one paragraph

Article in Therapeutic advances in neurological disorders, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Shujuan GanDepartment of Cerebrovascular Disease, Fujian Medical University Union Hospital, Fujian, China.ORCID https://orcid.org/0009-0003-4149-1635
Weifeng HuangDepartment of Cerebrovascular Disease, Fujian Medical University Union Hospital, Fujian, China.
Tingyu YiCerebrovascular and Neuro-Intervention Department, Zhangzhou Affiliated Hospital of Fujian Medical University, Fujian, China.
Wenli ZhangDepartment of Neurology, The Second Hospital of Zhangzhou, Fujian, China.
Xiongwei LuDepartment of Neurology, Xiushui County First People's Hospital, Jiangxi, China.
Zhiting ChenDepartment of Cerebrovascular Disease, Fujian Medical University Union Hospital, Fujian, China.
Jinfeng MiaoDepartment of Cerebrovascular Disease, Fujian Medical University Union Hospital, Fujian, China.
Yanmin WuCerebrovascular and Neuro-Intervention Department, Zhangzhou Affiliated Hospital of Fujian Medical University, Fujian, China.
Meihua WuCerebrovascular and Neuro-Intervention Department, Zhangzhou Affiliated Hospital of Fujian Medical University, Fujian, China.
Caixia LiCerebrovascular and Neuro-Intervention Department, Zhangzhou Affiliated Hospital of Fujian Medical University, Fujian, China.
Yining YangCerebrovascular and Neuro-Intervention Department, Zhangzhou Affiliated Hospital of Fujian Medical University, Fujian, China.
Jinhua YeCerebrovascular and Neuro-Intervention Department, Zhangzhou Affiliated Hospital of Fujian Medical University, Fujian, China.
Huanghuang ChenCerebrovascular and Neuro-Intervention Department, Zhangzhou Affiliated Hospital of Fujian Medical University, Fujian, China.
Ying WuCerebrovascular and Neuro-Intervention Department, Zhangzhou Affiliated Hospital of Fujian Medical University, Fujian, China.
Xiaona ZhuangDepartment of Cerebrovascular Disease, Fujian Medical University Union Hospital, Fujian, China.
Yuxin XuDepartment of Cerebrovascular Disease, Fujian Medical University Union Hospital, Fujian, China.
Liqun JiaoDepartment of Neurosurgery, Xuanwu Hospital, China International Neuroscience Institute, Capital Medical University, National Center for Neurological Disorders, Beijing 100053, China.
Wenhuo ChenDepartment of Cerebrovascular Disease, Fujian Medical University Union Hospital, Fuzhou 350001, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The quality and clinical outcomes of mechanical thrombectomy (MT) performed at thrombectomy-capable stroke centers (TSCs) versus comprehensive stroke centers (CSCs) remain insufficiently characterized. Objective: To compare MT outcomes between TSCs and CSCs and to develop and externally validate an online tool for individualized prognosis and decision support. Design: Retrospective cohort study including derivation and external validation cohorts from multiple stroke centers. Method: Patients with anterior circulation large vessel occlusion who underwent MT within 24 h were analyzed. Inverse probability of treatment weighting (IPTW) and multivariable logistic regression estimated the effects of stroke center certification. Sensitivity analyses using alternative model specifications, patient subsets, and predefined subgroups assessed robustness and heterogeneity. A prognostic model was developed using least absolute shrinkage and selection operator regression after IPTW, externally validated using 2023-2024 data from different centers, and deployed as a Shiny-based online tool predicting 90-day modified Rankin Scale outcomes (0-2 for independence, 0-5 for survival). Results: The median age was 69 years (interquartile range (IQR) 60-77) in the derivation cohort ( Conclusion: CSCs were significantly associated with a higher probability of survival compared to TSCs, while no significant difference was observed in favorable functional outcomes. An online multivariable model could predict clinical outcomes and guide decision-making between TSCs and CSCs in routine clinical practice.

Indexed as

large vessel occlusionprognostic modelingstroke centersthrombectomytreatment outcome

Identifiers

PMID41522282
PMCPMC12789381

What Socratic holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.