Evidence map›Paper›PMID 36313517›Full record

ArticleFrontiers in neurology2022

The difference in red blood cell distribution width from before to after thrombolysis as a prognostic factor in acute ischemic stroke patients: A 2-year follow-up.

Yanyan Jiang, Chuancheng Ren, Aydos Alimujiang, Yuncheng Wu, Dongya Huang, Weiting Yang

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Article in Frontiers in neurology, 2022. 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

Authors and funding

6 authors.

Yanyan JiangDepartment of Neurology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
Chuancheng RenDepartment of Neurology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
Aydos AlimujiangDepartment of Neurology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
Yuncheng WuDepartment of Neurology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Dongya HuangDepartment of Neurology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
Weiting YangDepartment of Neurology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: The aim of our study was to determine whether delta red blood cell distribution (ΔRDW) improves neurological outcomes in acute ischemic stroke (AIS) patients 2 years after intravenous thrombolysis (IVT) therapy. Methods: AIS patients who received IVT between January 2013 and December 2019 were retrospectively analyzed. In accordance with their mRS scores, the patients were divided into two groups. A binary logistic regression analysis was conducted to determine the influencing factors of adverse functional outcomes. It was decided to evaluate the variables' the predictive ability by using the area under the receiver operating characteristic. For the poor neurological recovery risk model, features were selected using the LASSO regression model. We also developed a predictive model based on logistic regression analysis, which combined the features selected in the minimum absolute contraction and selection operator regression models. An evaluation of the discrimination, calibration, and clinical applicability of the predictive model was conducted using the C index, calibration chart, and decision curve analysis. Internal validation was evaluated via bootstrapping. Results: Binary logistic regression analysis showed that ΔRDW was an independent influencing factor for poor neurofunctional outcomes. The most appropriate ΔRDW cut-off value for predicting the recovery of poor neurological outcomes was 18.9% (sensitivity: 89.9%, specificity: 78.6%, Conclusion: In patients with AIS after thrombolysis, the ΔRDW is a potential influencing factor that can be readily used to predict the likelihood of poor neurological function recovery.

Indexed as

2-year follow-upacute ischemic strokepredictive factorrecombinant tissue plasminogen activatorred blood cell distribution width

Identifiers

PMID36313517
PMCPMC9606336

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