ORIGINAL RESEARCH article
Front. Neurol.
Sec. Neurological Biomarkers
Associations between Blood glucose - lipid levels and post-intravenous thrombolysis outcomes in stroke patients: A retrospective study utilizing logistic regression analysis
Department of neurology, Affiliated Hospital of Southwest Jiaotong University, The Third People's Hospital of Chengdu, Chengdu Sichuan 610031, China, Chengdu, China
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Abstract
Objective: This study investigates the relationship between blood glucose and lipid profiles and the functional outcomes of acute ischemic stroke (AIS) patients treated with intravenous thrombolysis. Methods: We retrospectively analyzed data from AIS patients admitted to a tertiary hospital in Chengdu between September 2023 and March 2025. Patients were grouped according to post-thrombolysis modified Rankin Scale (mRS) scores into good outcome (0–2) and poor outcome (3–6) categories. Multivariable logistic regression and nomogram modeling were used to identify predictors of 30- and 90-day outcomes. Results: The final predictive model included 11 variables, and the results showed higher age, smoking, diabetes, higher systolic blood pressure (SBP) , higher diastolic blood pressure (DBP), higher total cholesterol (TC), lower high-density lipoprotein cholesterol (HDL), higher low-density lipoprotein cholesterol (LDL), higher haemoglobin A1c (HbA1c), and higher fasting plasma glucose (FPG) were independent risk factors. This model demonstrated robust predictive performance and accuracy across all timepoints (training dataset at 30 days, the AUC of 0.821 ,95%CI: 0.765-0.877; training dataset at 90 days, the AUC of 0.871 ,95%CI: 0.824-0.919). Conclusion: Blood glucose and lipid levels are linked to outcomes after intravenous thrombolysis in stroke. Despite model limitations, these modifiable parameters may support risk-stratified management, potentially improving functional outcomes post-thrombolysis.
Summary
Keywords
Acute ischemic stroke, blood glucose-lipid levels, intravenousthrombolysis, logistic regression model, Modified Rankin scale
Received
03 October 2025
Accepted
02 February 2026
Copyright
© 2026 He, Li, Liu, Tan, Wang, Zhu, Zhou, Yang and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Hua Liu
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