Journal of Multidisciplinary Healthcare (Dec 2022)

A Prediction Model for Rapid Identification of Ischemic Stroke: Application of Serum Soluble Corin

  • Lu Y,
  • Wang W,
  • Tang Z,
  • Chen L,
  • Zhang M,
  • Zhang Q,
  • Wu L,
  • Jiang J,
  • Zhang X,
  • He C,
  • Peng H

Journal volume & issue
Vol. Volume 15
pp. 2933 – 2943

Abstract

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Ying Lu,1,* Weiqi Wang,1,* Zijie Tang,1 Linan Chen,1 Min Zhang,2 Qiu Zhang,3 Lei Wu,4 Jun Jiang,5 Xiaolong Zhang,5 Chuan He,1 Hao Peng1,5,6 1Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, People’s Republic of China; 2Department of Central Office, Suzhou National New and Hi-tech Industrial Development Zone Center for Disease Control and Prevention, Suzhou, People’s Republic of China; 3Department of Chronic Disease, Gusu Center for Disease Control and Prevention, Suzhou, People’s Republic of China; 4Department of Maternal and Child Health, Suzhou Industrial Park Center for Disease Control and Prevention, Suzhou, People’s Republic of China; 5Department of Tuberculosis Control, Suzhou Center for Disease Control and Prevention, Suzhou, People’s Republic of China; 6Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, People’s Republic of China*These authors contributed equally to this workCorrespondence: Hao Peng; Chuan He, Department of Epidemiology, School of Public Health, Medical College of Soochow University, 199 Renai Road, Industrial Park District, Suzhou, 215123, People’s Republic of China, Tel +86 512 6588 0079, Email [email protected]; [email protected]: Rapid identification is critical for ischemic stroke due to the very narrow therapeutic time window. The objective of this study was to construct a diagnostic model for the rapid identification of ischemic stroke.Methods: A mixture population constituted of patients with ischemic stroke (n = 481), patients with hemorrhagic stroke (n = 116), and healthy individuals from communities (n = 2498) were randomly resampled into training (n = 1547, mean age: 55 years, 44% males) and testing (n = 1548, mean age: 54 years, 43% males) samples. Serum corin was assayed using commercial ELISA kits. Potential risk factors including age, sex, education level, cigarette smoking, alcohol consumption, obesity, blood pressure, lipids, glucose, and medical history were obtained as candidate predictors. The diagnostic model of ischemic stroke was developed using a backward stepwise logistic regression model in the training sample and validated in the testing sample.Results: The final diagnostic model included age, sex, cigarette smoking, family history of stroke, history of hypertension, systolic blood pressure, total cholesterol, high-density lipoprotein cholesterol, fasting glucose, and serum corin. The diagnostic model exhibited good discrimination in both training (AUC: 0.910, 95% CI: 0.884– 0.936) and testing (AUC: 0.907, 95% CI: 0.881– 0.934) samples. Calibration curves showed good concordance between the observed and predicted probability of ischemic stroke in both samples (all P> 0.05).Conclusion: We developed a simple diagnostic model with routinely available variables to assist rapid identification of ischemic stroke. The effectiveness and efficiency of this model warranted further investigation.Keywords: ischemic stroke, serum corin, biomarker, prediction model

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