Infarction stroke risk prediction model for Indonesian population: A case-control study

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Muhammad Isman Jusuf, Mohammad Hasan Machfoed, Soedjadjadi Keman

2016 Bangladesh Journal of Medical Science Vol. 15 Issue 2 Article Cited by 5 SDG 3SDG 16SDG 17 Quartile

Abstract

Background: Stroke is the main cause of death and disabilities in Indonesia and the world. Various prediction model for stroke have been developed. This study attempts to develop a model used to predict infarction stroke in Indonesia. Objective: This study aims to develop a model to predict infarction stroke risks. Method: This study is an observational research applying case-control research design. The number of samples used in this study were 310 individuals, consisting of 155 members of case group and 155 members of control groups. The writers used discriminant analysis to conduct statistical analysis on the data. Results: Valid and reliable risk factors of stroke used to develop prediction model for infarction stroke in this study are systolic blood pressure, diastolic blood pressure, triglyceride levels, stroke history, hypertension history, dyslipidemia history, vegetable consumption, sleep duration, snoring, exercises, and emotional stresses. Conclusion: This study comes up with a prediction model for infarction stroke risks. The prediction model is expressed by following formula: Infarction stroke risk = 0.929 x Systolic Blood Pressure + 0.886 Diastolic Blood Pressure + 0.160 x Triglyceride Levels + 0.850 x Hypertension History + 0.332 x Stroke History + 0.084 x Dyslipidemia History + 0.124 x Vegetable Consumption + 0.245 x Emotional Stresses + 0.346 x Snoring Habit – 0.193 x Exercise Habit – 0.190 x Sleep Duration. © 2016, Ibn Sina Trust. All rights reserved.

Affiliations

Faculty of Health and Sports, Gorontalo State University, Gorontalo, Indonesia; Faculty of Medicine, Airlangga University, Surabaya, Indonesia; Faculty of Public Health, Airlangga University, Surabaya, Indonesia

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