International Journal of Mathematics Trends and Technology
Volume 66 | Issue 3 | Year 2020 | Article Id. IJMTT-V66I3P516 | DOI : https://doi.org/10.14445/22315373/IJMTT-V66I3P516
In the 1960s, Diabetes was considered insignificant in Nigeria. However, its increase prevalence has been contributed to by major socio-economic changes, with 12% cases recorded in some areas. The study assesses the contribution of some risk factors to the survival diabetes patients. Cox proportional hazards regression model, Long-rank and Kaplan- Meier methods were employed in analyzing data collected from a tertiary hospital. The Kaplan Meier curves indicate consistently better survival prognosis in Type 1 diabetes patients than type 2 and gestational diabetes. The long-rank test compared survival function of various levels of the covariates. It was observed that survival experience of different gender is not significantly different while that of various years of admission and diabetes categories did at 0.05 level of significance. Hazard ratio also revealed short survival time in patients diagnosed with type 1 and 2 diabetes relative to baseline hazard (gestational diabetes). However, diagnosis does not contribute significantly to the model. Based on the data, it has been established to a usable extent that better survival prognosis in type 1 diabetes patients than those with type 2 or gestational diabetes, Shorter survival time in female patients than male and no gender difference in survival of diabetes. The only significant factor amongst gender, year of admission and diagnosis was year of admission and earlier admission may be free of event.
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Akindutire O. R, Ogunlade T. O, "Risk Factor Identification Using Survival Analysis," International Journal of Mathematics Trends and Technology (IJMTT), vol. 66, no. 3, pp. 104-109, 2020. Crossref, https://doi.org/10.14445/22315373/IJMTT-V66I3P516
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