TIME-TO-OPTIMAL CONTROL OF HYPERTENSION USING KAPLAN-MEIER ESTIMATOR, COX PROPORTIONAL HAZARD AND WEIBULL MODEL
Keywords:
Hypertension, Time-to-Event, Optimal control, Cox proportional hazard, Weibull modelAbstract
Hypertension is a worldwide public health challenge. The study investigated the time it takes to attain an optimal control of hypertension and the major factors that influence the control in Specialist Hospital, Sokoto.
A retrospective cohort study was conducted involving 300 patient records. The population consisted all hypertensive patients on follow-ups at Specialist Hospital Sokoto from1st February, 2015 to 1st February, 2021.Statistical Package for the Social Sciences version 20 and R software were used for descriptive, Kaplan-Meier estimator, Cox Proportional Regression (CPH) Model and Weibull Regression Model analyses.
Hypertensive patients attain an optimal control after a median survival time of 40.43 (at 95% CI: 33.67- 47.19) months (3.37 years) and mean survival time of 44.18 (CI: 37.24-51.12) months (3.68 years). The CPH analysis revealed that the factors that influenced an optimal control of hypertension were body mass index (BMI) (P <0.001), number of anti-hypertensive drugs (P <0.001), place of residence (P = 0.030). similarly, the Weibull model revealed that the factors that affected an optimal control of hypertension were BMI (P <0.01), number of anti-hypertensive drugs (P <0.001), place of residence (P = 0.042) and educational status (P = 0.036).
In conclusion, BMI, number of anti-hypertensive drugs, Place of residence, Educational status. should be watched out during management of hypertensive patients. This also call for an extension of this study through a prospective design to be able to measure the effect of other factors in the achievement of optimal control of hypertension
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FUDMA Journal of Sciences
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