Bayesian Joint Modeling of Longitudinal and Survival Time Measurement of Hypertension Patients

Joint modeling of longitudinal change of fasting blood sugar and systolic blood pressure with survival time to death among hypertension patients

Hypertension is a universal public health challenge and a leading modifiable risk factor for cardiovascular disease and death. It is also called high blood pressure, described by two measured quantities systolic blood pressure (SBP) 140 mmHg or greater and diastolic blood pressure (DBP) 90 mmHg or greater. As the result, this study aims to use the joint model application to identify the factors that affect longitudinal changes in fasting blood sugar, SBP, and survival time to death of hypertension patients and their associations admitted to the Arba Minch General Hospital. We considered a total of 354 random samples of hypertension patients who had under follow-up at Arba Minch general hospital from January 2012 to February 2020. Among 2330 hypertension patients under follow-up, 354 were selected with a simple random sampling technique, and data was collected from the patient's medical cards. After evaluating the longitudinal data with a linear mixed model and the baseline data with Cox proportional models, the joint models of both sub-models were assessed in R software version 4.2. According to the findings, the association between longitudinal changes (FBS, SBP, and time to death in hypertension patients was statistically significant. Ages, place of residence, lifestyle change, stages of hypertension, blood cholesterol level, related diseases, adherence to treatment, family history of hypertension patients, and DBP at baseline were associated factors that affect survival time and longitudinal measurement of FBS and SBP of the patients. The computed association parameters revealed subject-specific values. The subject-specific linear time slope of FBS and SBP was negatively related to the hazard rate of time to death of hypertension patients in Arba Minch general hospital. To reduce the risk of hypertension in patients, health professionals, governmental organizations, and non-governmental organizations must promote the implementation of community-based screening programs for early detection of hypertension.

Joint modeling of blood pressure measurement and survival time of hypertension patients

Hypertension is a chronic disease that has a major health problem over the centuries due to its significant contribution to the global burden. The objective of this study was to examine the association of survival time and longitudinal Systolic Blood Pressure (SBP) measurement and finding potential barrier that affects SBP measurement and the survival time of hypertension patients. The study considered a cohort of 318 hypertension patients who were aged 18 years or older and were under follow-up from January 1, 2012, to February 30, 2020, at Arba Minch General Hospital. To analyze the data we employed linear mixed effect model, Weibull model, and joint modeling approach for longitudinal and survival data. The results from joint model analysis indicate that systolic blood pressure measurement is significantly associated with survival time of hypertension patients. The results from the longitudinal sub-model reveals that alcohol use, Khat intake, smoking tobacco, stages of hypertension diseases, adherence to treatment, related diseases, and family history had statistical significant relationship with mean change in the [Formula: see text] measurement. Furthermore, from the survival sub-model, we found the survival probability of hypertension patients was determined by family history, stages of hypertension disease, related diseases, and smoking tobacco. The analysis suggests that there is a strong association between SBP measurement and survival time of hypertension patients. Thus we recommend aggressive work by all concerned bodies towards awareness creation about the effect of potential barriers.