Bivariate longitudinal data analysis: a case of hypertensive patients at Felege Hiwot Referral Hospital, Bahir Dar, Ethiopia

Workie, Demeke Lakew; Zike, Dereje Tesfaye; Fenta, Haile Mekonnen

doi:10.1186/s13104-017-3044-4

Cited by 9 publications

(25 citation statements)

References 24 publications

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“…The present study stated that average SBP and average DBP were higher for patients who had diabetes compared to patients who had no diabetic disease. Consistent with previous studies [4,27,28] the average SBP and DBP of patients who had diabetes disease were signi cantly increased compared to patients who had no diabetes disease. Which state that co-existence of diabetes mellitus and hypertension is also associated with accelerated blood pressure rising.…”

Section: Discussionsupporting

confidence: 91%

Joint Modeling of Longitudinal Measurements and Survival Time to Cardiovascular Disease Complication among Hypertensive Outpatients Treated at Debretabor Hospital, Ethiopia

Hirbo,

Kuse,

Hola

et al. 2023

Preprint

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The objective of the study was to identify factors that affect longitudinal outcomes and survival time to cardiovascular disease complications among hypertension outpatients. A retrospective study design was conducted on a cohort of 178 randomly selected hypertensive outpatients at Debre Tabor Hospital under a follow-up period from September 2017 to December 2019. To analyze the data, the study used three different models namely: the bivariate mixed-effects model, cox-proportional hazard model, and bivariate joint model for longitudinal and survival sub-model linked by shared random effects. The bivariate mixed-effects and a cox proportional hazards survival sub-model jointly were preferred based on the minimum Akaike Information Criterion value. The estimated values of the association parameters were 0.0655(p-value = 0.0270), and 0.963(p-value = 0.0387) that the association of systolic blood pressure, and diastolic blood pressure with time to event is guaranteed. The joint bivariate mixed-effects model analysis shows that hypertension outpatients with a family history of hypertension and clinical stage II hypertension have a high chance of developing cardiovascular disease complications and have high average systolic blood pressure and diastolic blood pressure compared to their counter groups. Hypertension outpatients with diabetes have high systolic blood pressure and diastolic blood pressure compared to their counter groups. Generally, systolic blood pressure and diastolic blood pressure became stable over the follow-up time of treatment while adherence for developed cardiovascular disease complications was statistically insignificant. Health professionals and concerned bodies should therefore focus on outpatients with comorbidity, aged and poor adherence patients to control hypertension and cardiovascular disease complications. Paying attention to treatment time to stable progression of systolic blood pressure and diastolic blood pressure of patients is also recommended.

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Section: Discussionsupporting

confidence: 91%

Joint Modeling of Longitudinal Measurements and Survival Time to Cardiovascular Disease Complication among Hypertensive Outpatients Treated at Debretabor Hospital, Ethiopia

Hirbo,

Kuse,

Hola

et al. 2023

Preprint

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“…Related disease is another prognostic factor that signi cantly predicts the recovery time of patients with hypertension. It showed that patients having kidney disease, other and have no related disease shortened the recovery time compared to diabetes patients; this study is supported by the study [14].…”

Section: Discussionsupporting

confidence: 80%

Determinants of time-to-recovery from hypertension by application of Weibull-Inverse Gaussian shared frailty model

Yihuna

Takele²,

Muluneh³

2023

Preprint

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Hypertension is a major public health problem that is responsible for morbidity and mortality. In Ethiopia hypertension is becoming a double burden due to urbanization. The aim of the study is to identify factors that affect time-to-recovery from hypertension. In this study, a retrospective study design was used and the data was collected in the patient’s chart from September 2016 to January 2018. Accelerated failure time, and parametric shared frailty models were employed to identify factors associated with the recovery time of hypertension patients. Eighty one percent of sampled patients were recovered to normal condition and nineteen percent of patients were censored observations. The median survival time of hypertensive patients to attain normal condition was 13 months. Weibull- inverse Gaussian shared frailty model which was found to be the best model for predicting recovery time of hypertension patients. Unobserved heterogeneity in residences as estimated by the Weibull-Inverse Gaussian shared frailty model was θ = 0.385 (p-value = 0.00). Predictor age, systolic blood pressure, related disease, creatine, blood urea nitrogen, and the interaction between blood urea nitrogen and age were the determinant factors of the recovery status of patients. Therefore, health-care providers give great attention and priorities those identified factors and forward frequent counseling about reducing hypertension disease.

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“…According to the results of the study conducted at Jimma University Specialized Hospital, Ethiopia, there was a high correlation between BPs evolution and the association of evolution approximates one [ 2 , 31 ]. The evolution of association between the BPs at the baseline was 0.260 and has a slight increment as time changes, this is also supported by a study FHRH, Bahir Dar, Ethiopia [ 10 ]. In the multivariate longitudinal sub-model; the observation time was negatively associated with the average SBP and DBP, that is, as the observation time increases patient’s average SBP and DBP had increased proportionately.…”

Section: Discussionsupporting

confidence: 74%

“…Following therapy modifications over time, the average systolic and diastolic blood pressure biomarkers of hypertensive patients were primarily reported [ 9 ]. A separate longitudinal study conducted by [ 10 ] aims to assess the trends of systolic and diastolic BP over time using a bivariate linear mixed model.…”

Section: Introductionmentioning

confidence: 99%

Joint modeling of longitudinal changes of blood pressure and time to remission of hypertensive patients receiving treatment: Bayesian approach

Getaneh¹,

Tesfaw

Dessie

et al. 2023

PLoS ONE

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Introduction Hypertension is a widespread condition when the blood’s force on the artery walls is extremely high to develop adverse health effects. This paper aimed to jointly model the longitudinal change of blood pressures (systolic and diastolic) and time to the first remission of hypertensive outpatients receiving treatment. Methods A retrospective study design was used to collect appropriate data on longitudinal changes in blood pressure and time-to-event from the medical charts of 301 hypertensive outpatients under follow-up at Felege Hiwot referral hospital, Ethiopia. The data exploration was done using summary statistics measures, individual profile plots, Kaplan-Meier plots, and log-rank tests. To get wide-ranging information about the progression, joint multivariate models were employed. Results A total of 301 hypertensive patients who take treatment was taken from Felege Hiwot referral hospital recorded between Sep. 2018 to Feb. 2021. Of this 153 (50.8%) were male, and 124 (49.2%) were residents from rural areas. About 83(27.6%), 58 (19.3%), 82 (27.2%), and 25 (8.3%) have a history of diabetes mellitus, cardiovascular disease, stroke, and HIV respectively. The median time of hypertensive patients to have first remission time was 11 months. The hazard of the patient’s first remission time for males was 0.63 times less likely than the hazard for females. The time to attain the first remission for patients who had a history of diabetes mellitus was 46% lower than for those who had no history of diabetes mellitus. Conclusion Blood pressure dynamics significantly affect the time to the first remission of hypertensive outpatients receiving treatment. The patients who had a good follow-up, lower BUN, lower serum calcium, lower serum sodium, lower hemoglobin, and take the treatment enalapril showed an opportunity in decreasing their blood pressure. This compels patients to experience the first remission early. Besides, age, patient’s history of diabetes, patient’s history of cardiovascular disease, and treatment type were the joint determinant factors for the longitudinal change of BP and the first remission time. The Bayesian joint model approach provides specific dynamic predictions, wide-ranging information about the disease transitions, and better knowledge of disease etiology.

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Bivariate longitudinal data analysis: a case of hypertensive patients at Felege Hiwot Referral Hospital, Bahir Dar, Ethiopia

Cited by 9 publications

References 24 publications

Joint Modeling of Longitudinal Measurements and Survival Time to Cardiovascular Disease Complication among Hypertensive Outpatients Treated at Debretabor Hospital, Ethiopia

Joint Modeling of Longitudinal Measurements and Survival Time to Cardiovascular Disease Complication among Hypertensive Outpatients Treated at Debretabor Hospital, Ethiopia

Determinants of time-to-recovery from hypertension by application of Weibull-Inverse Gaussian shared frailty model

Joint modeling of longitudinal changes of blood pressure and time to remission of hypertensive patients receiving treatment: Bayesian approach

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