Joint Modeling of Longitudinal Pulse Rate and Time-to-Default from Treatment of Congestive Heart Failure Patients

Abebaw, Yikeber; Mohammed, Kasim; Aragaw, Adem; Melese, Bezanesh

doi:10.2147/rrcc.s326229

Cited by 2 publications

(2 citation statements)

References 20 publications

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“…The goal of treatment for heart failure patients includes reducing symptoms and disease progression, prolonging survival, and improving quality of life. However, in Ethiopia, heart failure patent came after NYHA Class III and IV with limited knowledge about their disease, poor medication adherence practice, and transitional care (13)(14)(15). Furthermore, risky lifestyles such as smoking, a sedentary lifestyle, excessive salt intake, and alcohol consumption are most common in Ethiopia, which are predictors of unplanned hospitalizations for HF patients (16,17).…”

Section: Introductionmentioning

confidence: 99%

Unplanned readmission to hospital and its predictors in heart failure patients, Ethiopia: a retrospective cohort study

Anleye

Kumar

Endris

2022

Preprint

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Background: The burden of heart failure increases over time and is a leading cause of unplanned readmissions worldwide. In addition, its impact has doubled in countries with limited health resources, including Ethiopia. Identifying and preventing the possible contributing factors is crucial to reduce unplanned hospital readmission and to improve clinical outcomes. Method: A hospital-based retrospective cohort study design was employed from January 1, 2016, to December 30, 2020. The data was collected from 572 randomly selected medical records using data extraction checklists. Data were entered in Epi-data version 4.6 and analyzed with Stata version 17. The Kaplan-Meier and log-rank tests were used to estimate and compare the survival failure time. A Cox proportional hazard analysis was computed to identify predictors of readmission. Finally, the statistical significance level was declared at a p-value <0.05 with an adjusted odds ratio and a 95% confidence interval. Result: In this study, a total of 151 (26.40%) heart failure patients were readmitted within 30 days of discharge. In the multivariate cox proportional hazards analysis being an age (>65 years) (AHR: 3.172, 95%CI:.21, 4.55), rural in residency (AHR: 2.47, 95%CI: 1.44, 4.24), Asthma/COPD (AHR: 1.62, 95%CI: 1.11, 2.35), HIV/AIDS (AHR: 1.84, 95%CI: 1.24, 2.75), Haemoglobin level 8-10.9 g/dL (AHR: 6.20, 95%CI: 3.74, 10.28), and Mean platelet volume >9.1fl (AHR: 2.08, 95%CI: 1.27, 3.40) were identified as independent predictors of unplanned hospital readmission. Conclusion: The incidence of unplanned hospital readmission was relatively high among heart failure patients. Elderly patients, rural residency, comorbidity, higher mean platelet volume, and low hemoglobin level were independent predictors of readmission. Therefore, working on these factors will help to reduce the hazard of unplanned hospital readmission.

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Section: Introductionmentioning

confidence: 99%

Unplanned readmission to hospital and its predictors in heart failure patients, Ethiopia: a retrospective cohort study

Anleye

Kumar

Endris

2022

Preprint

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“…Other key biomarkers which appeared in multiple studies were High sensitivity Troponin T (HsTnT), C-Reactive Protein (CRP), Cancer Antigen 125 (CA125), creatinine, Suppression of Tumorigenicity 2 (ST2), Galectin-3 (GAL-3) and Growth Differentiation Factor 15 (GDF-15) [ 22 , 27 , 33 – 35 , 37 , 41 , 42 ], indicating that repeat measures of these markers are of interest within heart failure populations. Additionally, other less frequent markers included lactase dehydrogenase trends (LDH) [ 30 ], Red blood cell Distribution Width (RDW) [ 17 ] and ambulatory markers such as Systolic Blood Pressure (SBP), heart rate and haemoglobin [ 18 , 21 , 27 ].…”

Section: Resultsmentioning

confidence: 99%

Joint modelling of longitudinal processes and time-to-event outcomes in heart failure: systematic review and exemplar examining the relationship between serum digoxin levels and mortality

Field

Adamson

Jhund

et al. 2023

BMC Med Res Methodol

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Background Joint modelling combines two or more statistical models to reduce bias and increase efficiency. As the use of joint modelling increases it is important to understand how and why it is being applied to heart failure research. Methods A systematic review of major medical databases of studies which used joint modelling within heart failure alongside an exemplar; joint modelling repeat measurements of serum digoxin with all-cause mortality using data from the Effect of Digoxin on Mortality and Morbidity in Patients with Heart Failure (DIG) trial. Results Overall, 28 studies were included that used joint models, 25 (89%) used data from cohort studies, the remaining 3 (11%) using data from clinical trials. 21 (75%) of the studies used biomarkers and the remaining studies used imaging parameters and functional parameters. The exemplar findings show that a per unit increase of square root serum digoxin is associated with the hazard of all-cause mortality increasing by 1.77 (1.34–2.33) times when adjusting for clinically relevant covariates. Conclusion Recently, there has been a rise in publications of joint modelling being applied to heart failure. Where appropriate, joint models should be preferred over traditional models allowing for the inclusion of repeated measures while accounting for the biological nature of biomarkers and measurement error.

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Joint Modeling of Longitudinal Pulse Rate and Time-to-Default from Treatment of Congestive Heart Failure Patients

Cited by 2 publications

References 20 publications

Unplanned readmission to hospital and its predictors in heart failure patients, Ethiopia: a retrospective cohort study

Unplanned readmission to hospital and its predictors in heart failure patients, Ethiopia: a retrospective cohort study

Joint modelling of longitudinal processes and time-to-event outcomes in heart failure: systematic review and exemplar examining the relationship between serum digoxin levels and mortality

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