Progression of Chronic Kidney Disease Among Older Adults with Hypertension Using Group-Based Trajectory Modeling
Author(s)
Gupta AK1, Goswami S1, Vivek V1, Sharma M1, Aparasu RR2
1Complete HEOR Solutions (CHEORS), Chalfont, PA, USA, 2University of Houston, College of Pharmacy, Houston, TX, USA
OBJECTIVES: Hypertension significantly elevates the risk for chronic kidney disease (CKD) among older adults. This study aimed to assess the trajectories of CKD progression among older adults with CKD and hypertension.
METHODS: This was a retrospective, US-based longitudinal cohort study using data from the Health and Retirement Study (HRS) from 2008 to 2016. Patients included those ≥50 years old with estimated glomerular filtration rate (eGFR) <90 mL/min/1.73 m2 in 2008 and having comorbid hypertension. Changes in eGFR in the eight-year follow-up period were assessed and groups with distinct patterns of progression were identified using group-based trajectory modeling (GBTM). The number of disease progression groups to capture the dynamics of disease trajectory was determined based on considerations of Log-Likelihood, Akaike Information Criterion, Bayesian Information Criterion, and Entropy.
RESULTS: A total of 814 participants were included (mean age: 70.79 years, 63.03% females, mean eGFR: 60.96 mL/min/1.73 m2). The GBTM identified three trajectory groups: “severely impaired kidney function” (n=267, 32.80%) “declining kidney function” (n=444, 54.55%), and improved kidney function” (n=103, 12.65%). The mean baseline eGFRs of the three identified groups was 42.49, 68.45, and 76.52 mL/min/1.73 m2, respectively. The mean age of participants in the three groups was 76.51, 69.37, and 62.12 years, respectively. The baseline mean systolic blood pressure for the three groups was 138.51, 137.92, and 132.66, respectively. The prediabetes prevalence during baseline in the three groups was 35.41%, 32.29%, and 27.54%, respectively.
CONCLUSIONS: This study provides valuable insights into the diverse trajectories of CKD progression among individuals with comorbid hypertension with significant differences in clinical characteristics of the three groups. The findings may have important implications for targeted interventions and personalized management strategies in this high-risk population.
Conference/Value in Health Info
Value in Health, Volume 27, Issue 6, S1 (June 2024)
Code
CO49
Topic
Clinical Outcomes, Epidemiology & Public Health, Methodological & Statistical Research, Study Approaches
Topic Subcategory
Artificial Intelligence, Machine Learning, Predictive Analytics, Clinical Outcomes Assessment, Surveys & Expert Panels
Disease
Cardiovascular Disorders (including MI, Stroke, Circulatory), Urinary/Kidney Disorders