Risk Management and Healthcare Policy (Nov 2022)

Dynamic Trajectory of a Patient-Reported Outcome and Its Associated Factors for Patients with Chronic Heart Failure: A Growth Mixture Model Approach

  • Tian J,
  • Ding F,
  • Wang R,
  • Han G,
  • Yan J,
  • Yuan N,
  • Du Y,
  • Han Q,
  • Zhang Y

Journal volume & issue
Vol. Volume 15
pp. 2083 – 2096

Abstract

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Jing Tian,1,2 Fengqin Ding,3 Ruoya Wang,3 Gangfei Han,1 Jingjing Yan,3 Na Yuan,3 Yutao Du,3 Qinghua Han,1 Yanbo Zhang2– 4 1Department of Cardiology, the 1st Hospital of Shanxi Medical University, Taiyuan, People’s Republic of China; 2Shanxi Provincial Key Laboratory of Major Diseases Risk Assessment, Taiyuan, People’s Republic of China; 3Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, People’s Republic of China; 4Shanxi University of Chinese Medicine, Jinzhong, People’s Republic of ChinaCorrespondence: Yanbo Zhang, Department of Health Statistics, School of Public Health, Shanxi Medical University, Taiyuan, People’s Republic of China, Tel +86 3327518812, Email [email protected] Correspondence: Qinghua Han, Department of Cardiology, the 1st Hospital of Shanxi Medical University, Taiyuan, People’s Republic of China, Tel +86 3100113031, Email [email protected]: This study aimed to identify subgroups of chronic heart failure (CHF) patients with distinct trajectories of quality of life (QOL) and to identify baseline characteristics associated with the trajectories.Patients and methods: Two-year, prospective, cohort study including 315 patients with CHF was conducted from July 2017. Information on QOL assessed by CHF-patient-reported outcomes measure (CHF-PROM) was collected at baseline, 6, 12, 18, and 24 months. Demographic and clinical variables were recorded at baseline. Growth mixture model was used to identify distinct trajectories of CHF-PROM and its physical, psychological, social, and therapeutic domains. Single factor analysis was employed to assess the factors associated with development of CHF-PROM over time.Results: Two classes of overall score of CHF-PROM were identified: poorer (14.0%) and better (86.0%). Poorer class tended to be aged, have low diastolic blood pressure, have concomitant atrial fibrillation, diabetes, chronic obstructive pulmonary disease, cancers, and central nervous system diseases, and used nitrates. Three classes of physical scores were identified: unstable-poorer (5.2%), stable-poorer (29.4%) and better (65.4%). Age, NYHA grade, chronic obstructive pulmonary disease, combined with cancers and central nervous system diseases were related to the grouping. Poorer (8.6%) and better (91.4%) classes of psychological scores were identified. Poorer class tended to be female and had concomitant atrial fibrillation. Degenerate class (34.6%) and meliorate class (65.4%) of therapeutic scores were identified. Degenerate class tended to have concomitant chronic obstructive pulmonary disease and use less angiotensin converting enzyme inhibitors.Conclusion: We identified different classes with distinct trajectories of QOL that may help proper evaluate QOL and further improve its status for patients CHF.Keywords: patient-reported outcome, chronic heart failure, growth mixture model, dynamic trajectory

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