Prevalence of depression and its association with quality of life in patients after pacemaker implantation during the COVID-19 pandemic: A network analysis

• Type of Material: Article
• Authors: Yun Lin, Capital Medical University; Hong Cai, University of Macau; Hong-Hong Liu, Capital Medical University; Xue-Jian Su, Capital Medical University; Chen-Yu Zhou, Capital Medical University; Jing Li, Capital Medical University; Yilang Tang, Emory University; Todd Jackson, University of Macau; Yu-Tao Xiang, University of Macau
• Language: English
• Date: 2023-03-16
• Publisher: FRONTIERS MEDIA SA
• Publication Version: Final Published Version
• Copyright Statement: © 2023 Lin, Cai, Liu, Su, Zhou, Li, Tang, Jackson and Xiang.
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.3389/fpsyt.2023.1084792
• Title of Journal or Parent Work: FRONTIERS IN PSYCHIATRY
• Volume: 14
• Start Page: 1084792
• End Page: 1084792
• Grant/Funding Information: This study was supported by the National Science and Technology Major Project for Investigations of New Drugs (2018ZX09201-014), the Beijing Municipal Science & Technology Commission (no. Z181100001518005), and the University of Macau (MYRG2019-00066-FHS; MYRG2022-00187-FHS).
• Keywords: network analysis; Science & Technology; ANXIETY; COMMUNITY; SYMPTOMS; HEALTH; EXPERIENCES; DISORDER; Psychiatry; pacemaker implantation; depression; COVID-19; quality of life; CARDIOVERTER-DEFIBRILLATOR; Life Sciences & Biomedicine; DISEASE; CHINA; OLDER-ADULTS
• Research Categories: Health Sciences, Mental Health

Abstract

Background: This study was designed to investigate the prevalence and predictors of depression in patients after pacemaker implantation during the COVID-19 pandemic in addition to identifying specific depressive symptoms associated with quality of life (QOL) using network analysis (NA). Methods: This cross-sectional, observational study was conducted in China between July 1, 2021, and May 17, 2022. Descriptive analysis was used to calculate depression prevalence. Univariate analyses were used to compare differences in demographic and clinical characteristics between depressed and non-depressed patients following pacemaker implantation. Binary logistic regression analysis was used to assess factors independently associated with depression. Network analysis “expected influence,” and flow function indexes were used to identify symptoms central to the depression network of the sample and depressive symptoms that were directly associated with QOL, respectively. Network stability was examined using a case-dropping bootstrap procedure. Results: In total, 206 patients implanted with a pacemaker met the study entry criteria and completed the assessment. The overall prevalence of depression (PHQ-9 total score ≥ 5) was 39.92% [95% confidence interval (CI) = 29.37−42.47%]. A binary logistic regression analysis revealed that patients with depression were more likely to report a poor health status (p = 0.031), severe anxiety symptoms (p < 0.001), and fatigue (p < 0.001). In the network model for depression, “Sad mood,” “Poor Energy,” and “Guilt” were the most influential symptoms. “Fatigue” had the strongest negative association with QOL, followed by “Sad mood” and “Appetite”. Conclusion: Depression is common among patients having undergone pacemaker implantation during the COVID-19 pandemic. Anxiety, central symptoms of depression (i.e., “Sad mood”, “Poor Energy”, and “Guilt”) and depressive symptoms linked to QOL (i.e., “Sad mood”, “Appetite”, and “Fatigue”) identified in this study are promising targets for interventions and preventive measures for depression in patients who have undergone pacemaker implants.