Real-world evaluation of arrhythmias detection in hemodialysis patients using wearable electrocardiogram monitor: a two-phase multicenter observational study
Arrhythmia is a common and clinically relevant complication among patients with chronic kidney disease (CKD) undergoing hemodialysis (HD), contributing to adverse cardiovascular outcomes. We hypothesized that wearable electrocardiogram (ECG) monitors, being more patient-acceptable than standard ECG devices, could facilitate the detection of arrhythmias, including asymptomatic cases, in HD patients. This two-phase real-world observational study enrolled CKD patients undergoing maintenance HD. In Phase I, we assessed the wearable single-lead ECG monitors with comparison to standard 12-lead Holter monitoring for detecting arrhythmias and measuring heart rate variability (HRV). In Phase II, we used the wearable ECG monitors to investigate the prevalence of arrhythmias during HD. Additionally, LASSO logistic regression was conducted to identify subgroups of patients most likely to benefit from wearable devices. This study enrolled 538 patients from five hospitals. In Phase I (n = 185), we found that the wearable ECG enabled continuous monitoring of arrhythmias and HRV in patients undergoing HD. Linear regression revealed a significant correlation of parameters of HRV, including SDNN, SDANN, and pNN50 between the wearable ECG and the standard Holter monitoring (p < 0.001). LASSO logistic regression model identified the older patients (age ≥ 50) would benefit more from the usage of wearable devices than the younger. In Phase II, arrhythmias were detected in 34.0% of the HD population, with 80.8% of cases being asymptomatic. This study confirmed the efficacy of wearable devices to detect arrhythmia and evaluate HRV in HD patients. The high prevalence of asymptomatic arrhythmias underscores the clinical value of using convenient wearable devices in this population. Cardiovascular disease is the main cause of hospitalization and death for hemodialysis (HD) patients, accounting for nearly 40% of the total mortality rate, and US Renal Data System database shows two thirds of cardiac deaths are attributed to arrhythmia. Precise monitoring of heart rhythm abnormalities in chronic kidney disease (CKD) patients is of great significance in reducing serious cardiovascular events. The study validated the feasibility and effectiveness of the wearable device in detecting arrhythmias during dialysis in HD patients, and advanced age is a factor associated with increased likelihood of benefiting from wearable devices. Moreover, asymptomatic arrhythmia was found highly prevalent, emphasizing the paramount role of wearable device during HD. Our study promote a more patient-friendly solution to identify arrhythmias and real-time monitor the cardiovascular and electrolyte parameters in CKD patients during HD therapy, thereby aiding patients in self-management of their health and potentially enhancing both their survival rates and quality of life.
Authors
- Li Jin Huang
- Zhengyi Zhu (ORCID: https://orcid.org/0000-0003-1166-426X)
- Tristan D. Yan (ORCID: https://orcid.org/0000-0002-7473-1522)
- Shaobin Yu (ORCID: https://orcid.org/0000-0001-7074-7458)
- Xiaoxi Zeng (ORCID: https://orcid.org/0000-0001-9946-4291)
- Gang Liu (ORCID: https://orcid.org/0000-0002-2594-6383)
- Ping Fu
- Qi Mei (ORCID: https://orcid.org/0000-0002-9826-5044)
- De-zheng Chen
- Hu Ma (ORCID: https://orcid.org/0000-0003-1654-1576)
Institutions
- Sichuan University (CN)
- West China Medical Center of Sichuan University (CN)
- Meizhou City People's Hospital (CN)
- West China Hospital of Sichuan University (CN)
- Fuyang City People's Hospital (CN)
- Tibet Autonomous Region People's Hospital (CN)
- First People's Hospital of Nanning (CN)
Publication Details
- Journal
- BMC Nephrology
- Published
- 2025-10-14
- DOI
- https://doi.org/10.1186/s12882-025-04489-2
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Sichuan University
- Chengdu Science and Technology Bureau
- West China Hospital, Sichuan University