ArticleBMC nephrology2025
Management of volume load for patients undergoing hemodialysis via WeChat and home monitoring in China: a protocol for a cluster-randomized trial.
Article in BMC nephrology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06333574 (Clinical Randomized Controlled Trial of Weight Intervention to Improve Volumetric Load in Hemodialysis Patients), which is not on this map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Clinical Randomized Controlled Trial of Weight Intervention to Improve Volumetric Load in Hemodialysis Patients
Who cites it
3 citing papers in PubMed.
- WeChat-assisted strategies for personalized health management in patients with AECOPD: A randomized controlled trial.PloS one · 2025Trial
- Effectiveness of a New Media Health Education Program in Patients with Chronic Kidney Disease.Patient preference and adherence · 2026Article
- Development and validation of a nomogram for predicting calcification of arteriovenous access in hemodialysis patients.Renal failure · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVolume overload is a major mortality risk in hemodialysis (HD) patients. Drug therapy and conventional dialysis limitations underscore the importance of managing volume load through effective lifestyle interventions. In this regard, WeChat, along with its built-in self-monitoring function, has demonstrated considerable potential for application. WeChat, a versatile social media platform in China, integrating Facebook, WhatsApp, Twitter, and PayPal functionalities, shows potential in managing volume load, especially when paired with home monitoring. This method may also reduce adverse events and improve patient outcomes.
methodThe study will be conducted at the Hemodialysis Center of the Hospital of Chengdu University of Traditional Chinese Medicine, recruiting 135 participants. All patients will be cluster randomly assigned to three group according to their HD schedules. The control group will receive standard care. The WeChat group will receive volume load management via WeChat message in addition to standard care. The home monitoring-feedback group will be required to monitor their blood pressure and weight at home, and upload the number to WeChat subscription account "Health Dialysis" in addition to standard care and volume load management via WeChat message. Data will be collected during the baseline period, one, two, and three months after the intervention starts, and three months after the intervention ends to evaluate the effectiveness of this intervention measure. DISCUSSION: This study aims to effectively manage the volume load of HD patients and enhance their quality of life through a combination of intervention methods utilizing the WeChat platform and home monitoring. If this intervention measure proves effective, it will not only provide empirical evidence for managing HD patients through the WeChat platform but also serve as a reference model for other HD centers in addressing patient volume load issues. What's more, if significant differences are observed between the results of the WeChat groups and the home monitoring-feedback group, this will further substantiate the importance and impact of home monitoring in volume load management.
trial registrationClinicalTrials.gov (NCT06333574). Registered 13 March 2024.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.