ArticlePilot and feasibility studies2022
Protocol of a pilot-scale, single-arm, observational study to assess the utility and acceptability of a wearable hydration monitor in haemodialysis patients.
Article in Pilot and feasibility studies, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04623281 (Haemodialysis Outcomes & Patient Empowerment Study 02), which is not on this map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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.
Haemodialysis Outcomes & Patient Empowerment Study 02
Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Impact of digital health technology-based nutritional interventions on the nutritional status of hemodialysis patients: a systematic review and meta-analysis.Frontiers in nutrition · 2025Pooled it
- Recent Advancements in Wearable Hydration-Monitoring Technologies: Scoping Review of Sensors, Trends, and Future Directions.JMIR mHealth and uHealth · 2025Article
- Digital symptom management interventions for people with chronic kidney disease: a scoping review based on the UK Medical Research Council Framework.BMC public health · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
backgroundFluid overload has a high prevalence in haemodialysis patients and is an important risk factor for excess mortality and hospitalisations. Despite the risks associated with chronic fluid overload, it is clinically difficult to assess and maintain fluid status adequately. Current methods of fluid status assessment are either imprecise or time intensive. In particular, to date, no method exists to accurately assess fluid status during the interdialytic interval.
objectivesThis pilot study aimed to evaluate whether a prototype wearable hydration monitor can accurately and reproducibly detect fluid overload in the haemodialysis population when compared to haemodialysis and bioimpedance data.
methodsA prospective, open-label, single-arm observational trial of 20 patients commenced in January 2021 in a single haemodialysis centre in Ireland, with a wearable hydration monitor, the Sixty device. The Sixty device uses diffuse reflectance spectroscopy to measure fluid levels at the level of the subdermis and uses machine learning to develop an algorithm that can determine fluid status. The Sixty device was worn at every dialysis session and nocturnally over a three-week observational period. Haemodialysis parameters including interdialytic weight gain, ultrafiltration volume, blood pressure, and relative blood volume were collected from each session, and bioimpedance measurements using the Fresenius body composition monitor were performed on 4 occasions as a comparator. The primary objective of this trial was to determine the accuracy and reproducibility of the Sixty device compared to bioimpedance measurements.
conclusionIf the accuracy of the wearable hydration monitor is validated, further studies will be conducted to integrate the device output into a multi-parameter machine learning algorithm that can provide patients with actionable insights to manage fluid overload in the interdialytic period.
trial registrationwww.clinicaltrials.gov NCT04623281 . Registered November 10th, 2020.
Identifiers
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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.