Karimi, M., Dideban, D. and Heidari, H. (2022) Using the intelligent system to improve the delivered adequacy of dialysis by preventing intradialytic complications. Journal of Healthcare Engineering, 2022, 8160269. (doi: 10.1155/2022/8160269) (PMID:35783584) (PMCID:PMC9246598)
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Abstract
Acute kidney failure patients while detoxificated by hemodialysis (HD) mostly or continuously faced regular problems such as low blood pressure (hypotension), muscle cramps, nausea, or vomiting. Higher intradialytic symptom leads to low-quality HD treatment. Although more known therapeutic interventions are used to relieve the HD side effects, this study was designed to investigate how intelligent systems can make highly beneficial alterations in dialysis facilities and equipment to ease intradialytic complications and help the staff deliver high-quality treatment. A search was performed among relevant research articles based on nonpharmacological intervention methods considered to prevent adverse effects of renal replacement therapy until 2020 in the PubMed databases using the terms “intradialytic complications,” “intradialytic complication interventions,” “nonpharmacological interventions,” “intradialytic exercises,” and “adequacy calculation methods.” Studies included the prevalence of intradialytic complications, different strategies with the aim of preventing complications, the outcome of intradialytic exercises on dialysis symptoms, and dialysis dose calculation methods. The results showed the incidence of hypotension varying between 5% and 30%, fatigue, muscular cramps, and vomiting as the most common complications during dialysis, which greatly affect the outcome of HD sessions. To prevent hypotension, ultrafiltration profiling, sodium modeling, low dialysate temperature, and changing the position to Trendelenburg are some strategies. Urea reduction ratio (URR), formal urea kinetic modeling (FUKM), formal single-pool urea kinetics, and online clearance monitoring (OCM) are methods for calculating the delivered dose of dialysis in which OCM is a low-cost and accessible way to monitor regularly the quality of dialysis delivered. Integration of the chair and HD machine which is in direct contact with the patient provides an intelligent system that improves the management of the dialysis session to enhance the quality of healthcare service.
| Item Type: | Articles |
|---|---|
| Additional Information: | (is work was supported by the University of Kashan, Iran (1073372), and by Microelectronics Lab (meLab) through the University of Glasgow, United Kingdom (EPSRC IAA EP/R511705/1). |
| Keywords: | Health Informatics, Biomedical Engineering, Surgery, Biotechnology |
| Status: | Published |
| Refereed: | Yes |
| Glasgow Author(s) Enlighten ID: | Heidari, Professor Hadi |
| Authors: | Karimi, M., Dideban, D., and Heidari, H. |
| College/School: | College of Science and Engineering > School of Engineering > Electronics and Nanoscale Engineering |
| Journal Name: | Journal of Healthcare Engineering |
| Publisher: | Hindawi |
| ISSN: | 2040-2295 |
| ISSN (Online): | 2040-2309 |
| Published Online: | 23 June 2022 |
| Copyright Holders: | Copyright © 2022 Mohammad Karimi et al |
| First Published: | First published in Journal of Healthcare Engineering 2022: 81606269 |
| Publisher Policy: | Reproduced under a Creative Commons License |
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