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Choi JW, Lee H, Lee JC, Lee S, Kim YS, Yoon HJ, Kim HC. Application of genetic algorithm for hemodialysis schedule optimization. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2017; 145:35-43. [PMID: 28552124 DOI: 10.1016/j.cmpb.2017.04.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2016] [Revised: 04/03/2017] [Accepted: 04/07/2017] [Indexed: 06/07/2023]
Abstract
BACKGROUND The conventional hemodialysis (HD) schedule has been used for decades, even though new modalities have been introduced. Many reasons limit practices of frequent dialysis, such as patients' environments and unknown optimal schedules for each patient. This research provides a theoretical recommendation of HD schedule through genetic algorithm (GA). METHODS An end-stage renal disease (ESRD) with various dialysis conditions was modeled through a classic variable-volume two-compartment kinetic model to simulate an anuric patient, and GA was implemented to search for an optimal HD schedule for each individual considering and ignoring burden consumption of each dialysis session. The adequacy of the optimized HD schedules through GA was assessed with time average concentration (TAC) and time average deviation (TAD). RESULTS While ignoring the burden of dialysis sessions, GA returned schedules with slightly improved values of adequacy criteria (EKRc and std Kt/V), compared to the conventional regular uniform HD schedules. The optimized HD schedules also showed decreased TAC and TAD values compared to the conventional regular uniform HD schedules. It showed that frequent dialysis resulted in more effective treatment and higher fitness values. However, when burden was considered, less frequent dialysis schedules showed better fitness value. CONCLUSIONS Through this research, GA confirmed that at least 12h of dialysis should be conducted for a week. The optimized schedules from GA indicated that evenly distributing the intervals amongst sessions is efficient, and that scheduling a session at the start and end of a week is optimal to overcome a long weekend interval. The theoretical optimal schedule of HD may help distribution of frequent dialysis and provide more schedule options to patients.
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Affiliation(s)
- Jin Woo Choi
- Interdisciplinary Program in Bioengineering, Seoul National University Graduate School, Seoul, Korea
| | - Hajeong Lee
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea; Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea; Kidney Research Institute, Medical Research Center, Seoul National University, Seoul, Korea
| | - Jung Chan Lee
- Department of Biomedical Engineering, Seoul National University Hospital, Seoul, Korea; Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Korea; Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul, Korea.
| | - Saram Lee
- Biomedical Research Institute, Seoul National University Hospital, Seoul, Korea
| | - Yon Su Kim
- Department of Internal Medicine, Seoul National University Hospital, Seoul, Korea; Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea; Kidney Research Institute, Medical Research Center, Seoul National University, Seoul, Korea
| | - Hyung-Jin Yoon
- Department of Biomedical Engineering, Seoul National University Hospital, Seoul, Korea; Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Korea; Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul, Korea
| | - Hee Chan Kim
- Department of Biomedical Engineering, Seoul National University Hospital, Seoul, Korea; Department of Biomedical Engineering, Seoul National University College of Medicine, Seoul, Korea; Institute of Medical and Biological Engineering, Medical Research Center, Seoul National University, Seoul, Korea
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