Interdisciplinary Program in Bioengineering, Seoul National University Graduate School, Seoul, Korea.
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.
Comput Methods Programs Biomed. 2017 Jul;145:35-43. doi: 10.1016/j.cmpb.2017.04.003. Epub 2017 Apr 8.
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).
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).
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.
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.
尽管已经引入了新的模式，但传统的血液透析（HD）方案已经使用了几十年。许多因素限制了频繁透析的实践，例如患者的环境和每个患者的最佳方案未知。本研究通过遗传算法（GA）为 HD 方案提供了理论建议。
通过经典的变容两室动力学模型对各种透析条件的终末期肾病（ESRD）进行建模，以模拟无尿患者，并实施 GA 为每个个体搜索最佳 HD 方案，同时考虑和忽略每个透析疗程的负担消耗。通过时间平均浓度（TAC）和时间平均偏差（TAD）评估通过 GA 优化的 HD 方案的充分性。
在忽略透析疗程负担的情况下，GA 返回的方案与常规定期均匀 HD 方案相比，适当性标准（EKRc 和 std Kt/V）略有改善。与常规定期均匀 HD 方案相比，优化的 HD 方案也显示出 TAC 和 TAD 值降低。这表明频繁透析会带来更有效的治疗和更高的适应度值。然而，当考虑到负担时，较少的透析方案显示出更好的适应性值。
通过这项研究，GA 证实每周至少应进行 12 小时的透析。GA 生成的优化方案表明，在疗程之间均匀分配间隔是有效的，并且在一周的开始和结束时安排一次疗程是克服长周末间隔的最佳选择。HD 的理论最佳方案可能有助于频繁透析的分配，并为患者提供更多的方案选择。
