Computational modeling of peritoneal dialysis: An overview
Peritoneal dialysis (PD) is a kidney replacement therapy for patients with end-stage renal disease. It is becoming more popular as a result of a rising interest in home dialysis. Its effectiveness depends on several physiological and technical factors, which have led to the development of various co...
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| Format: | Article |
| Language: | English |
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AIMS Press
2025-02-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2025017 |
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| author | Sangita Swapnasrita Joost C de Vries Carl M. Öberg Aurélie MF Carlier Karin GF Gerritsen |
| author_facet | Sangita Swapnasrita Joost C de Vries Carl M. Öberg Aurélie MF Carlier Karin GF Gerritsen |
| author_sort | Sangita Swapnasrita |
| collection | DOAJ |
| description | Peritoneal dialysis (PD) is a kidney replacement therapy for patients with end-stage renal disease. It is becoming more popular as a result of a rising interest in home dialysis. Its effectiveness depends on several physiological and technical factors, which have led to the development of various computational models to better understand and predict PD outcomes. In this review, we traced the evolution of computational PD models, discussed the principles underlying these models, including the transport kinetics of solutes, the fluid dynamics within the peritoneal cavity, and the peritoneal membrane properties, and reviewed the various PD models that can be used to optimize and personalize PD treatment. By providing a comprehensive overview, we aim to guide both current clinical practice and future research into novel PD techniques such as the application of continuous flow and sorbent-based dialysate regeneration where mathematical modeling may offer an inexpensive and effective tool to optimize design of these novel techniques at a patient specific level. |
| format | Article |
| id | doaj-art-a58e33c5934b43869bfbe7e220d24d1f |
| institution | DOAJ |
| issn | 1551-0018 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-a58e33c5934b43869bfbe7e220d24d1f2025-08-20T03:16:58ZengAIMS PressMathematical Biosciences and Engineering1551-00182025-02-0122243147610.3934/mbe.2025017Computational modeling of peritoneal dialysis: An overviewSangita Swapnasrita0Joost C de Vries1Carl M. Öberg2Aurélie MF Carlier3Karin GF Gerritsen4MERLN Institute for Regenerative Medicine, Maastricht University, Universiteitssingel 40, 6229 ER Maastricht, The NetherlandsDepartment of Nephrology and Hypertension, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The NetherlandsDepartment of Clinical Sciences Lund, Division of Nephrology, Skåne University Hospital, Lund, University, Lund, SwedenMERLN Institute for Regenerative Medicine, Maastricht University, Universiteitssingel 40, 6229 ER Maastricht, The NetherlandsDepartment of Nephrology and Hypertension, University Medical Center Utrecht, Heidelberglaan 100, 3584 CX Utrecht, The NetherlandsPeritoneal dialysis (PD) is a kidney replacement therapy for patients with end-stage renal disease. It is becoming more popular as a result of a rising interest in home dialysis. Its effectiveness depends on several physiological and technical factors, which have led to the development of various computational models to better understand and predict PD outcomes. In this review, we traced the evolution of computational PD models, discussed the principles underlying these models, including the transport kinetics of solutes, the fluid dynamics within the peritoneal cavity, and the peritoneal membrane properties, and reviewed the various PD models that can be used to optimize and personalize PD treatment. By providing a comprehensive overview, we aim to guide both current clinical practice and future research into novel PD techniques such as the application of continuous flow and sorbent-based dialysate regeneration where mathematical modeling may offer an inexpensive and effective tool to optimize design of these novel techniques at a patient specific level.https://www.aimspress.com/article/doi/10.3934/mbe.2025017peritoneal dialysismathematical modelingsolute fluxvolume fluxparameter determination |
| spellingShingle | Sangita Swapnasrita Joost C de Vries Carl M. Öberg Aurélie MF Carlier Karin GF Gerritsen Computational modeling of peritoneal dialysis: An overview Mathematical Biosciences and Engineering peritoneal dialysis mathematical modeling solute flux volume flux parameter determination |
| title | Computational modeling of peritoneal dialysis: An overview |
| title_full | Computational modeling of peritoneal dialysis: An overview |
| title_fullStr | Computational modeling of peritoneal dialysis: An overview |
| title_full_unstemmed | Computational modeling of peritoneal dialysis: An overview |
| title_short | Computational modeling of peritoneal dialysis: An overview |
| title_sort | computational modeling of peritoneal dialysis an overview |
| topic | peritoneal dialysis mathematical modeling solute flux volume flux parameter determination |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2025017 |
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