Characterization of the cylindrical electrospun nanofibrous polysulfone membrane for hemodialysis with modelling approach

Farzaneh Mohammadi*, Zeinab Yavari, Farideh Mohammadi

*Corresponding author for this work

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Electrospun nanofibrous membrane (ENM) is a membrane fabricated using electrospinning technique which has considerable characteristics such as high porosity, nanometer pore size, and simple process. Although ENMs are being evaluated in various medical applications, the effectiveness for hemodialysis (HD) has not been evaluated carefully. Thus, in this study, the cylindrical electrospun nanofibrous polysulfone (CENP) membrane was fabricated and its performance in the dialysis adequacy in HD patients was evaluated. The CENP membrane was fabricated in a tabular shape. The physical characteristics of the membrane are examined using scanning electron microscope (SEM) images and the permporometry technique. Then, its efficiency in urea and creatinine removal from the blood serum of 21 HD patients was evaluated at a low blood flow rate (BFR) of 200 ml min-1 and dialysate fluid rate (DFR) of 300 ml min-1. Afterwards, the results were modeled and optimized using artificial neural network (ANN) and genetic algorithm (GA), respectively. Finally, sensitive analysis was performed via Spearman’s rank correlation coefficient. The highest dialysis adequacy was observed in membranes with an inner diameter of 3 mm. The CENP membrane belongs to the super high-flux membrane and it could be replaced with existing commercial hollow fiber membranes. Graphical abstract: [Figure not available: see fulltext.].

Original languageEnglish
Pages (from-to)1629-1641
Number of pages13
JournalMedical and Biological Engineering and Computing
Volume59
Issue number7-8
DOIs
Publication statusPublished - 2021

Keywords

  • Artificial neural network modelling
  • Electrospinning
  • Hemodialysis
  • Kidney
  • Nanofibrous membrane

ASJC Scopus subject areas

  • Biomedical Engineering
  • Computer Science Applications

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