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Mathematical model for treatment of neonatal hyperbilirubinemia


  • Received: 05 April 2021 Accepted: 23 September 2021 Published: 13 October 2021
  • Based on the mechanism of neonatal hyperbilirubinemia treatment methods (light, exchange blood and drugs), three types of neonatal hyperbilirubinemia treatment mathematical models are established, and the expressions of the model solutions are given in this paper. By applying clinical test data and numerical approximation algorithm, the relevant parameters in the model can be estimated. According to the standards of "Expert Consensus", two treatment plans are designed, which are 1) the combined transfusion and phototherapy treatment plan and 2) the combined treatment plan of drugs, transfusion and phototherapy. The results of the program operation are numerically simulated and compared with the treatment data of clinical cases. It is found that the coincidence effect is important, which verified the rationality of the model. The model results can track and predict the changes of bilirubin levels in real-time, which provides a theoretical basis for the clinical design of treatment plans.

    Citation: DongMei Li, Rui-xue Zhang, Qian Xie, Qi Wang. Mathematical model for treatment of neonatal hyperbilirubinemia[J]. Mathematical Biosciences and Engineering, 2021, 18(6): 8758-8782. doi: 10.3934/mbe.2021432

    Related Papers:

  • Based on the mechanism of neonatal hyperbilirubinemia treatment methods (light, exchange blood and drugs), three types of neonatal hyperbilirubinemia treatment mathematical models are established, and the expressions of the model solutions are given in this paper. By applying clinical test data and numerical approximation algorithm, the relevant parameters in the model can be estimated. According to the standards of "Expert Consensus", two treatment plans are designed, which are 1) the combined transfusion and phototherapy treatment plan and 2) the combined treatment plan of drugs, transfusion and phototherapy. The results of the program operation are numerically simulated and compared with the treatment data of clinical cases. It is found that the coincidence effect is important, which verified the rationality of the model. The model results can track and predict the changes of bilirubin levels in real-time, which provides a theoretical basis for the clinical design of treatment plans.



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