Hemoglobin Modeling and Simulation for Anemia Management in Chronic Kidney Disease

• Author / Creator

  Bajwa, Nirwair Singh

• Chronic Kidney Disease (CKD) affects a huge number of people in the world. One of the signicant side effects of this infection is the inability to maintain the body's red blood cell production (RBC), and along these lines, the mass of a protein called hemoglobin inside the body. The wellbeing of these patients crumbles and over time they become anemic. Recently, exogenous erythropoietin stimulating agents have turned into the standard for treating anemia during CKD. The pharmaceutical works greatly well for what it is intended to do. The issue with this situation is the failure of the doctor's to have the capacity to pick an appropriate dose for every patient. The dosing protocols are not standardized crosswise over hospitals and huge numbers of the dosings regimens are ineffectively designed. In that capacity, many patients' hemoglobin levels are inadequately controlled. The poor hemoglobin control in CKD patients is well documented in the literature. Automated anemia management based on feedback is one approach to address this issue. A reliable model is very important in the design of the control system.
  In this thesis, the objectives are (1) to present an articial patient simulator developed exclusively based on measurement noise and time-varying parameters in Pharmacokinetics and Pharmacodynamics (PKPD) model, (2) performance assessment of non-linear constrained ARX model (C-ARX), and (3) hemoglobin modeling technique with modifed constrained ARX modeling (C-ARX) method utilizing additional
  measurement such iron saturation and white blood cell (WBC) count. The hemoglobin response modeling methods are compared on a clinical data containing 167 patients. It will be demonstrated that the new modeling method offers better
  modeling results to the previously developed C-ARX model.

• Subjects / Keywords

  • System Identication with Iron Level and WBC
  • Model Performance Assessment of Constrained ARX model
  • Artificial Patient Simulator Design

• Graduation date

  Fall 2018

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R37M04G62

• License

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