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Abohtyra, R.

Publications and source records attributed to Abohtyra, R..

3 recordsLinked to original sources

Nonlinear Parameter and State Estimation Approach for Intradialytic Measurement of Absolute Blood Volume

BackgroundManaging blood and fluid volumes in chronic kidney disease (CKD) patients plays an essential role in dialysis therapy to replace kidney function. ObjectiveThis study aims to develop an estimation approach to provide predictable information on blood and fluid volumes during a regular dialysis routine. MethodsThe method utilizes a non-linear fluid volume model, an optimization technique, and the Unscented Kalman Filter (UKF). This method does not rely on specific ultrafiltration and dilution protocols and uses the Fisher information matrix to quantify the estimation error. ResultsThe method was applied to 21 data sets of ten patients. A significant moderate correlation was obtained when estimated blood volumes were compared to a different method applied to the same data set. Average specific blood volumes were plausible and in the range of 78.7 and 75.9 mL/kg at the end of the high ultrafiltration rate pulse and above the critical level of 65 mL/kg. Critical blood volumes were only observed in four studies done on three patients. ConclusionThe absolute blood volume estimated at the beginning and during every dialysis session offers the opportunity to detect critical blood volumes and to improve fluid management in CKD patients significantly.

bioengineering↗

Nonlinear Parameter and State Estimation Approach in End-stage Kidney Disease Patients

BackgroundBlood and fluid volume management in End-stage Kidney Disease (ESKD) patients plays an essential role in dialysis therapy to replace kidney function. Reliable knowledge of blood and fluid volumes before and during dialysis could be used to improve treatment outcomes significantly. ObjectiveThis study aims to develop an estimation approach providing predictable information on blood and fluid volumes before and during a regular dialysis routine. MethodsA new approach is developed to estimate blood volume, fluid overload, and vascular refilling parameters from dialysis data. The method utilizes a nonlinear fluid volume model, an optimization technique, and the Unscented Kalman Filter (UKF) incorporated with data. This method does not rely on restricted ultrafiltration (UF) and dilution protocols and uses the Fisher information matrix to quantify error estimation. ResultsAccurate estimations for blood volumes (5.9{+/-}0.07L and 4.8{+/-}0.03L) and interstitial fluid volumes (18.81{+/-}0.15L and 12.19{+/-}0.03) were calculated from dialysis data consisting of constant and stepwise UF profiles. We demonstrated that by implementing the estimated parameters into the model, a precise prediction of the measured hematocrit (HCT) can be achieved during the treatment. ConclusionWe showed that the result does not depend highly on initial conditions and can be accurately estimated from a short data segment. A new method, applicable to the current dialysis routine, is now available for ESKD patients to be implemented within the dialysis machines.

bioengineering↗

Nonlinear Stability Analysis for Artificial Kidney Multi-compartmental Models

This paper addresses a new global stability analysis for a specific class of nonlinear multi-compartment models with non-positive flows and whose balances are described by equilibrium sets. We apply the stability analysis to our physiological-based model of extracellular fluid used during dialysis therapy in end-stage kidney disease patients. To gain an in-depth understanding of the risk associated with fluid removal by the artificial kidney during the short time (3-5hrs) of the dialysis therapy, we use the stability results to analyze the solutions behavior of our model under standard ultrafiltration and patient-specific ultrafiltration profiles. Therefore, the standard ultrafiltration profiles do not guarantee optimal outcomes, and we highly recommend incorporating physiological insights into the ultrafiltration profiles to improve outcomes.

bioengineering↗