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Abstract: FR-PO564

Mathematical Model of Intradialytic Acid-Base Dynamics in Patients Subjected to Extracorporeal CO2 Removal

Session Information

Category: Fluid‚ Electrolyte‚ and Acid-Base Disorders

  • 1002 Fluid‚ Electrolyte‚ and Acid-Base Disorders: Clinical

Authors

  • Paneque Galuzio, Paulo, Renal Research Institute, New York, New York, United States
  • Cherif, Alhaji, Renal Research Institute, New York, New York, United States
  • Kunz, Lisa-Marie, Fresenius Medical Care AG & Co KGaA, Bad Homburg, Hessen, Germany
  • Klewinghaus, Juergen, Fresenius Medical Care AG & Co KGaA, Bad Homburg, Hessen, Germany
  • Leinenbach, Hans Peter, Fresenius Medical Care AG & Co KGaA, Bad Homburg, Hessen, Germany
  • Thompson, David, Fresenius Medical Care North America, Waltham, Massachusetts, United States
  • Kotanko, Peter, Renal Research Institute, New York, New York, United States
Background

The use of low flow extracorporeal CO2 removal (ECCO2R) devices in ICU has been introduced to assist in decarboxylation and augmenting protective ventilation strategies for patients with acute respiratory distress syndrome (ARDS). AKI may develop in 25-60% of patients with ARDS. These patients often develop mixed acid-base disorders and need renal replacement therapy (RRT). To manage complex metabolic derangements, it is possible to attach an oxygenator, post-filter, in the continuous kidney replacement therapy (CKRT) circuit as a combined low flow extracorporeal strategy.

Methods

Using a previous acid-base model (Cherif, 2020, Math Biosci Eng), we incorporated models of dialyzer and ECCO2R oxygenator. The model describes the regulation of H+, CO2, and HCO3-. Each component of the system has been separately validated with literature data. The model was structured to capture CVVHD with a gas exchanger integrated into the continuous kidney replacement system post-filter.

Results

The model was parametrized to average data from 10 ventilated critically ill patients with ARDS and AKI undergoing renal and respiratory replacement therapy (Forster et al. Critical Care 2013). We fixed blood flow 355±79 ml/min, dialysate flow 2.3±0.7 L/h, ultrafiltration rate 58ml/h (ranging from 0 to 200 ml/h), gas flow 5.2±1.0 L/min, and treatment duration 95±68 h. The model accurately predicts serum pH and pCO2 for the first 24 h of treatment, with R2 values of 0.98 for pH and 0.94 for pCO2 (Fig. 1). We observe that pH and pCO2 equilibrate within the first 4 hrs.

Conclusion

Our model captured the appropriate dynamical behavior of serum pH, pCO2, and HCO3-. The model could be used as a tool to prescribe CKRT parameters to control acid-base status and to help understand the effectiveness of different arrangements.