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Abstract: TH-PO307

Dynamical Monitoring of "Intraperitoneal" Pressures by a Sensor Integrated into a Peritoneal Dialysis (PD) Cycler: Proof-of-Principle Bench Studies

Session Information

  • Home Dialysis - I
    November 02, 2023 | Location: Exhibit Hall, Pennsylvania Convention Center
    Abstract Time: 10:00 AM - 12:00 PM

Category: Dialysis

  • 802 Dialysis: Home Dialysis and Peritoneal Dialysis

Authors

  • Zhu, Fansan, Renal Research Institute, New York, New York, United States
  • Rosales M., Laura, Renal Research Institute, New York, New York, United States
  • Tisdale, Lela, Renal Research Institute, New York, New York, United States
  • Yi, Jun, Fresenius Medical Care, Waltham, Massachusetts, United States
  • Fischer, Karsten, Fresenius Medical Care, Waltham, Massachusetts, United States
  • Plahey, Kulwinder, Fresenius Medical Care, Waltham, Massachusetts, United States
  • Chamney, Paul William, Fresenius Medical Care (UK) Ltd, Huthwaite, United Kingdom
  • Schiller, Brigitte, Fresenius Medical Care, Waltham, Massachusetts, United States
  • Kotanko, Peter, Renal Research Institute, New York, New York, United States
Background

We performed two bench studies utilizing a PD simulator. One evaluated the accuracy and precision of IPP measurements by a pressure sensor integrated in a PD cycler; the second assessed the relationship between IPP and intraperitoneal volume (IPV) during volume exchanges.

Methods

The first study was performed using a PD simulator filled with 2 liters of 2.5% dextrose dialysate (Fig.1). The IPP was monitored every 15 seconds by the Liberty Cycler (Fresenius Medical Care North America, Waltham, MA). The height (h) of the PD simulator was adjusted to increase in 6 steps and decrease in 5 steps. The height increment (Δh) was 5.08 cm; each step was maintained for 10 minutes. The change in pressure (ΔP) is calculated as ΔP=ρ*g*Δh, where ρ (density of dialysate) and g (acceleration of gravity) were kept constant. The coefficient of variation (CV% = 100*Mean/SD) of the IPP was obtained at each step. The second bench study kept the PD simulator at a constant height and IPP measurements were repeated 8 times. Regression analysis and Bland-Altman plots were performed to determine the relationship between calculated and measured IPP.

Results

Fig.2 shows the change in height (a) of the simulator and the concurrent increased and decreased in IPP (b) with the steps up and down. ΔIPP correlated (R2=0.98, p<0.0001) with ΔP in each step (c). IPPs were accurately and precisely measured with a smaller bias (0.34±0.87 cmH2O) and CV (2.5±1.9 %). IPP correlated with IPV (Fig.3) during filling (R2=0.99, p<0.0001) and draining (R2=0.86, p<0.0003) respectively.

Conclusion

This bench study shows that ΔIPP can be measured accurately and precisely by the pressure sensor integrated in the Liberty Cycler and that IPP measurements should be feasibly, non-invasively and automatically performed using a PD cycler equipped with a pressure sensor. Given the importance of IPP changes during a PD treatment, the technique could be a valuable tool to dynamically assess IPP.