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Abstract: PO0964

Smartphone Application to Assist Peritoneal Dialysis Patients for Timely Detection of Peritonitis

Session Information

Category: Dialysis

  • 702 Dialysis: Home Dialysis and Peritoneal Dialysis

Authors

  • Garbaccio, Mia, Renal Research Institute, New York, New York, United States
  • Tao, Xia, Renal Research Institute, New York, New York, United States
  • Wang, Xiaoling, Renal Research Institute, New York, New York, United States
  • Wang, Xin, Renal Research Institute, New York, New York, United States
  • Haq, Zahin Sultana, Renal Research Institute, New York, New York, United States
  • Patel, Amrish U., Renal Research Institute, New York, New York, United States
  • Tisdale, Lela, Renal Research Institute, New York, New York, United States
  • Thwin, Ohnmar, Renal Research Institute, New York, New York, United States
  • Wang, Lin-Chun, Renal Research Institute, New York, New York, United States
  • Grobe, Nadja, Renal Research Institute, New York, New York, United States
  • Kotanko, Peter, Renal Research Institute, New York, New York, United States
Background

Timely detection of peritonitis in patients undergoing peritoneal dialysis (PD) is critical to lower the risk of catheter loss, morbidity and mortality (Muthucumarana, 2016). Current practice of screening potential peritonitis events at home relies on patients' visual detection of turbid spent dialysate and symptoms recognition. . To assist patients with the timely capture of a potential peritonitis episode, we developed a smartphone app, which uses light detection to quantitate cloudiness and estimate white blood cell (WBC) count in PD effluent (PDE).

Methods

The app uses the built-in light sensor and compares measurements taken from the ambient light (Lambient) and light through PD bags (Lbag) to estimate dialysate cloudiness. PDE samples were obtained as part of two IRB-approved clinical studies over a period of 6 months. Cloudiness of each sample was measured 3x with the app. Cloudiness (in %) was calculated as (1 - Lbag /Lambient ) * 100. WBC were counted using a hematology analyzer (Horiba 80XL).

Results

Patients maintained a stable baseline cloudiness of 2-5% (Fig 1). A peritonitis episode (subject PDMET0002) increased the cloudiness to 40%, which is 32 percentage points over the patient’s peritonitis-free baseline. One suspected peritonitis sample (albeit WBCs <100 cells/mL) showed slightly higher cloudiness than non-peritonitis samples (Fig 2).

Conclusion

Our smartphone app can distinguish peritonitis from normal PDE samples. Smartphone-enabled detection of cloudiness in PDE samples using light transmission is possible and has the potential to easily monitor and diagnose patients at risk for peritonitis. Studies to define diagnostic performance in a large patient cohort are underway.