ASN's Mission

ASN leads the fight to prevent, treat, and cure kidney diseases throughout the world by educating health professionals and scientists, advancing research and innovation, communicating new knowledge, and advocating for the highest quality care for patients.

learn more

Contact ASN

1401 H St, NW, Ste 900, Washington, DC 20005

email@asn-online.org

202-640-4660

The Latest on Twitter

Kidney Week

Abstract: PO1274

Monitoring for Early Signs of Peritonitis in Patients Undergoing Peritoneal Dialysis

Session Information

Category: Dialysis

  • 703 Dialysis: Peritoneal Dialysis

Authors

  • Fischman, Michael Alan, Southland Renal Medical Group, Long Beach, California, United States
  • Briggs, Benjamin, University of California San Francisco, San Francisco, California, United States
  • Chertow, Glenn Matthew, Stanford University, Stanford, California, United States
Background

In 2019 the U.S. Department of Health and Human Services (HHS) established the “Advancing American Kidney Health” initiative, with a goal of increasing home-based dialysis from 12% to over 50% by 2025. To meet this goal, healthcare providers must address the common complications of peritoneal dialysis (PD) that contribute to modality failure and reluctance to opt for PD when starting dialysis. A sharp increase in PD utilization will require new approaches to reducing peritonitis and infection-related hospitalization.

Methods

Current strategies to detect peritonitis rely on crude signs and symptoms – predominantly cloudy spent dialysate and abdominal pain – an insensitive and non-specific approach. With the CloudCath monitoring system, the intent is to automatically and quantitively monitor the turbidity of the effluent fluid. We evaluated the CloudCath monitoring device which includes a cloud-based algorithmic solution for early detection of the patient condition associated with peritonitis.

Results

The device and algorithm were tested in a proof of concept clinical study where we found a discernable change in monitoring status in 99% of samples from patients with peritonitis, while changes in monitoring status were present in only 2% of samples from dialysis sessions of otherwise healthy PD patients. In some cases, the device was able to provide indicators of impending peritonitis, before standard laboratory values met accepted diagnostic criteria peritonitis. The device (CloudCath, San Francisco, CA) remotely monitors the patient’s effluent dialysis fluid and sends alerts via the cloud to healthcare providers as soon as abnormal fluid characteristics are detected.

Conclusion

Early detection of peritonitis can lead to earlier clinical intervention and a better clinical response, relative to the current standard of care. Studies are ongoing to test the ability of the device to reduce morbidity, reduce infection-driven hospitalizations, and maintain PD as the patient’s preferred dialysis modality.

Funding

  • Commercial Support