Honorable Mention Automated Blood Volume Quantification: Towards Personalized Dialysis

Although many areas of medicine are advancing rapidly through new technology, patient empowerment and data, the treatment if end-stage kidney disease (ESKD) has remain largely unchanged for decades. We present a prototype system based on three components: (1) A set of transit-time ultrasound/dilution probes integrated onto the hemodialysis machine to allow novel physiological measurements, (2) an easy-to-use Cartridge blood tubing set that seamlessly forms couplings to the probes, and (3) a smartphone or machine-based GUI app to curate the data to the patient, solicit feedback and drive engagement. The integrated package allows full automation of measurement tasks, which traditionally have required significant workflow burden and has limited the adoption of sensing technology despite offering numerous clinical benefits.

We demonstrate via a novel bench model the capacity to quantify active circulating blood volume (ACBV) via a saline dilution technique. We constructed a simulated circulatory system, including heart model, lung model, fast and slow circulatory compartments based with volume and flow rates based on literature. We examined the impact of factors such as cardiac output, hemodialysis blood flow rate, system volume, vascular access type (fistula/graft shunt or central venous catheter) and vascular access flow rate on the prototype s ability to quantify ACBV. Overall accuracy was 2.6% ± 7.4%, N = 46 experiments. In a future hemodialysis system, this information can be used to automatically adjust treatment parameters to avoid complications such as intradialytic hypotension.

By empowering patients with easy-to-use hemodialysis technology, automated measurement capabilities and bidirectional feedback portal through apps, we are able to expand what is possible in care settings such as in-home or self-care in-center hemodialysis. The integrated system prototype model eliminates dependence on external factors such as trained users, workflow disruption and standalone equipment to perform measurements. Additionally, equipped with access to their data, the patient has expanded empowerment and increased participation in their care. By allowing physiologic data capture to be more ubiquitous, unprecedented detail in large, longitudinal datasets across patient populations can be generated that will inform and guide future innovation.

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