Early Bayesian modeling of a potassium lab-on-a-chip for monitoring of heart failure patients at increased risk of hyperkalaemia

Abstract

Objectives: Innovative point-of-care (POC) diagnostics are likely to have a strong impact on health care. The aim of this study is to conduct an early assessment of a point-of-care chip for the detection of a pathological deviation of the potassium levels in patients at increased risk, specifically in patients with heart failure (HF) requiring diuretics and ACE inhibitors that can both interfere with potassium levels, which may lead to serious clinical complications. This study also identifies the key factors that determine the success of the application under study. Methods: A Markov health state transition model was developed representing the disease process. Model parameters were obtained..