Exploring the Gut-Brain Connection in Gastroparesis with Autonomic and Gastric Myoelectric Monitoring

Abstract

ObjectiveThe goal of this study was to identify autonomic and gastric myoelectric biomarkers from throughout the day that differentiate patients with gastroparesis, diabetics without gastroparesis, and healthy controls, while providing insight into etiology.MethodsWe collected 19 24-hour recordings of electrocardiogram (ECG) and electrogastrogram (EGG) data from healthy controls and patients with diabetic or idiopathic gastroparesis. We used physiologically and statistically rigorous models to extract autonomic and gastric myoelectric information from the ECG and EGG data respectively. From these, we constructed quantitative indices which differentiated the different groups and demonstrated their application in automatic classification paradigms and as quantitative summary scores.ResultsWe identified several differentiators that separate healthy controls from gastroparetic patient groups, specifically around sleep and meals. We also demonstrated the downstream utility of these differentiators in automatic classification and quantitative scoring paradigms. Even with this small pilot dataset, automated classifiers achieved an accuracy of 79% separating autonomic phenotypes and 65% separating gastrointestinal phenotypes. We also achieved 89% accuracy separating controls from gastroparetic patients in general and 90% accuracy separating diabetics with and without gastroparesis. These differentiators also suggested varying etiologies for different phenotypes.ConclusionThe differentiators we identified were able to successfully distinguish between several autonomic and gastrointestinal (GI) phenotypes using data collected while at-home with non-invasive sensors.SignificanceAutonomic and gastric myoelectric differentiators, obtained using at-home recording of fully non-invasive signals, can be the first step towards dynamic quantitative markers to track severity, disease progression, and treatment response for combined autonomic and GI phenotypes.

On the Use of Impedance Detuning for Gastrointestinal Segment Tracking of Ingestible Capsules

“…In this context, this paper examines several operational parameters of three common ingestible antenna types (dipole, patch, and loop) within the GI tract to analyze and compare their suitability for GI sensing throughout ST, SI, and LI. GI sensing refers to distinguishing different GI tissues and tracking the real-time relative location of the capsule in the GI tract, which can aid in diagnosing specific pathologies such as gastroparesis [42]. The examination is conducted in the 433 MHz Industrial, Scientific, and Medical (ISM) band using homogeneous phantoms representing GI tissues.…”