Diagnosis of Digestive Functional Disease by the Statistics of Continuous Monitoring of Esophageal Acidity.

Technological advances in the last few decennia allow the monitoring of many physiological observables in a continuous way, which in physics is called a "time series". The best studied physiological time series is that of the heart rhythm, which can be derived from an electrocardiogram (ECG). Studies have shown that a healthy heart is characterized by a complex time series and high heart rate variability (HRV). In adverse conditions, the cardiac time series degenerates towards randomness (as seen in, e.g., fibrillation) or rigidity (as seen in, e.g., ageing), both corresponding to a loss of HRV as described by, e.g., Golberger et. al [1]. Cardiac and digestive rhythms are regulated by the autonomous nervous system (ANS), that consists of two antagonistic branches, the orthosympathetic branch (ONS) that accelerates the cardiac rhythm but decelerates the digestive system, and the parasympathetic brand (PNS) that works in the opposite way. Because of this reason, one might expect that the statistics of gastro-esophageal time series, as described by Gardner et. al. [2,3], reflects the health state of the digestive system in a similar way as HRV in the cardiac case, described by Minocha et. al. In the present project, we apply statistical methods derived from HRV analysis to time series of esophageal acidity (24h pHmetry). The study is realized on data from a large patient population from the Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán. Our focus is on patients with functional disease (symptoms but no anatomical damage). We find that traditional statistical approaches (e.g. Fourier spectral analysis) are unable to distinguish between different degenerations of the digestive system, such as gastric esophageal reflux disease (GERD) or functional gastrointestinal disorder (FGID). [ABSTRACT FROM AUTHOR]