On a Correlation between the Results of In-Hospital Analysis of Biosamples from Children Performed Using Standard Methods and an Array of Piezosensors

A rapid procedure for obtaining information on changes in particular characteristics of urine as the most frequently taken biosample is presented. The relationship between the output data of an array of piezoelectric sensors based on different micro- and nanostructured phases and the standard characteristics of clinical urine analysis is discussed. Volatile organic compounds identified in an equilibrium headspace gas phase of the samples with deviations from normal characteristics of clinical urine analysis are considered. The tetrachoric correlation coefficients and associations between the parameters of a sensor array and standard characteristics were calculated. A minimum set of calculated parameters of an electronic nose for the rapid in-hospital monitoring of changes in the patient’s condition in the course of therapy or medical examination was recognized. A fast and economically affordable method was developed for the monitoring of body state characteristics using the profile of volatile urine compounds obtained with an electronic nose based on piezosensors. Two versions, a color scale and a table, were proposed for presenting the electronic nose data; they can be used even by specially untrained personnel for the rapid and easy assessment of the most important urine analysis data (protein, glucose, mucus, and bacteria). The method developed makes it possible to quickly (the time of a measurement is 120 s) perform the daily monitoring of patient’s condition to avoid an unnecessary burden on the laboratory and to increase the physician’s awareness of the dynamics of the patient’s condition and facilitate the choice of treatment tactics. This method can be used for clinical examinations in polyclinics and feldsher’s stations, and it will significantly shorten the time taken to obtain screening and diagnostic information on disruptions in the body, in particular, at the initial stages of diseases.