The first experience of creating a mobile application for diagnosis and correction of nutritional deficiency in cancer patients

Nutritional deficiency is a problem that occurs in 30 % to 80 % of cancer patients, but is often undiagnosed. In the era of digitalization, it is important to create programs aimed at increasing the availability of medical care. The purpose of the study was to сreate a mobile application for the diagnosis and correction of nutritional deficiency in cancer patients. Material and methods. A prospective study was conducted among cancer patients. Group 1 – cancer patients with nutritional deficiency (n=105), group 2 – without nutritional deficiency (n=96). Both groups were matched for age, gender, cancer diagnosis and concomitant pathology (p>0.05). The main phases of the study were: identification of significant markers associated with nutritional deficiency in cancer patients – complete blood count and biochemical analysis, anthropometric parameters and results of the functional tests; analysis of the capabilities of the mobile application; development of the application; validation of the created product. Results. Weight loss, body mass index, body mass deficit, skin-fat fold thickness above the triceps and below the scapula, dynamometry results in men, strength index in women, 5-fold chair stand-up test and 4-meter walk test were changed in cancer patient with nutritional deficiency. The equation for calculating the coefficient k was created using binary logistic regression, which allowed detection of nutritional deficiency. Diagnostic significance was: Sp=0.796, Se=0.798, Ac=0.785. Area under the ROC curve was 0.84 (95 % CI 0.79–0.89), p<0.001. The model formed the basis for creating a mobile application for identifying and correcting nutritional deficiency in cancer patients. The mobile application was developed based on the object-oriented programming language Object Pascal (Borland Delphi). The program eliminates the emergency complications in cancer patients. The patient or a relative or health care professional then enters the data and determines whether there is a nutritional deficiency. The personalization of recommendations is carried out by taking into consideration the functional features of eating. Сonclusion. The created mobile application makes it possible to improve the accuracy of diagnosis of nutritional deficiency by taking into account quantitative values associated with its development in cancer patients. Personalization of recommendations has been thought out, taking into account the functional status of nutritional characteristics.

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