Year: 2024
Type: article
Study design: Observational Study
Abstract: Introduction. Studying the influence of chemical sensitivity on functional disorders by means of digital diagnostic technologies is a significant medical and social problem. Aim. To study the possibility of the EcoMedic digital platform in the diagnosis of functional disorders with multiple chemical sensitivity (MCH). Materials and methods. Questionnaires were administered using the QEESI questionnaire to 468 outpatients undergoing preventive medical examination (232 men, mean age 34.2 ± 9.3 years and 236 women mean age 42.9 ± 13.8 years). Data were collected using the developed digital platform EcoMedic. Statistical processing was performed using MedCalc statistical programme. Results. The frequency of MCH was 211 patients (45.1%). The most frequent complaints in MCH were gastrointestinal (n = 174, 82.4%); second were cognitive symptoms (n = 158, 75.1%); dall neurological (n = 149, 71.1%); musculoskeletal (n = 144, 68.5%); neuromuscular (n = 139, 66.4%); respiratory and mucosal (n = 130, 62.1%); cutaneous (n = 124, 59.1%); affective (n = 118, 56.4%). In MCH, symptom frequency across all 10 symptom groups was significantly higher than in controls (p < 0.0001). In MCH, the frequency of symptoms in all 10 groups of symptoms was significantly higher than in patients without MCH (p < 0.0001). The frequency of overlapping of 3 regions of the MCH scales simultaneously in the group of patients with MCH was higher than without MCH (60.2% vs 3.1%, χ2 = 186.065, p = 0.000). The proportion of people with thresholds for severity of symptoms or impact on daily life according to only one of the scales in the group of patients with HCV was significantly lower (9% vs 32.6%, χ2 = 37.853, p = 0.001). Conclusions. The EcoMedic digital platform has prospects for scaling technologies to diagnose patients with HCV and conduct scientific and practical studies of functional symptoms.
DOI: 10.21518/ms2024-392
Institution: Kuban State Medical University
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
Funder: Kuban Science Foundation
OpenAlex ID: W4405343243