Artificial intelligence tools for phenotyping patients with anaphylaxis

BACKGROUND: Anaphylaxis is the most severe manifestation of immediate systemic hypersensitivity reactions. In recent years, there has been an increase in the number of reported cases of anaphylaxis. Given the variety of clinical manifestations behind the diagnosis of “anaphylaxis”, one of the most urgent issues at present is the task of phenotyping and endotyping of patients with this life-threatening pathology as part of implementation of the individual approach, both during treatment in the acute period and diagnosis in the period of recovery. AIM: To find the main clinical phenotypes of patients with immediate hypersensitivity reactions, which will further allow stratifying patients by risk groups bringing therapeutic and diagnostic algorithms to the modern level of personalized medicine. MATERIALS AND METHODS: The study was conducted based on retrospective stepwise analysis of patient medical record data from 2019 to 2022. To identify relatively homogeneous groups of patients based on clinical, agglomerative clustering was performed on 56 variables followed by 2 principal component extraction using the dimensionality reduction method with t-distributed stochastic neighbor embedding. Agglomerative clustering divided patients into 4 major clinical phenotypes, and each patient was assigned a corresponding phenotype. RESULTS: Based on this analysis, 4 phenotypes of patients with severe immediate-type hypersensitivity reactions were identified. CONCLUSION: A new classification based on the use of phenotypes, endotypes and biomarkers is currently being developed to broaden our understanding of anaphylactic reactions. Given the limitations of the study (patients were not subjected to additional examinations in the current study), it is not possible to reliably identify endophenotypic differences in different clusters. Additional studies are needed to identify the correlation between anaphylactic reaction phenotypes and its pathophysiological mechanisms of development.