Modern Possibilities for Predicting Systemic Manifestations of Food Allergy Based on the Results of a Prospective Cohort Study
- Authors: Lepeshkova T.S.1, Kovtun O.P.1, Beltyukov E.K.1, Naumova V.V.1, Tsarkova S.A.1, Bazarny V.V.1, Polushina L.G.1
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Affiliations:
- Ural State Medical University
- Issue: Vol 78, No 5 (2023)
- Pages: 455-466
- Section: PEDIATRICS: CURRENT ISSUES
- Published: 22.01.2024
- URL: https://vestnikramn.spr-journal.ru/jour/article/view/12970
- DOI: https://doi.org/10.15690/vramn12970
- ID: 12970
Cite item
Abstract
Background. Food allergies (FA) are a common problem in childhood. Food anaphylaxis (FAN) can be life threatening. In this regard, it is reasonable to study clinical and anamnestic data and factors that can influence FAN formation in order to develop mathematical models of prognosis aimed at reducing acute episodes of FA, including FAN. Aims — to establish clinical and pathogenetic factors contributing to the formation of systemic manifestations of FA in children and to develop a mathematical method for predicting severe systemic reactions to food. Methods. A prospective cohort open study included 76 children (5.12 ± 3.74 years) suffering from persistent FA with a history of FAN episodes. The comparison group included 134 children (7.18 ± 2.52 years old) who had atopic diseases, local manifestations of FA, but without systemic reactions to food. Illness and life history, presence and severity of concomitant diseases were studied, general clinical and immunological studies were performed (in blood serum and oral cavity). Results. Based on the data in 210 children, the odds ratio (OR) of systemic FA formation was calculated, where the risks were: caesarean section (OR 1.8; 95% CI [1.02; 3.01]; p < 0.05), immediate allergic reactions to food (OR 3.3; 95% CI [1.47; 7.39]; p < 0.05), maternal anemia during pregnancy (OR 3.5; 95% CI [1.83; 6.57]; p < 0.05), allergic diseases in siblings (OR 4.8; 95% CI [2.04; 11.18]; p < 0.05), presence of atopic dermatitis (AD) (OR 3.7; 95% CI [1.77; 7.68]; p < 0.05), allergy to cow’s milk proteins (CMP) (OR 7.8; 95% CI [4.31; 14.24]; p < 0.05), clinical need for introduction of amino acid formulae (OR 100.8; 95% CI [13.37; 760.67]; p < 0.05). A mathematical method was found for predicting FAN with a decision rule Y ≥ 0.35, with a forecast efficiency of up to 90% when using a linear regression equation: Y = 0.0518 + 0.2983×A1 + 0.2390 × A2 + 0.4793×A3 – 0.0037 × A4 + 0.0002 × A5, where A1 is CMP as the first allergic product (0 or 1), A2 is rapid onset of reaction (0 or 1), A3 is amino acid formulae use (0 or 1), A4 is age of wheezing (in months), A5 is eosinophils (cells/µl). Conclusions. Symptoms of AD and severe FA to CMP, requiring amino acid formulae introduction, should be considered as alarming anamnestic data for predicting possible FAN episodes, if the child has immediate type of FA, the mother’s pregnancy proceeded against the background of anemia, delivery was carried out operatively way and there are already children with atopic diseases in the family. The proposed mathematical method for predicting FAN makes it possible to determine probability of severe allergic reactions to food in children with an efficiency of up to 90%.
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About the authors
Tatiana S. Lepeshkova
Ural State Medical University
Email: levlpa@mail.ru
ORCID iD: 0000-0002-0716-3529
SPIN-code: 9397-6019
MD, PhD
Россия, YekaterinburgOlga P. Kovtun
Ural State Medical University
Email: usma@usma.ru
ORCID iD: 0000-0002-5250-7351
SPIN-code: 9919-9048
MD, PhD, Professor, Academician of the RAS
Россия, YekaterinburgEvgeny K. Beltyukov
Ural State Medical University
Email: asthma@mail.ru
ORCID iD: 0000-0003-2485-2243
SPIN-code: 6987-1057
MD, PhD, Professor, Corresponding Member of the RAS
Россия, YekaterinburgVeronika V. Naumova
Ural State Medical University
Author for correspondence.
Email: nika.naumova@gmail.com
ORCID iD: 0000-0002-3028-2657
SPIN-code: 8210-6478
MD, PhD
Россия, YekaterinburgSofya A. Tsarkova
Ural State Medical University
Email: tsarkova_ugma@bk.ru
ORCID iD: 0000-0003-4588-5909
SPIN-code: 8649-9681
MD, PhD, Professor
Россия, YekaterinburgVladimir V. Bazarny
Ural State Medical University
Email: bazarny@yandex.ru
ORCID iD: 0000-0003-0966-9571
SPIN-code: 4813-8710
MD, PhD, Professor
Россия, YekaterinburgLarisa G. Polushina
Ural State Medical University
Email: polushina-larisa@bk.ru
ORCID iD: 0000-0002-4921-7222
SPIN-code: 4391-5873
MD, PhD
Россия, YekaterinburgReferences
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