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Forecasting of Atopic Dermatitis in Newborns
BACKGROUND: Early forecasting of any pathological process is of great significance from both medical and economic point of view. An illness requires much more attention in the light of exhaustion of resources of the body, and a doctor should be maximally aware of the near and far future of a patient...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Wolters Kluwer - Medknow
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9644799/ https://www.ncbi.nlm.nih.gov/pubmed/36386108 http://dx.doi.org/10.4103/ijd.ijd_933_21 |
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author | Hajiyeva, Nurangiz Gafarov, Ismail Hajiyeva, Adelya Sultanova, Nailya Panahova, Tahira |
author_facet | Hajiyeva, Nurangiz Gafarov, Ismail Hajiyeva, Adelya Sultanova, Nailya Panahova, Tahira |
author_sort | Hajiyeva, Nurangiz |
collection | PubMed |
description | BACKGROUND: Early forecasting of any pathological process is of great significance from both medical and economic point of view. An illness requires much more attention in the light of exhaustion of resources of the body, and a doctor should be maximally aware of the near and far future of a patient. In this regard, the preparation of forecasting programs on a mathematical basis would be a rational and, most probably, the only true approach to the solution of forecasting. AIMS AND OBJECTIVES: The aim of the article is to study the forecasting of atopic dermatitis (AD) in newborns. METHODOLOGY: The authors studied 109 clinical and laboratory indicators in children without and with AD. Discriminant analysis was used as an algorithm for the resolution of diagnostic issues. RESULTS: The main indicators acceptable as a forecasting criterion in the formation of AD in children were defined. The sensitivity, specificity, and general diagnostic value of statistically valid differing factors in the formation of AD were studied. Key rules of the forecast were formed after processing all indicators through the KU–Kruskal–Wallis discriminant criterion, a universal computer method. CONCLUSION: It was concluded that the power of influence of rhinitis, cluster of differentiation 31, mucin 2, and intestinal trefoil factor 3 are higher in the AD model. |
format | Online Article Text |
id | pubmed-9644799 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Wolters Kluwer - Medknow |
record_format | MEDLINE/PubMed |
spelling | pubmed-96447992022-11-15 Forecasting of Atopic Dermatitis in Newborns Hajiyeva, Nurangiz Gafarov, Ismail Hajiyeva, Adelya Sultanova, Nailya Panahova, Tahira Indian J Dermatol Original Article BACKGROUND: Early forecasting of any pathological process is of great significance from both medical and economic point of view. An illness requires much more attention in the light of exhaustion of resources of the body, and a doctor should be maximally aware of the near and far future of a patient. In this regard, the preparation of forecasting programs on a mathematical basis would be a rational and, most probably, the only true approach to the solution of forecasting. AIMS AND OBJECTIVES: The aim of the article is to study the forecasting of atopic dermatitis (AD) in newborns. METHODOLOGY: The authors studied 109 clinical and laboratory indicators in children without and with AD. Discriminant analysis was used as an algorithm for the resolution of diagnostic issues. RESULTS: The main indicators acceptable as a forecasting criterion in the formation of AD in children were defined. The sensitivity, specificity, and general diagnostic value of statistically valid differing factors in the formation of AD were studied. Key rules of the forecast were formed after processing all indicators through the KU–Kruskal–Wallis discriminant criterion, a universal computer method. CONCLUSION: It was concluded that the power of influence of rhinitis, cluster of differentiation 31, mucin 2, and intestinal trefoil factor 3 are higher in the AD model. Wolters Kluwer - Medknow 2022 /pmc/articles/PMC9644799/ /pubmed/36386108 http://dx.doi.org/10.4103/ijd.ijd_933_21 Text en Copyright: © 2022 Indian Journal of Dermatology https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms. |
spellingShingle | Original Article Hajiyeva, Nurangiz Gafarov, Ismail Hajiyeva, Adelya Sultanova, Nailya Panahova, Tahira Forecasting of Atopic Dermatitis in Newborns |
title | Forecasting of Atopic Dermatitis in Newborns |
title_full | Forecasting of Atopic Dermatitis in Newborns |
title_fullStr | Forecasting of Atopic Dermatitis in Newborns |
title_full_unstemmed | Forecasting of Atopic Dermatitis in Newborns |
title_short | Forecasting of Atopic Dermatitis in Newborns |
title_sort | forecasting of atopic dermatitis in newborns |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9644799/ https://www.ncbi.nlm.nih.gov/pubmed/36386108 http://dx.doi.org/10.4103/ijd.ijd_933_21 |
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