20.500.12556/DiRROS-14264 Treatment outcome clustering patterns correspond to discrete asthma phenotypes in children Despite widely and regularly used therapy asthma in children is not fully controlled. Recognizing the complexity of asthma phenotypes and endotypes imposed the concept of precision medicine in asthma treatment. By applying machine learning algorithms assessed with respect to their accuracy in predicting treatment outcome, we have successfully identified 4 distinct clusters in a pediatric asthma cohort with specific treatment outcome patterns according to changes in lung function (FEV1 and MEF50), airway inflammation (FENO) and disease control likely affected by discrete phenotypes at initial disease presentation, differing in the type and level of inflammation, age of onset, comorbidities, certain genetic and other physiologic traits. The smallest and the largest of the 4 clusters- 1 (N = 58) and 3 (N = 138) had better treatment outcomes compared to clusters 2 and 4 and were characterized by more prominent atopic markers and a predominant allelic (A allele) effect for rs37973 in the GLCCI1 gene previously associated with positive treatment outcomes in asthmatics. These patients also had a relatively later onset of disease (6 + yrs). Clusters 2 (N = 87) and 4 (N = 64) had poorer treatment success, but varied in the type of inflammation (predominantly neutrophilic for cluster 4 and likely mixed-type for cluster 2), comorbidities (obesity for cluster 2), level of systemic inflammation (highest hsCRP for cluster 2) and platelet count (lowest for cluster 4). The results of this study emphasize the issues in asthma management due to the overgeneralized approach to the disease, not taking into account specific disease phenotypes. asthma allergy and immunology pediatrics machine learning treatment outcome phenotypes childhood asthma clustering astma alergija in imunologija pediatrija. strojno učenje izid zdravljenja fenotipi astma pri otrocih razvrščanje po skupinah true false true Springer Nature Angleški jezik Ni določen © The Author(s) 2021 Neznano 2021-08-16 13:05:45 2021-08-16 13:05:46 2022-08-20 03:34:34 0000-00-00 00:00:00 2021 0 Velika Britanija 0 Nasl. z nasl. zaslona; Soavtorja iz Slovenije: Matija Rijavec, Peter Korošec; Opis vira z dne 13. 8. 2021; Št. članka: 11; str. 1-11 Vol. 7 3 Aug. 2021 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 616.2 2054-7064 10.1186/s40733-021-00077-x 73007875 s40733-021-00077-x.pdf s40733-021-00077-x.pdf 1 6A3DE0C5C7A9EE5E9241A72D15B1875F c8dc330eef18630f7025553dd47f5a90f917f6af0201f689193e5c1440a1515c a9681d50-17b6-11ed-b6b8-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=17909 https://asthmarp.biomedcentral.com/track/pdf/10.1186/s40733-021-00077-x.pdf 1 https://dirros.openscience.si/Dokument.php?lang=slv&id=17910 Univerzitetna klinika za pljučne bolezni in alergijo Golnik 0 0 0