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1.
Hereditary angioedema due to C1-inhibitor deficiency in pediatric patients in Croatia : first national study, diagnostic and prophylactic challenges
Ljerka Karadža-Lapić, Marko Barešić, Renata Vrsalović, Irena Ivković-Jureković, Saša Sršen, Ingrid Prkačin, Matija Rijavec, Draško Cikojević, 2019

Povzetek: Hereditary angioedema (HAE) is a rare autosomal dominant disease with deficiency (type I) or dysfunction (type II) of C1 inhibitor, caused by mutations in the C1-INH gene, characterized by recurrent submucosal or subcutaneous edemas including skin swelling, abdominal pain and life-threatening episodes of upper airway obstruction. The aim of this study was to investigate healthcare experiences in children with HAE due to C1 inhibitor deficiency (C1-INH-HAE) in Croatia in order to estimate the number of affected children and to recommend management protocols for diagnosis, short-term prophylaxis and acute treatment. Patients were recruited during a 4-year period at five hospitals in Croatia. Complement testing was performed in patients with a positive family history. This pilot study revealed nine pediatric patients positive for C1-INH- HAE type I, aged 1-16 years, four of them asymptomatic. Before the age of one year, C1-INH levels may be lower than in adults; it is advisable to confirm C1-INH-HAE after the age of one year. Plasma-derived C1- INH is recommended as acute and short-term prophylactic treatment. Recombinant C1-INH and icatibant are licensed for the acute treatment of pediatric patients. In Croatia, HAE is still underdiagnosed in pediatric population.
Ključne besede: hereditary angioedemas -- genetics -- Croatia, inborn genetic diseases -- Croatia, pediatrics -- Croatia, C1 inhibitor, SERPING1 gene, children
DiRROS - Objavljeno: 16.12.2020; Ogledov: 478; Prenosov: 359
.pdf Celotno besedilo (477,81 KB)

2.
Treatment outcome clustering patterns correspond to discrete asthma phenotypes in children
Ivana Banić, Mario Lovrić, Gerald Cuder, Roman Kern, Matija Rijavec, Peter Korošec, Mirjana Kljajić-Turkalj, 2021

Povzetek: 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.
Ključne besede: asthma, allergy and immunology, pediatrics, machine learning, treatment outcome, phenotypes, childhood asthma, clustering
DiRROS - Objavljeno: 16.08.2021; Ogledov: 109; Prenosov: 67
.pdf Celotno besedilo (1,32 MB)

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