Clinical characteristics of children with asthma exacerbations: A cross-sectional descriptive study.
Ezgi CayVeysel KarakulakAhmet SezerHuseyin BaspinarNilgun BaharBusra Hatice FidanMahir SerbesSevcan BilenSevinc Puren YucelDilek OzcanDerya Ufuk AltintasPublished in: The Journal of asthma : official journal of the Association for the Care of Asthma (2024)
Aim: In this cross-sectional descriptive study, we aimed to determine the clinical characteristics of children admitted to a tertiary hospital with asthma exacerbations in a city in southern Turkey where aeroallergens are common and to determine how these characteristics affect the severity of exacerbations. Methods: Data from a cross-sectional analysis of children with asthma exacerbations who were followed up at the Cukurova University Medical Faculty Pediatric Emergency Department (ED) and Pediatric Allergy & Immunology inpatient clinic were retrospectively analyzed. The study included 106 children who were diagnosed with asthma and did not have any additional comorbidities. In a comparative analysis, the clinical characteristics and laboratory parameters of children with mild/moderate and severe exacerbations were examined. Results: While 81.1% of the patients had mild/moderate exacerbation, 18.8% had severe exacerbation. Additional atopic disease, Alternaria positivity in the skin prick test, the frequency of exacerbations in the previous year, S. pneumoniae infection, and the rate of noncompliance with treatment were significantly higher in children with severe asthma exacerbations. PEF, FEV1, and FEV1/FVC values were considerably lower in patients with severe exacerbations. Conclusions: Bacterial infections, presence of atopic disease, Alternaria exposure, low spirometric measures, number of exacerbations in the previous year, and low rate of treatment adherence may be relevant in predicting the severity of asthma exacerbations.
Keyphrases
- chronic obstructive pulmonary disease
- lung function
- cystic fibrosis
- emergency department
- young adults
- healthcare
- early onset
- mental health
- primary care
- palliative care
- machine learning
- acute respiratory distress syndrome
- combination therapy
- electronic health record
- soft tissue
- insulin resistance
- wound healing
- medical students
- extracorporeal membrane oxygenation
- acute care