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- Title
儿童气管支气管异物临床特征、延迟诊断因素及并发症高危因素分析.
- Authors
陈进喜; 高平明; 林业辉; 张洁妍; 黄殷; 裴夫瑜
- Abstract
Objective: To explore the clinical characteristics, delayed diagnosis factors and complication risk factors of children with tracheobronchial foreign body. Methods: A total of 167 children with suspected tracheobronchial foreign bodies, admitted to our hospital from May 2014 to July 2022, were used as the study subjects. Among the 167 patients, 112 were male and 55 were female, with a mean age (25.10 ± 21.51) months. According to the results of bronchoscopy, the children were divided into foreign bodies (n=140) and non-foreign bodies (n=27). The child was divided into delayed diagnosis group (n=100) and early diagnosis group (n=40) according to whether the diagnosis time of the child was admitted within 24h. All children were divided into complications (n=122) and complications (n=18). Results: There were no significant differences between the foreign body group and the non-foreign body group in terms of gender, age, and time to see a doctor after onset (P>0.05). There were significant differences in the retention site, CRP, PCT, imaging at the first diagnosis, residence of the children and the history of foreign body inhalation(P>0.05). The multivariate logistics regression, with whether delayed diagnosis was the dependent variable, showed that age, imaging at first diagnosis, residence of the child, and history of foreign body inhalation were independent risk factors (P>0.05). The results of multifactorial logistic regression with the occurrence of complications as the dependent variable showed that age, imaging at the first visit, the child's place of residence, delayed diagnosis and history of foreign body aspiration were independent risk factors (P>0.05). Conclusion: Children with tracheobronchial foreign bodies have obvious age characteristics, delayed diagnosis and complications are affected by complex factors such as age, foreign body inhalation history and imaging examination.
- Subjects
FOREIGN bodies; DELAYED diagnosis; EARLY diagnosis; LOGISTIC regression analysis; DEPENDENT variables; RESPIRATORY aspiration; ASPIRATION pneumonia
- Publication
Progress in Modern Biomedicine, 2023, Vol 23, Issue 11, p2063
- ISSN
1673-6273
- Publication type
Article
- DOI
10.13241/j.cnki.pmb.2023.12.012