2021
DOI: 10.1002/ppul.25603
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Family history of asthma influences outpatient respiratory outcomes in children with BPD

Abstract: Introduction Preterm children with bronchopulmonary dysplasia (BPD) are at increased risk for intermittent and chronic respiratory symptoms during childhood and adult life. Identifying children at higher risk for respiratory morbidities in the outpatient setting could help improve long‐term outcomes. In this study, we hypothesized that a family history of asthma (FHA) is a risk factor for higher acute care usage and respiratory symptoms in preterm infants/children with BPD, following initial discharge home. Me… Show more

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Cited by 5 publications
(3 citation statements)
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“…Conversely, BPD control could also be influenced by genetic factors, such as a family history of asthma. 27 Further work is needed to assess the outpatient influences on preterm respiratory disease.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Conversely, BPD control could also be influenced by genetic factors, such as a family history of asthma. 27 Further work is needed to assess the outpatient influences on preterm respiratory disease.…”
Section: Discussionmentioning
confidence: 99%
“…However, disease that was partially or not controlled based on sum scores was not associated with any of the demographic factors assessed; this may potentially suggest that other outpatient factors, such as daycare attendance, 21,22 secondhand smoke exposure, 23,24 or exposure to air pollution, 25,26 could play a larger role in disease control than the demographic or clinical characteristics assessed. Conversely, BPD control could also be influenced by genetic factors, such as a family history of asthma 27 . Further work is needed to assess the outpatient influences on preterm respiratory disease.…”
Section: Discussionmentioning
confidence: 99%
“…Previous studies have reported that early childhood wheezing is associated with antenatal maternal smoking, atopy, male sex, breastfeeding and other exposure factors ( 24 , 25 ). In the present study, we used machine-learning algorithms to assess the relative significance of various factors on inhaler use.…”
Section: Discussionmentioning
confidence: 99%