A validated clinical model to predict the need for admission and length of stay in children with acute bronchiolitis

OBJECTIVE:To develop and validate a logistic regression model to predict need for admission and length of hospital stay in children presenting to the Emergency Department with bronchiolitis. SETTING:Two childrenʼs hospitals in Dublin, Ireland. METHODS:We reviewed 118 episodes of bronchiolitis in 99...

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Veröffentlicht in:European journal of emergency medicine 2004-10, Vol.11 (5), p.265-272
Hauptverfasser: Walsh, Paul, Rothenberg, Stephen J, OʼDoherty, Sinead, Hoey, Hilary, Healy, Roisin
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Sprache:eng
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Zusammenfassung:OBJECTIVE:To develop and validate a logistic regression model to predict need for admission and length of hospital stay in children presenting to the Emergency Department with bronchiolitis. SETTING:Two childrenʼs hospitals in Dublin, Ireland. METHODS:We reviewed 118 episodes of bronchiolitis in 99 children admitted from the Emergency Department. Those discharged within 24 h by a consultant/attending paediatrician were retrospectively categorized as suitable for discharge. We then validated the model using a cohort of 182 affected infants from another paediatric Emergency Department in a bronchiolitis season 2 years later. In the validation phase actual admission, failed discharge, and age less than 2 months defined the need for admission. RESULTS:The model predicted admission with 91% sensitivity and 83% specificity in the validation cohort. Age [odds ratio (OR) 0.86, 95% confidence interval (CI) 0.76–0.97], dehydration (OR 2.54, 95% CI 1.34–4.82), increased work of breathing (OR 3.39, 95% CI 1.29–8.92) and initial heart rate above the 97th centile (OR 3.78, 95% CI 1.05–13.57) predicted the need for admission and a longer hospital stay. CONCLUSION:We derived and validated a severity of illness model for bronchiolitis. This can be used for outcome prediction in decision support tools or severity of illness stratification in research/audit.
ISSN:0969-9546
1473-5695
DOI:10.1097/00063110-200410000-00005