title: Chest radiological patterns predict the duration of mechanical ventilation in children with RSV infection.
abstract: BACKGROUND
  RSV-infected children demonstrate various radiographic features, some of which are associated with worse clinical outcomes.
  
  
  OBJECTIVE
  To investigate whether specific chest radiological patterns in RSV-infected children with acute respiratory failure (ARF) in the peri-intubation period are associated with prolonged duration of mechanical ventilation.
  
  
  METHODS
  We included RSV-infected children <1 year of age admitted with ARF from 1996 through 2002 to the pediatric intensive care unit at Massachusetts General Hospital. Their chest radiographs were evaluated at three time-points: preintubation (day -1) and days 1 and 2 after intubation. Univariate and multiple logistic regressions models were utilized to investigate our objective.
  
  
  RESULTS
  The study included 46 children. Using day 1 chest radiograph findings to predict duration of mechanical ventilation of >8 days, a backward stepwise regression arrived at a model that included age and right and left lung atelectasis. Using day 2 chest radiograph results, the best model included age and left lung atelectasis. A model combining the two days' findings yielded an area under the ROC curve of 0.92 with a satisfactory fit (P = 0.95).
  
  
  CONCLUSIONS
  Chest radiological patterns around the time of intubation can identify children with RSV-associated ARF who would require prolonged mechanical ventilation.
authors.affiliation: Division of Pediatric Critical Care and Cardiology, College of Medicine, University of Arkansas for Medical Sciences, Little Rock, AR, USA.
authors.forename: Parthak
authors.initials: P
authors.lastname: Prodhan
authors.forename: Sjirk J
authors.initials: SJ
authors.lastname: Westra
authors.forename: James
authors.initials: J
authors.lastname: Lin
authors.forename: Sarit
authors.initials: S
authors.lastname: Karni-Sharoor
authors.forename: Susan
authors.initials: S
authors.lastname: Regan
authors.forename: Natan
authors.initials: N
authors.lastname: Noviski
mesh_terms: D000465:Algorithms; D015331:Cohort Studies; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D011379:Prognosis; D013902:Radiography, Thoracic / Q000379:methods*; D015203:Reproducibility of Results; D012121:Respiration, Artificial; D018357:Respiratory Syncytial Virus Infections / Q000000981:diagnostic imaging* / Q000534:rehabilitation*; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D013813:Therapy, Computer-Assisted / Q000379:methods*