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J Hosp Med. 2014 Sep;9(9):559-64. doi: 10.1002/jhm.2227. Epub 2014 Jun 18.

Admission chest radiographs predict illness severity for children hospitalized with pneumonia.

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1
Monroe Carell Jr. Children's Hospital at Vanderbilt and the Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, Tennessee.

Abstract

OBJECTIVE:

To assess whether radiographic findings predict outcomes among children hospitalized with pneumonia.

METHODS:

This retrospective study included children <18 years of age from 4 children's hospitals admitted in 2010 with clinical and radiographic evidence of pneumonia. Admission radiographs were categorized as single lobar, unilateral or bilateral multilobar, or interstitial. Pleural effusions were classified as absent, small, or moderate/large. Propensity scoring was used to adjust for potential confounders, including need for supplemental oxygen, intensive care, and mechanical ventilation, as well as hospital length of stay and duration of supplemental oxygen.

RESULTS:

There were 406 children (median age, 3 years). Infiltrate patterns included: single lobar, 61%; multilobar unilateral, 13%; multilobar bilateral, 16%; and interstitial, 10%. Pleural effusion was present in 21%. Overall, 63% required supplemental oxygen (median duration, 31.5 hours), 8% required intensive care, and 3% required mechanical ventilation. Median length of stay was 51.5 hours. Compared with single lobar infiltrate, all other infiltrate patterns were associated with need for intensive care; only bilateral multilobar infiltrate was associated with need for mechanical ventilation (adjusted odds ratio [aOR]: 3.0, 95% confidence interval [CI]: 1.2-7.9). Presence of effusion was associated with increased length of stay and duration of supplemental oxygen; only moderate/large effusion was associated with need for intensive care (aOR: 3.2, 95% CI: 1.1-8.9) and mechanical ventilation (aOR: 14.8, 95% CI: 9.8-22.4).

CONCLUSIONS:

Admission radiographic findings are associated with important hospital outcomes and care processes and may help predict disease severity.

PMID:
24942619
PMCID:
PMC4154996
DOI:
10.1002/jhm.2227
[Indexed for MEDLINE]
Free PMC Article
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