Decoding neonatal chest radiographic patterns of disease: retrospective analysis from a tertiary care hospital

Authors

DOI:

https://doi.org/10.18203/2320-6012.ijrms20185096

Keywords:

Bronchiolitis, Chest radiograph, Neonatal respiratory distress, Respiratory distress syndrome

Abstract

Background: To evaluate chest radiographic patterns in neonatal respiratory distress using a predesigned performa and algorithm and to correlate results with the clinical diagnosis.

Methods: A retrospective review was done of bedside chest radiographs acquired over a month for respiratory distress from the neonatal intensive care unit. The radiographs were systematically evaluated according to a predesigned performa and algorithm. A presumptive radiographic diagnosis was assigned to each patient based on the combination of radiographic features. Radiographic diagnosis was compared with the clinical diagnosis. The most important diagnostic features were outlined.

Results: The radiographic diagnosis correlated with clinical diagnosis in 93.3% of cases. Most common radiographic feature was pulmonary air space opacity (n=21). Air space opacity without any mediastinal shift in absence of any compensatory factors was a reliable diagnostic feature for pneumonic consolidation, which was the most common diagnosis (n=10). Bilateral granular lung fields were a specific indicator of respiratory distress syndrome. Flattening of domes of diaphragm was the most frequent feature for hyperinflation. Bilateral hyperinflation could be accurately used to diagnose bronchiolitis in all but one case (n=4/5). Pleural complications were accurately diagnosed.

Conclusions: Systematic evaluation of neonatal chest radiographic patterns of disease has a high diagnostic accuracy.

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Published

2018-12-26

How to Cite

Ghasi, R. G. (2018). Decoding neonatal chest radiographic patterns of disease: retrospective analysis from a tertiary care hospital. International Journal of Research in Medical Sciences, 7(1), 77–84. https://doi.org/10.18203/2320-6012.ijrms20185096

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Original Research Articles