A computed tomography scoring system to assess pulmonary disease among premature infants

Abstract

CONTEXT AND OBJECTIVE: High-resolution computed tomography (HRCT) is considered to be the best method for detailed pulmonary evaluation. The aim here was to describe a scoring system based on abnormalities identified on HRCT among premature infants, and measure the predictive validity of the score in relation to respiratory morbidity during the first year of life. DESIGN AND SETTING: Prospective cohort study in Instituto Fernandes Figueira, Fundação Oswaldo Cruz. METHODS: Scoring system based on HRCT abnormalities among premature newborns. The affected lung area was quantified according to the number of compromised lobes, in addition to bilateral pulmonary involvement. Two radiologists applied the score to 86 HRCT scans. Intraobserver and interobserver agreement were analyzed. The score properties were calculated in relation to predictions of respiratory morbidity during the first year of life. RESULTS: Most of the patients (85%) presented abnormalities on HRCT, and among these, 56.2% presented respiratory morbidity during the first year of life. Scores ranged from zero to 12. There was good agreement between observers (intraclass correlation coefficient, ICC = 0.86, confidence interval, CI: 0.64-0.83). The predictive scores were as follows: positive predictive value 81.8%, negative predictive value 56.3%, sensitivity 39.1%, and specificity 90.0%. CONCLUSION: The scoring system is reproducible, easy to apply and allows HRCT comparisons among premature infants, by identifying patients with greater likelihood of respiratory morbidity during the first year of life. Its use will enable HRCT comparisons among premature infants with different risk factors for respiratory morbidity.