Predicting respiratory distress syndrome using gestational age and lamellar body count

Qiuhong Zhao, Zhen Zhao, Van Leung-Pineda, Carmen L. Wiley, Paul J. Nelson, David G. Grenache, Fred S. Apple, Amy K. Saenger, Ann M. Gronowski

Research output: Contribution to journalArticle

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Abstract

Objectives: To design a predictive model for assessing the risk of developing respiratory distress syndrome (RDS) using gestational age (GA) and lamellar body counts (LBC). Design and methods: LBCs and patient outcome data was obtained from five medical centers. A total of 223 patients were included in this study; 19 gave birth to infants that developed RDS, 204 gave birth to infants that were unaffected. The absolute risk and odds ratios of an infant developing RDS as a function of GA and LBC were calculated. Logistic analysis was used to model the odds of RDS as a function of GA and LBC. Results: The odds of RDS decreased for each increasing week of GA and decreased with increase in the LBC. GA-specific LBC cutoffs are provided for sensitivities between 84 and 100%. The bias adjusted area under the ROC curve for the classification of RDS, based on GA and LBC, was 0.906 using the logistic model and 0.746 using a single cutoff of LBC (50,000/μL) to classify immaturity. Conclusions: GA-specific risk assessment and GA-specific cutoffs provide increased sensitivity and specificity in the evaluation of fetal lung maturity.

Original languageEnglish
Pages (from-to)1228-1232
Number of pages5
JournalClinical Biochemistry
Volume46
Issue number13-14
DOIs
StatePublished - Sep 1 2013

Keywords

  • Fetal lung maturity
  • Gestational age
  • Lamellar body count
  • Respiratory distress syndrome
  • Sensitivity
  • Specificity

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    Zhao, Q., Zhao, Z., Leung-Pineda, V., Wiley, C. L., Nelson, P. J., Grenache, D. G., Apple, F. S., Saenger, A. K., & Gronowski, A. M. (2013). Predicting respiratory distress syndrome using gestational age and lamellar body count. Clinical Biochemistry, 46(13-14), 1228-1232. https://doi.org/10.1016/j.clinbiochem.2013.03.020