Literature DB >> 2235227

Predicting risk for bronchopulmonary dysplasia: selection criteria for clinical trials.

R A Sinkin1, C Cox, D L Phelps.   

Abstract

Early identification of neonates in whom bronchopulmonary dysplasia is most likely to develop permits appropriate enrollment into clinical trials testing early intervention therapies for the prevention or treatment of bronchopulmonary dysplasia. Analysis of 160 neonatal intensive care unit survivors to 28 days revealed that supplemental oxygen requirement at 28 days could be predicted by a logistic regression including (1) birth weight, gestational age, 5-minute Apgar score, and peak inspiratory pressure at 12 hours for 12-hour-old neonates and (2) birth weight, gestational age, peak inspiratory pressure at 12 hours, and mean airway pressure at 10 days for 10-day-old neonates. These two regression analyses were applied prospectively to three new data sets totaling 238 neonates to test their predictive ability. Neonates were classified into low-, moderate-, or high-risk groups on the basis of their predicted probability of requiring oxygen supplementation at 28 days; low = probability of less than 25%, moderate = probability of 25% to 75%, and high = probability greater than 75%. Although these populations were demographically distinct from the original group, the regression analyses performed well. The regression analysis for 12 hours of age classified 125 neonates at low risk of whom 9% required supplemental oxygen at 28 days, and the regression analysis for 10 days classified 141 neonates at low risk of whom 7% required supplemental oxygen. The 12-hour regression analysis classified 80 neonates at moderate risk of whom 33% required supplemental oxygen at 28 days and the 10-day regression analysis classified 49 neonates at moderate risk of whom 24% required supplemental oxygen.(ABSTRACT TRUNCATED AT 250 WORDS)

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Year:  1990        PMID: 2235227

Source DB:  PubMed          Journal:  Pediatrics        ISSN: 0031-4005            Impact factor:   7.124


  21 in total

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2.  Prolonged respiratory disorder predicts adverse prognosis in infants with end-stage kidney disease.

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3.  Pulmonary artery pressure: early predictor of chronic lung disease in preterm infants.

Authors:  N V Subhedar; A H Hamdan; S W Ryan; N J Shaw
Journal:  Arch Dis Child Fetal Neonatal Ed       Date:  1998-01       Impact factor: 5.747

4.  A scoring system to predict chronic oxygen dependency.

Authors:  Caroline May; Valia Kavvadia; Gabriel Dimitriou; Anne Greenough
Journal:  Eur J Pediatr       Date:  2006-08-08       Impact factor: 3.183

Review 5.  Prevention and management of bronchopulmonary dysplasia: Lessons learned from the neonatal research network.

Authors:  Kathleen A Kennedy; C Michael Cotten; Kristi L Watterberg; Waldemar A Carlo
Journal:  Semin Perinatol       Date:  2016-10       Impact factor: 3.300

Review 6.  Chronic lung disease of prematurity: are we too cautious with steroids?

Authors:  M Silverman
Journal:  Eur J Pediatr       Date:  1994       Impact factor: 3.183

7.  Reduction in the risk of bronchopulmonary dysplasia from 1980-1990: results of a multivariate logistic regression analysis.

Authors:  J D Corcoran; C C Patterson; P S Thomas; H L Halliday
Journal:  Eur J Pediatr       Date:  1993-08       Impact factor: 3.183

8.  Scoring method for early prediction of neonatal chronic lung disease using modified respiratory parameters.

Authors:  Young Don Kim; Ellen Ai-Rhan Kim; Ki Soo Kim; Soo Young Pi; Weechang Kang
Journal:  J Korean Med Sci       Date:  2005-06       Impact factor: 2.153

Review 9.  Biomarkers, Early Diagnosis, and Clinical Predictors of Bronchopulmonary Dysplasia.

Authors:  Charitharth Vivek Lal; Namasivayam Ambalavanan
Journal:  Clin Perinatol       Date:  2015-10-01       Impact factor: 3.430

10.  Pharmacokinetics of Budesonide Administered with Surfactant in Premature Lambs: Implications for Neonatal Clinical Trials.

Authors:  Jessica K Roberts; Chris Stockmann; Mar Janna Dahl; Kurt H Albertine; Edmund Egan; Zhenjian Lin; Christopher A Reilly; Philip L Ballard; Roberta A Ballard; Robert M Ward
Journal:  Curr Clin Pharmacol       Date:  2016
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