Am J Perinatol 2016; 33(06): 569-576
DOI: 10.1055/s-0035-1569989
Original Article
Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Infant Outcomes after Periviable Birth: External Validation of the Neonatal Research Network Estimator with the BEAM Trial

Caroline C. Marrs
1   Division of Maternal-Fetal Medicine, University of Texas Medical Branch, Galveston, Texas
,
Claudia Pedroza
2   Center for Clinical Research and Evidence-Based Medicine, University of Texas Medical School, Houston, Texas
,
Hector Mendez-Figueroa
3   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, UT Health Science Center at Houston, Houston, Texas
,
Suneet P. Chauhan
3   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, UT Health Science Center at Houston, Houston, Texas
,
Jon E. Tyson
2   Center for Clinical Research and Evidence-Based Medicine, University of Texas Medical School, Houston, Texas
› Author Affiliations
Further Information

Publication History

07 July 2015

26 October 2015

Publication Date:
21 December 2015 (online)

Abstract

Objective The objective of this study was to use data from the 20-center beneficial effect of antenatal magnesium sulfate (BEAM) trial to assess the external validity of the Neonatal Research Network (NRN) estimator, a widely employed web-based counseling tool to estimate the probability of an adverse outcome for periviable infants given intensive care.

Study Design The probability of different adverse outcomes predicted from the NRN estimator was compared with observed rates at 18 to 22 months for ventilated, nonanomalous infants born at 23 to 25 weeks and assessed in BEAM as in the NRN. Results were assessed using rigorous validation methods for prediction models.

Results Among 289 eligible infants, 26% died, 40% died or had profound neurodevelopmental impairment (PNDI), and 71% died or had NDI. The area under the receiver operating characteristic curve was 0.70 (95% confidence interval [CI], 0.63–0.78) for death, 0.64 (95% CI, 0.56–0.71) for death or NDI, and 0.71 (95% CI, 0.65–0.78) for death or PNDI. Observed and predicted rates were somewhat different for death or NDI but quite similar for death and for death or PNDI in different risk groups. Brier scores for accuracy were favorable (0.17–0.22) for all outcomes.

Conclusion Our results provide external validation of the NRN estimator for assessing the probability of adverse outcomes at 18 to 22 months for periviable infants given intensive care.

 
  • References

  • 1 Raju TN, Mercer BM, Burchfield DJ, Joseph Jr GF. Periviable birth: executive summary of a joint workshop by the Eunice Kennedy Shriver National Institute of Child Health and Human Development, Society for Maternal-Fetal Medicine, American Academy of Pediatrics, and American College of Obstetricians and Gynecologists. Am J Obstet Gynecol 2014; 210 (5) 406-417
  • 2 Tyson JE, Parikh NA, Langer J, Green C, Higgins RD ; National Institute of Child Health and Human Development Neonatal Research Network. Intensive care for extreme prematurity—moving beyond gestational age. N Engl J Med 2008; 358 (16) 1672-1681
  • 3 American College of Obstetricians and Gynecologists. ACOG Practice Bulletin: Clinical Management Guidelines for Obstetricians Gynecologists: Number 38, September 2002. Perinatal care at the threshold of viability. Obstet Gynecol 2002; 100: 617-624
  • 4 Jefferies AL, Kirpalani HM ; Canadian Paediatric Society Fetus and Newborn Committee. Counselling and management for anticipated extremely preterm birth. Paediatr Child Health (Oxford) 2012; 17 (8) 443-446
  • 5 D'Onofrio BM, Class QA, Rickert ME, Larsson H, Långström N, Lichtenstein P. Preterm birth and mortality and morbidity: a population-based quasi-experimental study. JAMA Psychiatry 2013; 70 (11) 1231-1240
  • 6 Costeloe KL, Hennessy EM, Haider S, Stacey F, Marlow N, Draper ES. Short term outcomes after extreme preterm birth in England: comparison of two birth cohorts in 1995 and 2006 (the EPICure studies). BMJ 2012; 345: e7976
  • 7 Bader D, Kugelman A, Boyko V , et al; Israel Neonatal Network. Risk factors and estimation tool for death among extremely premature infants: a national study. Pediatrics 2010; 125 (4) 696-703
  • 8 Effect of corticosteroids for fetal maturation on perinatal outcomes. NIH Consens Statement 1994; 12 (2) 1-24
  • 9 NICHD Neonatal Research Network (NRN). Extremely Preterm Birth Outcome Data. http://www.nichd.nih.gov/about/org/der/branches/ppb/programs/epbo/pages/epbo_case.aspx . Last assessed date September 21 2015
  • 10 Kramer MS, McLean FH, Boyd ME, Usher RH. The validity of gestational age estimation by menstrual dating in term, preterm, and postterm gestations. JAMA 1988; 260 (22) 3306-3308
  • 11 Gjessing HK, Skjaerven R, Wilcox AJ. Errors in gestational age: evidence of bleeding early in pregnancy. Am J Public Health 1999; 89 (2) 213-218
  • 12 Collins GS, Moons KG. Comparing risk prediction models. BMJ 2012; 344: e3186
  • 13 Lee HC, Green C, Hintz SR , et al. Prediction of death for extremely premature infants in a population-based cohort. Pediatrics 2010; 126 (3) e644-e650
  • 14 Rouse DJ, Hirtz DG, Thom E , et al; Eunice Kennedy Shriver NICHD Maternal-Fetal Medicine Units Network. A randomized, controlled trial of magnesium sulfate for the prevention of cerebral palsy. N Engl J Med 2008; 359 (9) 895-905
  • 15 Saigal S, Stoskopf B, Streiner D , et al. Transition of extremely low birth weight infants from adolescence to adulthood. Comparison with normal birthweight controls. JAMA 2006; 295: 667-675
  • 16 Saigal S. Preemie Voices. Victoria, British Columbia: Friesen Press; 2014
  • 17 Steyerberg EW, Borsboom GJ, van Houwelingen HC, Eijkemans MJ, Habbema JD. Validation and updating of predictive logistic regression models: a study on sample size and shrinkage. Stat Med 2004; 23 (16) 2567-2586
  • 18 Altman DG, Vergouwe Y, Royston P, Moons KGM. Prognosis and prognostic research: validating a prognostic model. BMJ 2009; 338: b605
  • 19 Steyerberg EW, Vickers AJ, Cook NR , et al. Assessing the performance of prediction models: a framework for traditional and novel measures. Epidemiology 2010; 21 (1) 128-138
  • 20 Collins GS, Reitsma JB, Altman DG, Moons KG. Transparent reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): the TRIPOD statement. Ann Intern Med 2015; 162 (1) 55-63
  • 21 Moons KG, Altman DG, Reitsma JB , et al. Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD): explanation and elaboration. Ann Intern Med 2015; 162 (1) W1-W73
  • 22 Creinin MD, Keverline S, Meyn LA. How regular is regular? An analysis of menstrual cycle regularity. Contraception 2004; 70 (4) 289-292
  • 23 Fehring RJ, Schneider M, Raviele K. Variability in the phases of the menstrual cycle. J Obstet Gynecol Neonatal Nurs 2006; 35 (3) 376-384
  • 24 Ethridge Jr JK, Louis JM, Mercer BM. Accuracy of fetal weight estimation by ultrasound in periviable deliveries. J Matern Fetal Neonatal Med 2014; 27 (6) 557-560
  • 25 Chauhan SP, Hendrix NW, Magann EF, Morrison JC, Scardo JA, Berghella V. A review of sonographic estimate of fetal weight: vagaries of accuracy. J Matern Fetal Neonatal Med 2005; 18 (4) 211-220