International Journal of Preventive Medicine (Jan 2018)

Comparative effectiveness of prophylactic therapies for necrotizing enterocolitis in preterm infants: Protocol for a network meta-analysis of randomized trials

  • Behnam Sadeghirad,
  • Ivan D Florez,
  • Yaping Chang,
  • Farid Forutan,
  • Dena Zeraatkar,
  • Rebecca L Morgan,
  • Shaneela Shahid,
  • Malgorzata M Bala,
  • Joseph Beyene,
  • Martin Offringa,
  • Thomasin Adams-Webber,
  • Philip M Sherman,
  • Enas El-Gouhary,
  • Gordon H Guyatt,
  • Bradley C Johnston

DOI
https://doi.org/10.4103/ijpvm.IJPVM_328_17
Journal volume & issue
Vol. 9, no. 1
pp. 83 – 83

Abstract

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Necrotizing enterocolitis (NEC) is a common and devastating disease with high morbidity and mortality in premature infants. Current literature on the prevention of NEC has limitations including lack of direct and indirect comparisons of available therapies. We will search MEDLINE, EMBASE, Science Citation Index Expanded, Social Sciences Citation Index, CINAHL, Scopus, ProQuest Dissertations and Theses database, and grey literature sources to identify eligible trials evaluating NEC preventive therapies. Eligible studies will (1) enroll preterm (gestational age <37 weeks) and/or low birth weight (birth weight <2500 g) infants, (2) randomize infants to any preventive intervention or a placebo, or alternative active or nonactive intervention. Our outcomes of interest are severe NEC (stage II or more, based on Bell's criteria), all-cause mortality, NEC-related mortality, late-onset sepsis, duration of hospitalization, weight gain, time to establish full enteral feeds, and treatment-related adverse events. Two reviewers will independently screen trials for eligibility, assess risk of bias, and extract data. All discrepancies will be resolved by discussion. We will specify a priori explanations for heterogeneity between studies. For available comparisons between treatment and no treatment, and direct comparisons of treatments, we will conduct conventional meta-analysis using a random effects model. We will conduct a network meta-analysis using a random effects model within the Bayesian framework using Markov chain Monte Carlo methods to assess relative effects of eligible interventions. We will assess the certainty in direct, indirect, and network estimates using the Grading of Recommendations Assessment, Development and Evaluation approach. Ethics and Dissemination: We will disseminate our findings through a peer-reviewed publication and conference presentations.

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