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Association of urinary iodine concentration in pregnancy with maternal and neonatal outcomes: a systematic review

Grant number: 20/09621-1
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Effective date (Start): December 01, 2020
Effective date (End): November 30, 2021
Field of knowledge:Health Sciences - Medicine - Medical Clinics
Principal Investigator:Vania dos Santos Nunes Nogueira
Grantee:Maryan Borcsik Marum
Host Institution: Faculdade de Medicina (FMB). Universidade Estadual Paulista (UNESP). Campus de Botucatu. Botucatu , SP, Brazil

Abstract

Urinary iodine concentration is used as an indicator of iodine deficiency in pregnant women. However, there is not enough evidence if these laboratorial results have relationship with important maternal, neonatal and infant outcomes. Objectives: This study aims to evaluate if low levels of urinary iodine concentrations in pregnant women, when compared with normal levels, are associated to prejudice on maternal, neonatal and infant outcomes. Methods: A systematic literature review will be carried out according to the methodology of the Joanna Brigs Institute (JBI) to risk and etiology studies. We will include prospective cohort studies in which pregnant women with low urinary iodine concentration were compared to pregnant women with normal urinary iodine concentration. The maternal primary outcomes analysed will be hypothyroidism and preterm birth; the neonatal/infant will be perinatal mortality, low birthweight, neonatal hypothyroidism or elevated thyroid-stimulating hormone (TSH). Four general and adaptive search strategies have been created for the following electronic health databases: Embase, Medline and LILACS. The selection process, data extraction and evaluation of the risk of bias will be carried out independently by two reviewers. The risk of bias will be assessed according to the JBI instrument for evaluating risk of bias in etiology and risk studies. Similar outcomes measured in at least two trials will be plotted in the meta-analysis using the software JBI SUMARI. The analysis model in the meta-analysis will be random effects. The quality of the evidence will be generated according to the GRADE (Grading of Recommendations Assessment, Development, and Evaluation). (AU)

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