Identification of earlier predictors of pregnancy complications through wearable technologies in a Brazilian multicentre cohort : Maternal Actigraphy Exploratory Study I (MAES-I) study protocol

• Autor(a) principal: Souza, Renato Teixeira
• Data de Publicação: 2019
• Outros Autores: Cecatti, Jose Guilherme, Mayrink, Jussara, Galvão, Rafael Bessa, Costa, Maria Laura, Feitosa, Francisco Edson de Lucena, Rocha Filho, Edilberto Alves Pereira da, Leite, Debora Farias Batista, Vettorazzi, Janete, Tedesco, Ricardo Porto, Santana, Danielly S., Souza, João Paulo
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Institucional da UFRGS
• Texto Completo: http://hdl.handle.net/10183/220808
• topic: Prognóstico; Fatores de risco; Complicações na gravidez; Mulheres

Introduction Non-invasive tools capable of identifying predictors of maternal complications would be a step forward for improving maternal and perinatal health. There is an association between modification in physical activity (PA) and sleep–wake patterns and the occurrence of inflammatory, metabolic, pathological conditions related to chronic diseases. The actigraphy device is validated to estimate PA and sleep–wake patterns among pregnant women. In order to extend the window of opportunity to prevent, diagnose and treat specific maternal conditions, would it be possible to use actigraphy data to identify risk factors for the development of adverse maternal outcomes during pregnancy? Methods and analysis A cohort will be held in five centres from the Brazilian Network for Studies on Reproductive and Perinatal Health. Maternal Actigraphy Exploratory Study I (MAES-I) will enrol 400 low-risk nulliparous women who will wear the actigraphy device on their wrists day and night (24 hours/day) uninterruptedly from 19 to 21 weeks until childbirth. Changes in PA and sleep–wake patterns will be analysed throughout pregnancy, considering ranges in gestational age in women with and without maternal complications such as pre-eclampsia, preterm birth (spontaneous or provider-initiated), gestational diabetes, maternal haemorrhage during pregnancy, in addition to perinatal outcomes. The plan is to design a predictive model using actigraphy data for screening pregnant women at risk of developing specific adverse maternal and perinatal outcomes.