Follow-up after very preterm birth in Europe

• Main Author: Seppänen, AV
• Publication Date: 2022
• Other Authors: Draper, ES, Petrou, S, Barros, H, Andronis, L, Kim, SW, Maier, RF, Pedersen, P, Gadzinowski, J, Lebeer, J, Ådén, U, Toome, L, van Heijst, AFJ, Cuttini, M, Zeitlin, J, SHIPS Research Group
• Format: Other
• Language: eng
• Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Download full: https://hdl.handle.net/10216/151696
• topic: epidemiology; health services research; neonatology

Follow-up programmes aim to detect neurodevelopmental and health problems and enable early interventions for children born very preterm (<32 weeks of gestational age (GA)). Although the importance of postdischarge follow-up is widely acknowledged, recommendations differ regarding eligibility criteria, frequency, duration and content, especially for follow-up beyond early childhood.1–3 We used data from a European cohort of children born very preterm to describe the use of routine follow-up services until 5 years of age. The data were collected for the Effective Perinatal Intensive care in Europe and Screening to Improve Health in Very Preterm Infants studies, which constituted and followed up an area-based cohort of children born very preterm in 2011/2012 in 19 regions across 11 European countries.4 Perinatal data were collected from obstetric and neonatal records, and parents completed questionnaires at 2 and 5 years of age. Out of 7900 live births, 6792 were discharged from neonatal care, of whom 6759 were alive at 5 years and 3635 (53.8%) participated in the study. Based on a question on the use of routine follow-up services for children born very preterm in the 5-year parental questionnaire, we classified children as having never used follow-up, no longer using follow-up or still using follow-up services. We described associations with family sociodemographic characteristics and perinatal risks and estimated adjusted risks using multinomial regression models with robust variance estimators for clustered samples and inverse probability weights using baseline characteristics to account for study attrition bias.4