Objective : to evaluate the effect of prenatal care (PC) on perinatal outcomes of pregnant women with diabetes mellitus (DM). Methods : systematic review developed according to Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 guidelines and conducted through the population, intervention, control, and outcomes (PICO) strategy. Clinical trials and observational studies were selected, with adult pregnant women, single-fetus pregnancy, diagnosis of DM, or gestational DM and who had received PC and/or nutritional therapy (NT). The search was carried out in PubMed, Scopus, and BIREME databases. The quality of the studies was evaluated using the tools of the National Heart, Lung and Blood Institute-National Institutes of Health (NHLBI-NIH). Results : We identified 5972 records, of which 15 (n=47 420 pregnant women) met the eligibility criteria. The most recurrent outcomes were glycemic control (14 studies; n=9096 participants), hypertensive disorders of pregnancy (2; n=39 282), prematurity (6; n=40 163), large for gestational age newborns (4; n=1556), fetal macrosomia (birth weight >4kg) (6; n=2980) and intensive care unit admission (4; n=2022). Conclusions : The findings suggest that PC interferes with the perinatal outcome, being able to reduce the risks of complications associated with this comorbidity through early intervention, especially when the NT is an integral part of this assistance.
Keyphrases
- pregnant women
- glycemic control
- gestational age
- birth weight
- pregnancy outcomes
- systematic review
- type diabetes
- quality improvement
- preterm birth
- intensive care unit
- healthcare
- clinical trial
- meta analyses
- blood glucose
- randomized controlled trial
- weight gain
- palliative care
- emergency department
- public health
- preterm infants
- pain management
- atrial fibrillation
- mental health
- young adults
- physical activity
- risk assessment
- social media
- climate change
- adipose tissue
- risk factors
- tyrosine kinase
- blood pressure
- low birth weight
- deep learning
- metabolic syndrome
- case control
- open label
- health information
- double blind
- bone marrow