The Risk Factors and Prediction Models of Preterm Birth: An Update Systematic Literature Review
Keywords:Preterm Birth, Preterm Delivery, Risk Factors, Determinant, Prediction Model
Background: Every year there is an increase in preterm births in the world, and for this condition, Indonesia
occupies the highest position in ASEAN, with 15.5% of live births. The purpose of this study is to find for
risk factors and prediction models to detect preterm birth.
Method: This study is conducted in multistage process following PRISMA guidelines with the inclusion
criteria as follow, a) search for academic journals in the online database of ProQuest, Ebsco, PubMed,
SpringerLink and Science Direct, b) publications in the last 10 years (2009-2019), c) articles in English,
and d) the article contains outcome in the form of risk factors and prediction models for preterm birth e) the
population is pregnant women suspected of having risk factors for preterm birth.
Results: From the 1767 articles found in 5 online databases, only 16 articles fall into the PICOS categories
and are discussed in this paper. This study identified some of the most dominant risk factors for the incidence
of preterm birth, including demographic and socioeconomic, behavioral characteristics/life style, maternal
health/chronic conditions, current fetal conditions/pregnancy characteristics, pregnancy history/genetic
characteristics, biological characteristics and others. This study concludes that maternal age and previous
preterm birth are the factors that always used by the researchers. For the prediction of preterm birth, many
researchers include cervical length as a predictor.
Conclusions: Previous researches were more still focused on risk factors and not much about prediction
models. Therefore, this study suggests that the upcoming research should put more emphasis on risk
prediction model for detecting preterm birth.
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