TY - JOUR
T1 - A Systematic Review of Placental Biomarkers Predicting Small-for-Gestational-Age Neonates
AU - Ruchob, Rungnapa
AU - Rutherford, Julienne N.
AU - Bell, Aleeca F.
N1 - Publisher Copyright:
© 2018, © The Author(s) 2018.
PY - 2018/5/1
Y1 - 2018/5/1
N2 - Background: Neonates born small for gestational age (SGA) face increased risk of neonatal mortality, childhood developmental problems, and adult disease. The placenta is a key factor in SGA development because of its multiple biological processes that underlie fetal growth. However, valid and reliable placental biomarkers of SGA have not been determined. Objectives: The objective of this article was to systematically identify and review studies examining associations between placental biomarkers and SGA and assess those biomarkers’ predictive value. Methods: Use of the matrix method and the PRISMA guidelines ensured systematic identification of relevant articles based on selection criteria. PubMed, CINAHL, and EMBASE were searched for English articles published in 2005–2016 that addressed relationships between placental biomarkers and SGA. Results: The search captured 466 articles; 13 met selection criteria. The review identified 14 potential placental biomarkers for SGA, with placental growth factor and soluble fms-like tyrosine kinase 1 being the most commonly studied. However, findings for these and other biomarkers have often been contradictory. Thus, no placental biomarkers have been confirmed as reliable for predicting SGA. Conclusion: The inconsistent findings suggest low placental biomarker reliability, perhaps due to the multifactorial nature of SGA. This review is novel in its focus on identifying potential placental biomarkers for SGA, producing a better understanding of how placental function underlies fetal growth. Nevertheless, use of placental biomarkers alone may not be adequate for predicting SGA. Therefore, combinations of biomarkers and other predictive tests should be evaluated for their ability to predict risk of SGA.
AB - Background: Neonates born small for gestational age (SGA) face increased risk of neonatal mortality, childhood developmental problems, and adult disease. The placenta is a key factor in SGA development because of its multiple biological processes that underlie fetal growth. However, valid and reliable placental biomarkers of SGA have not been determined. Objectives: The objective of this article was to systematically identify and review studies examining associations between placental biomarkers and SGA and assess those biomarkers’ predictive value. Methods: Use of the matrix method and the PRISMA guidelines ensured systematic identification of relevant articles based on selection criteria. PubMed, CINAHL, and EMBASE were searched for English articles published in 2005–2016 that addressed relationships between placental biomarkers and SGA. Results: The search captured 466 articles; 13 met selection criteria. The review identified 14 potential placental biomarkers for SGA, with placental growth factor and soluble fms-like tyrosine kinase 1 being the most commonly studied. However, findings for these and other biomarkers have often been contradictory. Thus, no placental biomarkers have been confirmed as reliable for predicting SGA. Conclusion: The inconsistent findings suggest low placental biomarker reliability, perhaps due to the multifactorial nature of SGA. This review is novel in its focus on identifying potential placental biomarkers for SGA, producing a better understanding of how placental function underlies fetal growth. Nevertheless, use of placental biomarkers alone may not be adequate for predicting SGA. Therefore, combinations of biomarkers and other predictive tests should be evaluated for their ability to predict risk of SGA.
KW - biomarkers
KW - intrauterine growth restriction
KW - neonate
KW - placenta
KW - small for gestational age
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U2 - 10.1177/1099800418760997
DO - 10.1177/1099800418760997
M3 - Article
C2 - 29490471
AN - SCOPUS:85045298190
SN - 1099-8004
VL - 20
SP - 272
EP - 283
JO - Biological Research For Nursing
JF - Biological Research For Nursing
IS - 3
ER -