A first trimester prediction model for large for gestational age infants: a preliminary study.
Biochemical markers
Biophysical markers
First trimester
LGA
Prediction model
Journal
BMC pregnancy and childbirth
ISSN: 1471-2393
Titre abrégé: BMC Pregnancy Childbirth
Pays: England
ID NLM: 100967799
Informations de publication
Date de publication:
24 Sep 2021
24 Sep 2021
Historique:
received:
06
04
2021
accepted:
10
09
2021
entrez:
25
9
2021
pubmed:
26
9
2021
medline:
1
1
2022
Statut:
epublish
Résumé
Large for gestational age infants (LGA) have increased risk of adverse short-term perinatal outcomes. This study aims to develop a multivariable prediction model for the risk of giving birth to a LGA baby, by using biochemical, biophysical, anamnestic, and clinical maternal characteristics available at first trimester. Prospective study that included all singleton pregnancies attending the first trimester aneuploidy screening at the Obstetric Unit of the University Hospital of Modena, in Northern Italy, between June 2018 and December 2019. A total of 503 consecutive women were included in the analysis. The final prediction model for LGA, included multiparity (OR = 2.8, 95% CI: 1.6-4.9, p = 0.001), pre-pregnancy BMI (OR = 1.08, 95% CI: 1.03-1.14, p = 0.002) and PAPP-A MoM (OR = 1.43, 95% CI: 1.08-1.90, p = 0.013). The area under the ROC curve was 70.5%, indicating a satisfactory predictive accuracy. The best predictive cut-off for this score was equal to - 1.378, which corresponds to a 20.1% probability of having a LGA infant. By using such a cut-off, the risk of LGA can be predicted in our sample with sensitivity of 55.2% and specificity of 79.0%. At first trimester, a model including multiparity, pre-pregnancy BMI and PAPP-A satisfactorily predicted the risk of giving birth to a LGA infant. This promising tool, once applied early in pregnancy, would identify women deserving targeted interventions. ClinicalTrials.gov NCT04838431 , 09/04/2021.
Sections du résumé
BACKGROUND
BACKGROUND
Large for gestational age infants (LGA) have increased risk of adverse short-term perinatal outcomes. This study aims to develop a multivariable prediction model for the risk of giving birth to a LGA baby, by using biochemical, biophysical, anamnestic, and clinical maternal characteristics available at first trimester.
METHODS
METHODS
Prospective study that included all singleton pregnancies attending the first trimester aneuploidy screening at the Obstetric Unit of the University Hospital of Modena, in Northern Italy, between June 2018 and December 2019.
RESULTS
RESULTS
A total of 503 consecutive women were included in the analysis. The final prediction model for LGA, included multiparity (OR = 2.8, 95% CI: 1.6-4.9, p = 0.001), pre-pregnancy BMI (OR = 1.08, 95% CI: 1.03-1.14, p = 0.002) and PAPP-A MoM (OR = 1.43, 95% CI: 1.08-1.90, p = 0.013). The area under the ROC curve was 70.5%, indicating a satisfactory predictive accuracy. The best predictive cut-off for this score was equal to - 1.378, which corresponds to a 20.1% probability of having a LGA infant. By using such a cut-off, the risk of LGA can be predicted in our sample with sensitivity of 55.2% and specificity of 79.0%.
CONCLUSION
CONCLUSIONS
At first trimester, a model including multiparity, pre-pregnancy BMI and PAPP-A satisfactorily predicted the risk of giving birth to a LGA infant. This promising tool, once applied early in pregnancy, would identify women deserving targeted interventions.
TRIAL REGISTRATION
BACKGROUND
ClinicalTrials.gov NCT04838431 , 09/04/2021.
Identifiants
pubmed: 34560843
doi: 10.1186/s12884-021-04127-3
pii: 10.1186/s12884-021-04127-3
pmc: PMC8464112
doi:
Substances chimiques
Biomarkers
0
Pregnancy-Associated Plasma Protein-A
EC 3.4.24.-
PAPPA protein, human
EC 3.4.24.79
Banques de données
ClinicalTrials.gov
['NCT04838431']
Types de publication
Journal Article
Observational Study
Langues
eng
Sous-ensembles de citation
IM
Pagination
654Informations de copyright
© 2021. The Author(s).
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