Evidence map›Paper›PMID 34560843›Full record

Observational studyBMC pregnancy and childbirth2021

A first trimester prediction model for large for gestational age infants: a preliminary study.

Francesca Monari, Daniela Menichini, Ludovica Spano' Bascio, Giovanni Grandi, Federico Banchelli, Isabella Neri, Roberto D'Amico, Fabio Facchinetti

Registry-linked trialAbstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in BMC pregnancy and childbirth, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04838431 (Development of a Prediction Model for Large for Gestational Age Infants at First Trimester), which is not on this map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04838431 terminatednot on this map

Development of a Prediction Model for Large for Gestational Age Infants at First Trimester: a Preliminary Study

TypeobservationalSponsorUniversity of Modena and Reggio EmiliaRan2018 to 2019Enrolled503ConditionsLarge for Gestational Age Baby, Macrosomia, FetalArmsBlood sample and ultrasound at first trimester
3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Maternal Birth Weight FromJournal of pregnancy · 2025
    Article
  5. Article
  6. Article
  7. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Francesca MonariObstetrics Unit, Mother Infant Department, University Hospital Policlinico of Modena, Modena, Italy.
Daniela MenichiniInternational Doctorate School in Clinical and Experimental Medicine, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Via del Pozzo 71, 41121, Modena, Italy. daniela.menichini91@gmail.com.
Ludovica Spano' BascioObstetrics Unit, Mother Infant Department, University Hospital Policlinico of Modena, Modena, Italy.
Giovanni GrandiObstetrics Unit, Mother Infant Department, University Hospital Policlinico of Modena, Modena, Italy.
Federico BanchelliDepartment of Diagnostic, Clinical and Public Health Medicine, Statistics Unit, University of Modena and Reggio Emilia, Modena, Italy.
Isabella NeriObstetrics Unit, Mother Infant Department, University Hospital Policlinico of Modena, Modena, Italy.
Roberto D'AmicoDepartment of Diagnostic, Clinical and Public Health Medicine, Statistics Unit, University of Modena and Reggio Emilia, Modena, Italy.
Fabio FacchinettiObstetrics Unit, Mother Infant Department, University Hospital Policlinico of Modena, Modena, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLarge 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.

methodsProspective 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.

resultsA 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%.

conclusionAt 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 registrationClinicalTrials.gov NCT04838431 , 09/04/2021.

Indexed as

Body Mass IndexParityPregnancy-Associated Plasma Protein-APregnancy Trimester, FirstAdultBiomarkersFemaleFetal MacrosomiaHumansItalyPredictive Value of TestsPregnancyProspective StudiesRisk FactorsROC CurveSensitivity and SpecificityBiomarkersPAPPA protein, humanPregnancy-Associated Plasma Protein-ABiochemical markersBiophysical markersFirst trimesterLGAPrediction model

Identifiers

PMID34560843
PMCPMC8464112

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.