Evidence map›Paper›PMID 32131758›Full record

ArticleBMC pregnancy and childbirth2020

"INTERGROWTH21st vs customized fetal growth curves in the assessment of the neonatal nutritional status: a retrospective cohort study of gestational diabetes".

Juan Jesús Fernández-Alba, Estefanía Soto Pazos, Rocío Moreno Cortés, Ángel Vilar Sánchez, Carmen González Macías, María Castillo Lara, Luis Moreno Corral, José Antonio Sainz Bueno

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Article in BMC pregnancy and childbirth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.7field-weighted citation impact, top 25% of its field
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.

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 8 citations in OpenAlex.

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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 at 3 institutions in 1 country.

Juan Jesús Fernández-AlbaDepartment of Obstetrics and Gynecology, University Hospital of Puerto Real, Ctra. Nacional IV, km. 665. Puerto Real, 11510, Cádiz, Spain. jjesus.fernandez@uca.es.ORCID http://orcid.org/0000-0002-7297-6876
Estefanía Soto PazosDepartment of Obstetrics and Gynecology, University Hospital of Puerto Real, Ctra. Nacional IV, km. 665. Puerto Real, 11510, Cádiz, Spain.
Rocío Moreno CortésDepartment of Obstetrics and Gynecology, University Hospital of Puerto Real, Ctra. Nacional IV, km. 665. Puerto Real, 11510, Cádiz, Spain.
Ángel Vilar SánchezDepartment of Obstetrics and Gynecology, University Hospital of Puerto Real, Ctra. Nacional IV, km. 665. Puerto Real, 11510, Cádiz, Spain.
Carmen González MacíasDepartment of Obstetrics and Gynecology, University Hospital of Puerto Real, Ctra. Nacional IV, km. 665. Puerto Real, 11510, Cádiz, Spain.
María Castillo LaraDepartment of Obstetrics and Gynecology, University Hospital of Puerto Real, Ctra. Nacional IV, km. 665. Puerto Real, 11510, Cádiz, Spain.
Luis Moreno CorralNursing Department, Faculty of Health Sciences, Cádiz University, Campus de la Asunción, Av. Ana de Viya, 52, Cadiz, 11510, Spain.
José Antonio Sainz BuenoMaternity Unit, Valme University Hospital, Seville, Spain.
Hospital Universitario Puerto Real · ESHospital Universitario de Valme · ESUniversidad de Cádiz · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGestational diabetes mellitus is associated with increased incidence of adverse perinatal outcomes including newborns large for gestational age, macrosomia, preeclampsia, polyhydramnios, stillbirth, and neonatal morbidity. Thus, fetal growth should be monitored by ultrasound to assess for fetal overnutrition, and thereby, its clinical consequence, macrosomia. However, it is not clear which reference curve to use to define the limits of normality. Our aim is to determine which method, INTERGROWTH21st or customized curves, better identifies the nutritional status of newborns of diabetic mothers.

methodsThis retrospective cohort study compared the risk of malnutrition in SGA newborns and the risk of overnutrition in LGA newborns using INTERGROWTH21st and customized birth weight references in gestational diabetes. The nutritional status of newborns was assessed using the ponderal index. Additionally, to determine the ability of both methods in the identification of neonatal malnutrition and overnutrition, we calculate sensitivity, specificity, positive predictive value, negative predictive value and likelihood ratios.

resultsTwo hundred thirty-one pregnant women with GDM were included in the study. The rate of SGA indentified by INTERGROWTH21st was 4.7% vs 10.7% identified by the customized curves. The rate of LGA identified by INTERGROWTH21st was 25.6% vs 13.2% identified by the customized method. Newborns identified as SGA by the customized method showed a higher risk of malnutrition than those identified as SGA by INTERGROWTH21st. (RR 4.24 vs 2.5). LGA newborns according to the customized method also showed a higher risk of overnutrition than those classified as LGA according to INTERGROWTH21st. (RR 5.26 vs 3.57). In addition, the positive predictive value of the customized method was superior to that of INTERGROWTH21st in the identification of malnutrition (32% vs 27.27%), severe malnutrition (22.73% vs 20%), overnutrition (51.61% vs 32.20%) and severe overnutrition (28.57% vs 14.89%).

conclusionsIn pregnant women with DMG, the ability of customized fetal growth curves to identify newborns with alterations in nutritional status appears to exceed that of INTERGROWTH21st.

Indexed as

Diabetes, GestationalFetal DevelopmentNutritional StatusAdultAnthropometryBirth WeightCohort StudiesFemaleFetal Nutrition DisordersFetal WeightGestational AgeGrowth ChartsHumansInfant, NewbornInfant, Small for Gestational AgePregnancyBirth weightDiabetesFetal growthFetal macrosomiaFetal malnutritionGestational (gestational diabetes)Infant overnutritionSmall for gestational age (INFANT SGA)

Identifiers

PMID32131758
PMCPMC7057488
OpenAlexW3010701161

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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 OpenQuestion graph.