Evidence map›Paper›PMID 36856819›Full record

ArticleArchives of gynecology and obstetrics2024

Same disease - different effect: maternal diabetes impact on birth weight stratified by fetal sex.

Shani Gilron, Rinat Gabbay-Benziv, Rasha Khoury

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Article in Archives of gynecology and obstetrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–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

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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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Observational
  4. 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

3 authors.

Shani GilronSheba Tel Hashomer Medical Center, Ramat Gan, Israel.
Rinat Gabbay-BenzivMaternal Fetal Medicine Department, Hillel Yaffe Medical Center, Hadera, Israel.
Rasha KhouryMaccabi Healthcare Services, Central District, Jaffa, Israel. rasha.kho@gmail.com.ORCID 0000-0001-7468-5485

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMale-sex is an independent risk factor for adverse perinatal outcomes. One example is gestational diabetes mellitus (GDM), which is associated with large gestational age neonates. It was previously described that fetal glucose metabolism is affected by fetal sex. PURPOSE: To examine whether the birth weight of neonates is affected differently by GDM according to fetal sex.

methodsA retrospective normalized cohort analysis, using the open database of 2017 Natality Data from the National Vital Statistics System in the US. We compared the delta in neonatal birth weight, according to fetal sex, between pregnancies with or without GDM. Linear regression was used to take into consideration the effect of multiple confounders. For evaluation whether fetal sex is an independent risk factor for macrosomia (> 4000 and > 4500 g) following pregnancies complicated by GDM we used multivariate logistic regression.

resultsA significant relationship was found between the sex of the neonate and the delta in birth weight associated with GDM (P-value < 0.0001). The average weight gain in neonates to GDM pregnancies was 71 g in females, and 56 g in males. The prevalence of macrosomia above 4000 g and 4500 g that was attributed to GDM was higher in female-sex neonates compared to male-sex neonates (P < 0.05).

conclusionAccording to our study results, female sex is associated with higher fetal weight gain in pregnancies complicated by GDM. Moreover, macrosomia's rate (> 4000 g and > 4500 g) attributed to GDM raised in a more significant manner in female-sex neonates.

Indexed as

Diabetes, GestationalBirth WeightFemaleFetal MacrosomiaHumansInfant, NewbornMalePregnancyRetrospective StudiesRisk FactorsWeight GainGender medicineGestational diabetesMacrosomiaPregnancy complicationsSex and gender

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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.