Evidence mapPaperPMID 35596164Full record

ArticleBMC pregnancy and childbirth2022

Weight gain rate in the second and third trimesters and fetal growth in women with gestational diabetes mellitus: a retrospective cohort study.

Miao Hong, Feng Liang, Zheng Zheng, Huimin Chen, Yi Guo, Kuanrong Li, Xihong Liu

Open access · goldAbstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
2.6field-weighted citation impact, top 10% 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.

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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 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

7 authors at 1 institution in 1 country.

Miao Hong *Clinical Data Center, Institute of Pediatrics, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Jinsui Road, Guangzhou, 510623, Guangdong, China. hongm2525@163.com.
Feng Liang *Clinical Data Center, Institute of Pediatrics, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Jinsui Road, Guangzhou, 510623, Guangdong, China.
Zheng ZhengDepartment of Obstetrics, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510623, Guangdong, China.
Huimin ChenDepartment of Clinical Nutrition, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510623, Guangdong, China.
Yi GuoClinical Data Center, Institute of Pediatrics, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Jinsui Road, Guangzhou, 510623, Guangdong, China.
Kuanrong LiClinical Data Center, Institute of Pediatrics, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, 9 Jinsui Road, Guangzhou, 510623, Guangdong, China.
Xihong LiuDepartment of Clinical Nutrition, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510623, Guangdong, China.
Guangzhou Medical University · CN

Funding

Guangzhou Women and Children's Medical Center 3001153-04
6 · The paper itself

Abstract

backgroundControversial evidence regarding the applicability of the IOM's gestational weight gain (GWG) targets for women with gestational diabetes mellitus (GDM) has been reported. However, little is known about the weight gain rate (WGR) during the second and third trimesters. Moreover, previous studies failed to assess the effect modification of pre-pregnancy BMI because of the limited sample size. Therefore, we aimed to assess the applicability of the IOM recommendation for the WGR in women with GDM in different pre-pregnancy BMI categories.

methodsWe conducted this retrospective cohort study of 5275 women with GDM who delivered at Guangzhou Women and Children's Medical Center (GWCMC) between January 2017 and January 2021. Demographic and clinical information was collected from the electronic medical record system. The primary exposure was the WGR in the late second and third trimesters; they were classified as below, within, and above the IOM standard. The outcomes were fetal growth indicators, including large-for-gestational-age (LGA), macrosomia, small-for-gestational-age (SGA), and low birth weight (LBW). The associations between the WGR and such outcomes were assessed using multiple logistic regression.

resultsA WGR below the IOM standard was associated with the decreased odds of LGA (adjusted OR 0.74; 95% CI 0.49-1.13) and macrosomia (adjusted OR 0.54, 95% CI 0.32-0.92) for women with GDM in the normal weight BMI class. Such decreases were observed greater for women with GDM in the overweight/obese class, with adjusted ORs of 0.34 (95% CI 0.09-0.88) for LGA and 0.31 (95% CI 0.01-0.84) for macrosomia, respectively. No significant difference was observed in the odds ratios of SGA and LBW across the different WGR groups.

conclusionLGA and macrosomia are the main outcomes associated with the WGR in the late second and third trimesters, and a WGR below the IOM standard was associated with a decreased odds of such outcomes compared with a WGR within the IOM standard in women with GDM in the normal weight and overweight/obese classes. Our findings suggest that a stricter WGR target than that of the current IOM standard may be more beneficial for women with GDM.

Indexed as

Diabetes, GestationalBirth WeightBody Mass IndexChildFemaleFetal DevelopmentFetal Growth RetardationFetal MacrosomiaHumansInfant, NewbornObesityOverweightPregnancyPregnancy OutcomePregnancy Trimester, ThirdRetrospective StudiesFetal growthGestational diabetes mellitusGestational weight gain rateInstitute of Medicine

Identifiers

PMID35596164
PMCPMC9122248
OpenAlexW4280577053

What Socratic holds

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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 Socratic graph.