Evidence map›Paper›PMID 39294421›Full record

ArticleInternational journal of obesity (2005)2025

Glucose circadian rhythm assessment in pregnant women for gestational diabetes screening.

Rafael Bravo, Kyung Hyun Lee, Sarah A Nazeer, Jocelyn A Cornthwaite, Michal Fishel Bartal, Claudia Pedroza

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Article in International journal of obesity (2005), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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.

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

1 citing paper in PubMed.

  1. Review
4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Rafael BravoThe Institute for Clinical Research & Learning Health Care, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA. Rafael.BravoSantos@uth.tmc.edu.ORCID 0000-0001-6732-2205
Kyung Hyun LeeThe Institute for Clinical Research & Learning Health Care, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA.ORCID 0000-0003-2475-5814
Sarah A NazeerDivision of Maternal-Fetal Medicine, Department of Obstetrics, Gynecology, and Reproductive Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Jocelyn A CornthwaiteDivision of Maternal-Fetal Medicine, Department of Obstetrics, Gynecology, and Reproductive Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Michal Fishel BartalDivision of Maternal-Fetal Medicine, Department of Obstetrics, Gynecology, and Reproductive Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Claudia PedrozaThe Institute for Clinical Research & Learning Health Care, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGestational diabetes mellitus (GDM) is the most common complication during pregnancy, and it is associated with short- and long-term health impairments. Even with increasing incidence rates worldwide, to date, GDM lacks an international standard diagnosis criterion.

objectiveTo elucidate whether a chronobiological perspective may improve the identification of patients at risk for neonatal complications.

methodsWe analyzed a dataset with 92 recruited pregnant patients with Continuous Glucose Monitoring (CGM) data obtained in a blinded study. The primary outcome consisted in evaluating whether the composite of adverse neonatal outcomes could be predicted by chronobiological variables derived from fitting glucose oscillation to a circadian rhythm. The secondary neonatal outcomes included preterm birth, neonatal intensive care unit admission, hypoglycemia, mechanical ventilation or continuous positive airway pressure, hyperbilirubinemia, and hospital length of stay. The secondary maternal outcomes included weight gain during pregnancy, hypertensive disorders of pregnancy, induction of labor, cesarean delivery, and postpartum complications. 87 subjects had enough data to study for glucose circadian rhythmicity.

resultsWe developed a 3-covariate model including two chronobiological metrics, the midline estimating statistic of rhythm (MESOR) and glucose M10 start-time, and age that was predictive of the primary outcome, and associated with maternal secondary outcomes (preeclampsia with severe features and weight gain during pregnancy), and newborn secondary outcomes (preterm delivery < 37 weeks, indicated preterm delivery, NICU admission, need for CPAP, and differences in length of hospital stay).

conclusionsChronobiological parameters might contribute to a better identification of the adverse outcomes associated with GDM in both the mother and newborn.

Indexed as

Blood GlucoseCircadian RhythmDiabetes, GestationalAdultFemaleHumansInfant, NewbornMass ScreeningPregnancyPregnancy OutcomeBlood Glucose

Identifiers

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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 Socratic graph.