Evidence map›Paper›PMID 30302420›Full record

ArticleJournal of the Endocrine Society2018

A Pre-Pregnancy Biomarker Risk Score Improves Prediction of Future Gestational Diabetes.

Sylvia E Badon, Yeyi Zhu, Sneha B Sridhar, Fei Xu, Catherine Lee, Samantha F Ehrlich, Charles P Quesenberry, Monique M Hedderson

Open access · goldAbstract read
In one paragraph

Article in Journal of the Endocrine Society, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.6field-weighted citation impact, top 9% 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

14 citing papers in PubMed, 20 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Risk Prediction Model of Gestational Diabetes Mellitus in a Chinese Population Based on a Risk Scoring System.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2021
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  10. Review
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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 1 institution in 1 country.

Sylvia E BadonDivision of Research, Kaiser Permanente Northern California, Oakland, California.ORCID 0000-0002-2868-4067
Yeyi ZhuDivision of Research, Kaiser Permanente Northern California, Oakland, California.
Sneha B SridharDivision of Research, Kaiser Permanente Northern California, Oakland, California.
Fei XuDivision of Research, Kaiser Permanente Northern California, Oakland, California.
Catherine LeeDivision of Research, Kaiser Permanente Northern California, Oakland, California.
Samantha F EhrlichDivision of Research, Kaiser Permanente Northern California, Oakland, California.
Charles P QuesenberryDivision of Research, Kaiser Permanente Northern California, Oakland, California.
Monique M HeddersonDivision of Research, Kaiser Permanente Northern California, Oakland, California.
Kaiser Permanente · US

Funding

Pregravid biomarkers of GDM risk, fetal growth and progression to diabetesR01HD065904 · NICHD · KAISER FOUNDATION RESEARCH INSTITUTE · PI HEDDERSON, MONIQUE MARIE · 2010 to 2013
$2.0M
Physical Activity in Pregnancy for Intergenerational Obesity PreventionK01DK105106 · NIDDK · UNIVERSITY OF TENNESSEE KNOXVILLE · PI EHRLICH, SAMANTHA F · 2015 to 2021
$782k
T32 Training Program in Diabetes Translational ResearchT32DK116684 · NIDDK · KAISER FOUNDATION RESEARCH INSTITUTE · PI GRANT, RICHARD W, SCHMITTDIEL, JULIE A · 2018 to 2022
$714k
NICHD NIH HHS R01 HD065904NIDDK NIH HHS K01 DK105106
6 · The paper itself

Abstract

contextPrevious studies have not examined the ability of multiple preconception biomarkers, considered together, to improve prediction of gestational diabetes mellitus (GDM).

objectiveTo develop a preconception biomarker risk score and assess its association with subsequent GDM.

designA nested case-control study among a cohort of women with serum collected as part of a health examination (1984 to 1996) and subsequent pregnancy (1984 to 2009). Biomarkers associated with GDM were dichotomized into high/low risk.

settingIntegrated health care system.

participantsTwo controls were matched to each GDM case (n = 256 cases) on year and age at examination, age at pregnancy, and number of pregnancies between examination and index pregnancy.

main outcome measureGDM.

resultsHigh-risk levels of sex hormone-binding globulin (SHBG; <44.2 nM), glucose (>90 mg/dL), total adiponectin (<7.2 μg/mL), and homeostasis model assessment-estimated insulin resistance (>3.9) were independently associated with 2.34 [95% confidence interval (CI): 1.50, 3.63], 2.03 (95% CI: 1.29, 3.19), 1.83 (95% CI: 1.16, 2.90), and 1.67 (95% CI: 1.07, 2.62) times the odds of GDM and included in the biomarker risk score. For each unit increase in the biomarker risk score, odds of GDM were 1.94 times greater (95% CI: 1.59, 2.36). A biomarker risk score including only SHBG and glucose was sufficient to improve prediction beyond established risk factors (age, race/ethnicity, body mass index, family history of diabetes, previous GDM; area under the curve = 0.73 vs 0.67,

conclusionsThe improved, predictive ability of the biomarker risk score beyond established risk factors suggests clinical use of the biomarker risk score in identifying women at risk for GDM before conception for targeted prevention strategies.

Indexed as

biomarkergestational diabetespreconceptionpre-pregnancyrisk score

Identifiers

PMID30302420
PMCPMC6169465
OpenAlexW2892145676

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.