Evidence map›Paper›PMID 34983441›Full record

ArticleBMC pregnancy and childbirth2022

Diagnostic accuracy of first and early second trimester multiple biomarkers for prediction of gestational diabetes mellitus: a multivariate longitudinal approach.

Elham Shaarbaf Eidgahi, Malihe Nasiri, Nourossadat Kariman, Nastaran Safavi Ardebili, Masoud Salehi, Maryam Kazemi, Farid Zayeri

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 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
3.7field-weighted citation impact, top 6% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. First-trimester biomarkers of gestational diabetes mellitus: A scoping review.Acta obstetricia et gynecologica Scandinavica · 2025
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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 3 institutions in 1 country.

Elham Shaarbaf EidgahiDepartment of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Malihe NasiriDepartment of Basic Sciences, Faculty of Nursing and Midwifery, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Nourossadat KarimanDepartment of Midwifery and Reproductive Health Research Center, Faculty of Nursing and Midwifery, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Nastaran Safavi ArdebiliDepartment of Midwifery, Ardabil Branch, Islamic Azad University, Ardabil, Iran.
Masoud SalehiHealth Management and Economics Research Center and Department of Biostatistics, School of Public Health, Iran University of Medical Sciences, Tehran, Iran.
Maryam KazemiDepartment of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Farid ZayeriProteomics Research Center and Department of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical Sciences, Qods Square, Darband Street, Tehran, Iran. f_zayeri@sbmu.ac.ir.
Shahid Beheshti University of Medical Sciences · IRIran University of Medical Sciences · IRIslamic Azad University Ardabil · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGestational Diabetes Mellitus (GDM) is an underlying cause of maternal and newborn morbidity and mortality all around the world. Timely diagnosis of GDM plays an important role in reducing its adverse consequences and burden. This study aimed to determine diagnostic accuracy of multiple indicators in complete blood count (CBC) test for early prediction of GDM.

methodsIn this prospective cohort study, the data from 600 pregnant women was analyzed. In the study sample, the two-step approach was utilized for the diagnosis of GDM at 24-28 weeks of gestation. We also used the repeated measures of hemoglobin (Hb), hematocrit (Hct), fasting blood sugar (FBS) and red blood cell count (RBC) in the first and early second trimesters of pregnancy as the longitudinal multiple indicators for early diagnosis of GDM. The classification of pregnant women to GDM and non-GDM groups was performed using a statistical technique based on the random-effects modeling framework.

resultsAmong the sample, 49 women (8.2%) were diagnosed with GDM. In the first and early second trimester of pregnancy, the mean HcT, Hb and FBS of women with GDM was significantly higher than non-GDMs (P < 0.001). The concurrent use of multiple longitudinal data from HcT, Hb, RBC and FBS in the first and early second trimester of pregnancy resulted in a sensitivity, specificity and area under the curve (AUC) of 87%, 70% and 83%, respectively, for early prediction of GDM.

conclusionsIn general, our findings showed that the concurrent use of repeated measures data on Hct, Hb, FBS and RBC in the first and early second trimester of pregnancy might be utilized as an acceptable tool to predict GDM earlier in pregnancy.

Indexed as

Multivariate AnalysisAdultArea Under CurveBiomarkersBlood GlucoseCohort StudiesDiabetes, GestationalErythrocyte CountFemaleHematocritHemoglobinsHumansLongitudinal StudiesPregnancyPregnancy Trimester, FirstPregnancy Trimester, SecondBiomarkersBlood GlucoseHemoglobinsDiagnostic accuracyFasting blood sugarGestational diabetes mellitusHematocritHemoglobinRed blood cell count

Identifiers

PMID34983441
PMCPMC8728972
OpenAlexW4225263085

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.