Evidence map›Paper›PMID 33687700›Full record

ArticleJournal of endocrinological investigation2021

Using metabolic markers to identify insulin resistance in premenopausal women with and without polycystic ovary syndrome.

M R Blum, R A Popat, A Nagy, N A Cataldo, T L McLaughlin

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In one paragraph

Article in Journal of endocrinological investigation, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.3field-weighted citation impact, top 20% 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, 10 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. MicroRNAs as Biomarkers for Metabolic Disorders in Polycystic Ovary Syndrome (PCOS): A Review.Medical science monitor : international medical journal of experimental and clinical research · 2024
    Review
  6. [Analysis of Risk Factors for Recurrent Pregnancy Loss in Patients UndergoingSichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2024
    Article
  7. Article
  8. Review
  9. Article
  10. 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

5 authors at 3 institutions in 2 countries.

M R BlumDepartment of Health Research and Policy (Division of Epidemiology), Stanford University School of Medicine, Stanford, CA, USA.
R A PopatDepartment of Health Research and Policy (Division of Epidemiology), Stanford University School of Medicine, Stanford, CA, USA.
A NagyDivision of Endocrinology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA.
N A CataldoAmerica Institute for Reproductive Medicine, Alabama, One Independence Plaza, Suite 810, Birmingham, AL, USA.
T L McLaughlinDivision of Endocrinology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA. tmclaugh@stanford.edu.ORCID http://orcid.org/0000-0002-4829-8649
Stanford University · USStanford Medicine · USUniversity of Bern · CH

Funding

Heterogeneity of Fat Depots: Biological Differences Related to Insulin ResistanceR01DK080436 · NIDDK · STANFORD UNIVERSITY · PI MCLAUGHLIN, TRACEY · 2009 to 2011
$1.1M
NIDDK NIH HHS R01 DK080436NIH HHS R01 DK096283-01Swiss National Science Foundation P2BEP3_175289
6 · The paper itself

Abstract

backgroundInsulin resistance (IR) is associated with increased risk for type 2 diabetes mellitus and cardiovascular disease. Quantifying IR is invasive and time-consuming, and thus not routinely used in clinical practice. Simple metabolic markers to predict IR exist, but have not been validated in premenopausal women or women with polycystic ovary syndrome (PCOS).

objectiveTo evaluate the ability of metabolic markers to identify premenopausal women with/without PCOS who are insulin resistant. DESIGN/

settingCross-sectional analysis.

participantsOne hundred and seventy-one non-diabetic premenopausal overweight/obese women without PCOS and 71 women with PCOS.

methodsIR was quantified by the steady-state plasma glucose during the modified insulin-suppression test. Metabolic markers (BMI, lipid/lipoprotein concentrations, and fasting glucose) were evaluated for their discriminative ability to identify IR, using area under the receiver-operating-characteristic curve (AUROC) analysis. Optimal cut-points were evaluated for predictive power.

resultsIn the non-PCOS group, the triglyceride/HDL cholesterol ratio (TG/HDL-C) was the best marker (AUROC 0.73). Optimal diagnostic cut-point was 1.9. In the PCOS group, the TG/HDL-C ratio, cholesterol/HDL-C ratio (TC/HDL-C), and HDL-C performed well (AUROC > 0.80), with optimal cut-points for TG/HDL-C 1.3, TC/HDL-C 3.4, and HDL-C 52 mg/dL: TG/HDL-C was more sensitive, but HDL-C had a higher PPV for IR.

conclusionTG/HDL-C can identify IR in premenopausal women with and/without PCOS; diagnostic cut-points differ from those of men and postmenopausal women. HDL-C is an alternative predictor in women with PCOS. These simple metabolic markers, which are standardized between labs, inexpensive, and routinely measured, can be used to tailor lifestyle and medical interventions to improve health outcomes in insulin-resistant premenopausal women.

Indexed as

Insulin ResistancePremenopauseAdultArea Under CurveBiomarkersBlood GlucoseBody Mass IndexCase-Control StudiesCholesterol, HDLCross-Sectional StudiesFemaleFollow-Up StudiesGlucose IntoleranceHumansMalePolycystic Ovary SyndromeBiomarkersBlood GlucoseCholesterol, HDLTriglyceridesInsulin resistanceMetabolic markerPolycystic ovary syndromePremenopausal

Identifiers

PMID33687700
OpenAlexW3134362300

What OpenQuestion holds

Textmetadata
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.