Evidence mapPaperPMID 36790635Full record

ArticleHormones (Athens, Greece)2023

Value of the triglyceride-glucose index and non-traditional blood lipid parameters in predicting metabolic syndrome in women with polycystic ovary syndrome.

Lijuan Zhang, Hui Wang, Qi Ma, Yifan Liu, Airong Chen, Jing Lu, Liuliu Ren

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Article in Hormones (Athens, Greece), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
6.3field-weighted citation impact, top 3% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.

  1. Pooled it
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  6. Observational
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  12. 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
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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 2 institutions in 1 country.

Lijuan ZhangDepartment of Endocrinology and Metabolism, Lanzhou University Second Hospital, Lanzhou, 730000, Gansu, China.
Hui WangDepartment of Endocrinology and Metabolism, Lanzhou University Second Hospital, Lanzhou, 730000, Gansu, China.
Qi MaDepartment of Endocrinology and Metabolism, Lanzhou University Second Hospital, Lanzhou, 730000, Gansu, China.
Yifan LiuDepartment of Endocrinology and Metabolism, Lanzhou University Second Hospital, Lanzhou, 730000, Gansu, China.
Airong ChenDepartment of Endocrinology and Metabolism, Lanzhou University Second Hospital, Lanzhou, 730000, Gansu, China. chenair@lzu.edu.cn.
Jing LuDepartment of Endocrinology and Metabolism, Lanzhou University Second Hospital, Lanzhou, 730000, Gansu, China.
Liuliu RenDepartment of Endocrinology and Metabolism, Lanzhou University Second Hospital, Lanzhou, 730000, Gansu, China.
Lanzhou University Second Hospital · CNLanzhou University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeInsulin resistance (IR) is common in patients with polycystic ovary syndrome (PCOS). Metabolic syndrome (MS) includes, inter alia, IR, hypertension, dyslipidemia, and disturbances in glucose metabolism. The triglyceride-glucose (TyG) index and non-traditional lipid parameters are strong predictors of IR and cardiovascular disease and can be considered as screening indicators for MS. This study aimed to evaluate the predictive potential of non-traditional lipid parameters and the TyG index to identify MS in PCOS.

methodsThis cross-sectional study included 134 women diagnosed with PCOS (50 patients with comorbid MS and 84 patients without MS). Biochemical indices were collected, and triglycerides (TG)/high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC)/HDL-C, low-density lipoprotein cholesterol (LDL-C)/HDL-C, non-HDL-C, TyG, and TyG-BMI indices were calculated. Logistic regression analysis was used to compare and determine the association of the six parameters with MS, and the receiver operating characteristic (ROC) curve was used to evaluate the performance of each parameter in identifying MS in the PCOS population.

resultsAfter adjusting for age and body mass index (BMI), TG/HDL-C, TC/HDL-C, LDL-C/HDL-C, non-HDL-C, TyG, and TyG-BMI were associated with MS (all P<0.05). The odds ratios were 4.075 (0.891, 1.107), 3.121 (1.844, 5.282), 3.106 (1.734, 5.561), 2.238 (1.302, 3.848), 13.422 (4.364, 41.282), and 1.102 (1.056, 1.150), respectively. TG/HDL-C, TC/HDL-C, LDL-C/HDL-C, non-HDL-C, TyG, and TyG-BMI are effective predictors of MS in PCOS, and their cut-off values can be used for the early detection of MS. TyG-BMI had the strongest performance in predicting MS (area under the curve 0.905, 95% CI 0.855-0.956), and its optimal critical value for predicting MS was 202.542.

conclusionsTG/HDL-C, TC/HDL-C, LDL-C/HDL-C, non-HDL-C, TyG, and TyG-BMI are novel, clinically convenient and practical markers for the early identification of MS risk in PCOS patients.

Indexed as

Insulin ResistanceMetabolic SyndromePolycystic Ovary SyndromeBlood GlucoseCholesterol, HDLCholesterol, LDLCross-Sectional StudiesFemaleGlucoseHumansLipidsLipoproteinsTriglyceridesBlood GlucoseCholesterol, HDLCholesterol, LDLGlucoseLipidsLipoproteinsTriglyceridesInsulin resistanceMetabolic syndromeNon-traditional lipidsPolycystic ovary syndromeTriglyceride–glucose index

Identifiers

PMID36790635
OpenAlexW4320857464

What Socratic 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 Socratic graph.