Literature DB >> 27634940

Lipid accumulation product as a marker of cardiometabolic susceptibility in women with different phenotypes of polycystic ovary syndrome.

Ivana Božić-Antić1, Dušan Ilić1, Jelica Bjekić-Macut2, Tamara Bogavac1, Danijela Vojnović-Milutinović3, Biljana Kastratovic-Kotlica4, Nataša Milić5, Olivera Stanojlović6, Zoran Andrić2, Djuro Macut7.   

Abstract

OBJECTIVE: There are limited data on cardiometabolic risk factors and the prevalence of metabolic syndrome (MetS) across the different PCOS phenotypes in Caucasian population. Lipid accumulation product (LAP) is a clinical surrogate marker that could be used for evaluation of MetS in clinical practice. The aim of the study was to analyze metabolic characteristics and the ability of LAP to predict MetS in different PCOS phenotypes.
DESIGN: Cross-sectional clinical study analyzing 365 women with PCOS divided into four phenotypes according to the ESHRE/ASRM criteria, and 125 healthy BMI-matched controls.
METHODS: In all subjects, LAP was determined and MetS was diagnosed according to the National Cholesterol Education Program/Adult Treatment Panel III (NCEP-ATP III), the International Diabetes Federation (IDF) and the Joint Interim Statement (JIS) criteria. Logistic regression and ROC curve analyses were used to determine predictors of MetS in each PCOS phenotype. All analyses were performed with age and BMI adjustment.
RESULTS: All PCOS phenotypes in comparison to controls had higher prevalence of MetS assessed by NCEP-ATP III criteria, and only classic phenotypes when IDF and JIS criteria were used. All phenotypes had the same prevalence of MetS irrespective of used definition. LAP and exhibited the highest diagnostic accuracy and was an independent predictor of MetS in all phenotypes.
CONCLUSION: LAP is an independent and accurate clinical determinant of MetS in all PCOS phenotypes in our Caucasian population. All PCOS phenotypes, including non-classic ones, are metabolically challenged and with cardiovascular risk, particularly phenotype B.
© 2016 European Society of Endocrinology.

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Year:  2016        PMID: 27634940     DOI: 10.1530/EJE-16-0775

Source DB:  PubMed          Journal:  Eur J Endocrinol        ISSN: 0804-4643            Impact factor:   6.664


  5 in total

1.  Metabolic syndrome and the risk of cardiovascular complications in young patients with different phenotypes of polycystic ovary syndrome.

Authors:  Anna Krentowska; Agnieszka Łebkowska; Małgorzata Jacewicz-Święcka; Justyna Hryniewicka; Monika Leśniewska; Agnieszka Adamska; Irina Kowalska
Journal:  Endocrine       Date:  2021-01-13       Impact factor: 3.633

2.  Elucidating the impact of obesity on hormonal and metabolic perturbations in polycystic ovary syndrome phenotypes in Indian women.

Authors:  Roshan Dadachanji; Anushree Patil; Beena Joshi; Srabani Mukherjee
Journal:  PLoS One       Date:  2021-02-26       Impact factor: 3.240

3.  Lipid ratios and obesity indices are effective predictors of metabolic syndrome in women with polycystic ovary syndrome.

Authors:  Małgorzata Kałużna; Magdalena Czlapka-Matyasik; Pola Kompf; Jerzy Moczko; Katarzyna Wachowiak-Ochmańska; Adam Janicki; Karolina Samarzewska; Marek Ruchała; Katarzyna Ziemnicka
Journal:  Ther Adv Endocrinol Metab       Date:  2022-01-10       Impact factor: 3.565

4.  Visceral adiposity and renal function: an observational study from SPECT-China.

Authors:  Kun Zhang; Qin Li; Yi Chen; Ningjian Wang; Yingli Lu
Journal:  Lipids Health Dis       Date:  2017-10-27       Impact factor: 3.876

5.  Improving the accuracy and efficacy of diagnosing polycystic ovary syndrome by integrating metabolomics with clinical characteristics: study protocol for a randomized controlled trial.

Authors:  Cheng-Ming Ni; Wen-Long Huang; Yan-Min Jiang; Juan Xu; Ru Duan; Yun-Long Zhu; Xu-Ping Zhu; Xue-Mei Fan; Guo-An Luo; Yi-Ming Wang; Yan-Yu Li; Qing He; Lan Xu
Journal:  Trials       Date:  2020-02-11       Impact factor: 2.279

  5 in total

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