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Influence of hsCRP Parameter on the Occurrence of Metabolic Syndrome in Patients with Polycystic Ovary Syndrome

PCOS (polycystic ovary syndrome) is a common endocrine disorder that affects 8–13% of women of reproductive age. Increased body weight and insulin resistance may be associated with chronic inflammation, which increases the risk of cardiovascular complications. CRP (C-reactive protein) tests may be u...

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Autores principales: Lejman-Larysz, Katarzyna, Pietrzyk, Dominika, Ćwiertnia, Adrianna, Kozłowski, Mateusz, Kwiatkowski, Sebastian, Szydłowska, Iwona, Nawrocka-Rutkowska, Jolanta, Brodowski, Jacek, Sowińska-Przepiera, Elżbieta, Cymbaluk-Płoska, Aneta, Brodowska, Agnieszka
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10377555/
https://www.ncbi.nlm.nih.gov/pubmed/37509592
http://dx.doi.org/10.3390/biomedicines11071953
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author Lejman-Larysz, Katarzyna
Pietrzyk, Dominika
Ćwiertnia, Adrianna
Kozłowski, Mateusz
Kwiatkowski, Sebastian
Szydłowska, Iwona
Nawrocka-Rutkowska, Jolanta
Brodowski, Jacek
Sowińska-Przepiera, Elżbieta
Cymbaluk-Płoska, Aneta
Brodowska, Agnieszka
author_facet Lejman-Larysz, Katarzyna
Pietrzyk, Dominika
Ćwiertnia, Adrianna
Kozłowski, Mateusz
Kwiatkowski, Sebastian
Szydłowska, Iwona
Nawrocka-Rutkowska, Jolanta
Brodowski, Jacek
Sowińska-Przepiera, Elżbieta
Cymbaluk-Płoska, Aneta
Brodowska, Agnieszka
author_sort Lejman-Larysz, Katarzyna
collection PubMed
description PCOS (polycystic ovary syndrome) is a common endocrine disorder that affects 8–13% of women of reproductive age. Increased body weight and insulin resistance may be associated with chronic inflammation, which increases the risk of cardiovascular complications. CRP (C-reactive protein) tests may be use to assess persistent inflammation. Elevated CRP levels may be associated with insulin resistance and type 2 diabetes. Determination of hsCRP, highly sensitive C-reactive protein, can be used to assess cardiovascular risk in women with PCOS. In this study, 120 women between the ages of 18 and 42 were divided into two groups: patients with polycystic ovary syndrome (n = 80) and regular menstruating women in whom PCOS was excluded (n = 40). Lipid and carbohydrate metabolism parameters and hsCRP levels were assessed, followed by receiver operating characteristic (ROC) analysis for hsCRP, where metabolic syndrome was the dependent variable. For hsCRP, the cutoff point was 1.44 (mg/dL). Sensitivity for the cutoff point was 0.913 and specificity was 0.691. The area under the curve (AUC) was 0.851 (p < 0.000). The closer the AUC value is to unity, the better the predictive ability of the studied variable. There was also a statistically significant correlation between hsCRP levels and the presence of metabolic syndrome.
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spelling pubmed-103775552023-07-29 Influence of hsCRP Parameter on the Occurrence of Metabolic Syndrome in Patients with Polycystic Ovary Syndrome Lejman-Larysz, Katarzyna Pietrzyk, Dominika Ćwiertnia, Adrianna Kozłowski, Mateusz Kwiatkowski, Sebastian Szydłowska, Iwona Nawrocka-Rutkowska, Jolanta Brodowski, Jacek Sowińska-Przepiera, Elżbieta Cymbaluk-Płoska, Aneta Brodowska, Agnieszka Biomedicines Article PCOS (polycystic ovary syndrome) is a common endocrine disorder that affects 8–13% of women of reproductive age. Increased body weight and insulin resistance may be associated with chronic inflammation, which increases the risk of cardiovascular complications. CRP (C-reactive protein) tests may be use to assess persistent inflammation. Elevated CRP levels may be associated with insulin resistance and type 2 diabetes. Determination of hsCRP, highly sensitive C-reactive protein, can be used to assess cardiovascular risk in women with PCOS. In this study, 120 women between the ages of 18 and 42 were divided into two groups: patients with polycystic ovary syndrome (n = 80) and regular menstruating women in whom PCOS was excluded (n = 40). Lipid and carbohydrate metabolism parameters and hsCRP levels were assessed, followed by receiver operating characteristic (ROC) analysis for hsCRP, where metabolic syndrome was the dependent variable. For hsCRP, the cutoff point was 1.44 (mg/dL). Sensitivity for the cutoff point was 0.913 and specificity was 0.691. The area under the curve (AUC) was 0.851 (p < 0.000). The closer the AUC value is to unity, the better the predictive ability of the studied variable. There was also a statistically significant correlation between hsCRP levels and the presence of metabolic syndrome. MDPI 2023-07-10 /pmc/articles/PMC10377555/ /pubmed/37509592 http://dx.doi.org/10.3390/biomedicines11071953 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Lejman-Larysz, Katarzyna
Pietrzyk, Dominika
Ćwiertnia, Adrianna
Kozłowski, Mateusz
Kwiatkowski, Sebastian
Szydłowska, Iwona
Nawrocka-Rutkowska, Jolanta
Brodowski, Jacek
Sowińska-Przepiera, Elżbieta
Cymbaluk-Płoska, Aneta
Brodowska, Agnieszka
Influence of hsCRP Parameter on the Occurrence of Metabolic Syndrome in Patients with Polycystic Ovary Syndrome
title Influence of hsCRP Parameter on the Occurrence of Metabolic Syndrome in Patients with Polycystic Ovary Syndrome
title_full Influence of hsCRP Parameter on the Occurrence of Metabolic Syndrome in Patients with Polycystic Ovary Syndrome
title_fullStr Influence of hsCRP Parameter on the Occurrence of Metabolic Syndrome in Patients with Polycystic Ovary Syndrome
title_full_unstemmed Influence of hsCRP Parameter on the Occurrence of Metabolic Syndrome in Patients with Polycystic Ovary Syndrome
title_short Influence of hsCRP Parameter on the Occurrence of Metabolic Syndrome in Patients with Polycystic Ovary Syndrome
title_sort influence of hscrp parameter on the occurrence of metabolic syndrome in patients with polycystic ovary syndrome
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10377555/
https://www.ncbi.nlm.nih.gov/pubmed/37509592
http://dx.doi.org/10.3390/biomedicines11071953
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