Your browser doesn't support javascript.
loading
Predictive markers for abnormal glucose intolerance in women with polycystic ovary syndrome.
Jeong, Kyungah; Park, So Y; Jeon, Ji H; Lee, Sa R; Chung, Hye W.
Affiliation
  • Jeong K; Department of Obstetrics and Gynecology, School of Medicine, Ewha Womans University, Seoul, Korea - hyewon@ewha.ac.kr.
Minerva Med ; 2016 May 06.
Article in En | MEDLINE | ID: mdl-27152717
ABSTRACT

BACKGROUND:

The purpose of this study is to identify predictive markers for abnormal glucose metabolism in Korean women with polycystic ovary syndrome (PCOS).

METHODS:

A total of 312 PCOS patients were evaluated. All patients underwent 75g oral glucose tolerance tests. The 2 hour plasma glucose level was used to categorize subjects as impaired glucose tolerance (IGT) or non-insulin-dependent diabetes mellitus (NIDDM). Areas under the receiver operating characteristic (ROC) curves were used to compare the power of serum markers. Multiple linear regression analysis was used to evaluate the contribution of each confounding factor to the 2 hour post-load glucose value.

RESULTS:

285 PCOS women with normal glucose tolerance (91.3%) and 27 PCOS patients with abnormal glucose metabolism (8.7%) (IGT/NIDDM) were evaluated. Area under the curve (AUC) of hemoglobin(Hb) A1c, high sensitivity C-reactive protein (hs- CRP), lipid accumulation product(LAP) index, and triglyceride (TG) were 0.780, 0.772, 0.762, and 0.758 respectively. ROC analysis suggested a threshold value of 5.45 in HbA1c (71.4% sensitivity and 70.0% specificity), a value of 1.16 in high sensitivity CRP (70.3% sensitivity and 80.1% specificity), a value of 12.98 in LAP index (88.5% sensitivity and 52.3% specificity) and a value of 88.0 in TG (77.8% sensitivity and 63.5% specificity) to predict for abnormal glucose metabolism.

CONCLUSION:

HbA1c, hs-CRP, LAP index, and TG could be useful predictive markers for abnormal glucose metabolism (IGT/NIDDM) in Korean PCOS women.
Search on Google
Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Minerva Med Year: 2016 Document type: Article
Search on Google
Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies / Risk_factors_studies Language: En Journal: Minerva Med Year: 2016 Document type: Article