In:
BioMed Research International, Hindawi Limited, Vol. 2023 ( 2023-2-13), p. 1-9
Abstract:
Objective. Hyperandrogenaemia and insulin resistance (IR) are the main characteristics of polycystic ovary syndrome (PCOS). Here, we study to find appropriate markers predicting IR and hyperandrogenaemia of women with PCOS in northwest China. Methods. According to body mass index (BMI), 953 patients with PCOS were divided into two groups. All the patients underwent physical examination and ultrasonography and collected elbow vein blood. Their BMI, waist-to-height ratio (WHtR), waist-to-hip ratio (WHR), LAP, VAI, homeostasis model assessment index of insulin resistance (HOMA-IR), and free androgen index (FAI) were calculated. Each group (normal weight and obesity/overweight) was further divided into two subgroups according to their HOMA-IR and FAI: the IR+ subgroup/IR- subgroup and FAI+ subgroup/FAI- subgroup. Furthermore, we compared the clinical indices, hormone levels, and metabolic makers separately between these groups. The correlations between these parameters and HOMA-IR or FAI were tested; sensitivity, specificity, and receiver-operating characteristic (ROC) curves were calculated. Results. In the obesity/overweight group, the VAI (best cut-off value: 2.27, area under the curve AUC = 0.699 ) and LAP (best cut-off value: 45.54, AUC = 0.680 ) were sensitive predictors of IR ( sensitivity = 72 % and sensitivity = 67 % ). Additionally, the VAI (best cut-off value: 2.13, AUC = 0.624 ) and LAP (best cut-off value: 51.18, AUC = 0.582 ) were sensitive predictors of FAI ( sensitivity = 87 % and sensitivity = 64 % ). In the normal weight group, BMI could preferably predict HOMA-IR ( AUC = 0.717 , best cut-off value: 21.62) and HOMA-IR could preferably predict FAI (best cut-off value: 2.11, AUC = 0.648 ). Conclusion. Our data indicated that the VAI and LAP may contribute to the early identification of IR and hyperandrogenaemia in the obesity/overweight patients of PCOS. In normal weight PCOS, BMI was a better predictor to IR, and HOWA-IR was a better predictor to FAI.
Type of Medium:
Online Resource
ISSN:
2314-6141
,
2314-6133
DOI:
10.1155/2023/1508675
Language:
English
Publisher:
Hindawi Limited
Publication Date:
2023
detail.hit.zdb_id:
2698540-8
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