Gremlin-1 level in polycystic ovary syndrome and its clinical correlations; A case control study
DOI:
https://doi.org/10.47391/JPMA.EGY-S4-23Keywords:
Polycystic ovary syndrome, Hyperandrogenism, Follicular fluid, Anovulation, Predictive value, InfertilityAbstract
Objective: To evaluate the involvement of the level of Gremlin-1 in serum and follicular fluid in the diagnosis of polycystic ovary syndrome.
Methods: The case-control study was conducted at the Kafrelsheikh University Hospital, Egypt, from September 2021 to February 2022, and comprised women with polycystic ovary syndrome and healthy controls. All participants were subjected to a detailed clinical assessment, complete clinical examination and hormonal profile assessment. Gremlin- 1 concentrations in plasma and follicular fluid samples were assessed by a double-antibody sandwich enzyme-linked immunosorbent assay kit. Data was analysed using SPSS 20.
Results: Of the 90 subjects, 45(50%) were patients with a mean age of 29.53±4.82 years, and 45(50%) were controls with a mean age of 30.89±6.08 (p>0.05). Mean weight, body mass index, waist circumference and waist-hip ratio were significantly higher in patients compared to controls (p<0.05). Serum and follicular fluid Gremlin-1 levels were significantly higher in the patient group (p<0.05). The best cutoff of serum Gremlin-1 in the diagnosis of polycystic ovary syndrome was ≧1.325ng/ml with area under curve 0.857, sensitivity 93.3%, specificity 68.9%, positive predictive value 75%, negative predictive value 91.2% and overall accuracy 81.1%. The best cutoff of follicular fluid Gremlin-1 in
the diagnosis of polycystic ovary syndrome was ≧1.725ng/ml with area under curve 0.789, sensitivity 73.3%, specificity 68.9%, positive predictive value 70.2%, negative predictive value 72.1% and overall accuracy 71.1%.
Conclusion: There was a strong correlation between serum and follicular Gremlin-1 levels in polycystic ovary syndrome patients.
Keywords: Polycystic ovary syndrome, Hyperandrogenism, Follicular fluid, Anovulation, Predictive value, Infertility.
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