Objective: To compare the different polycystic ovarian syndrome (PCOS) phenotypes based on their clinical, metabolic, hormonal profile, and their differential response to clomiphene. Design: Prospective observational study. Setting: Infertility clinic,… Click to show full abstract
Objective: To compare the different polycystic ovarian syndrome (PCOS) phenotypes based on their clinical, metabolic, hormonal profile, and their differential response to clomiphene. Design: Prospective observational study. Setting: Infertility clinic, a government hospital. Sample Size: 164 women with PCOS-related infertility. Materials and Methods: Sample population was divided into four phenotypes based on the NIH (National Institute of Health) consensus panel criteria. The incremental dose of clomiphene from 50 to 150 mg/day over three cycles was given. Outcome Measures: Clinical history, metabolic, hormonal profile, and ultrasound features of each phenotype. Also, the response to clomiphene citrate was studied as presence or absence of ovulation. Results: The prevalence of phenotypes A, B, C, and D were 67.7%, 11%, 17.7%, and 3.6%, respectively. Phenotype A had significantly higher weight, body mass index, clinical, and biochemical hyperandrogenism, menstrual irregularities, ovarian reserve parameters, fasting insulin, HOMA-IR, and more deranged lipid profile (P < 0.05). Clomiphene resistance was significantly more common in phenotype A (P < 0.05). No significant differences were noted in the waist circumference, waist-hip ratio, blood pressure and blood sugar values (fasting, 1-hour postprandial, 2-hour postprandial). Also, the Follicle Stimulating Hormone (FSH), Luteinizing Hormone (LH), LH-FSH ratio, 17-hydroxyprogesterone, and vitamin D levels were not significantly different among various PCOS phenotypes. Conclusion: Full-blown PCOS (phenotype A) is at a higher risk of adverse metabolic and cardiovascular outcomes as compared with the others, and phenotype D is the least severe phenotype. Thus, the phenotypic division of patients with PCOS-related infertility can help in prognosticating the patients about the severity of the disease and the fertility outcome.
               
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