Combined effect of Vyoshadi Guggulu tablet with Kathakakhadiradi Pana on insulin resistance in Polycystic Ovarian Syndrome (PCOS)- a single arm clinical trial

Polycystic Ovarian Syndrome is a multifactorial disorder marked by chronic anovulation, hyperandrogenism, and polycystic ovaries, affecting approximately 1 in 10 women globally. Its prevalence varies depending on diagnostic criteria, with estimates ranging from 6 to13 percent, and up to 70 percent of cases remaining undiagnosed. Comorbidities commonly associated with PCOS include metabolic syndrome, obesity, infertility, impaired glucose tolerance, cardiovascular risk, depression, obstructive sleep apnea, and endometrial cancer. PCOS is often genetically predisposed and exacerbated by obesity. Weight gain in such individuals can lead to clinical and biochemical manifestations of the condition. Conversely, modest weight loss, around 5 percent has been shown to significantly improve reproductive, hyperandrogenic, and metabolic features. Despite its high prevalence, there is no universally accepted treatment protocol for PCOS. The condition is complex due to its heterogeneous presentation and overlap with obesity related metabolic dysfunctions. In Ayurveda, PCOS is considered a Vyadhi Sankara, with symptoms varying in severity and presentation across different life stages. It resembles Pushpagni Jathaharini, characterized by anovulatory cycles, excess body hair, and menstrual disturbances. It may also align with Nashtartava, where obstruction in the Artavavaha Srotas, mainly due to Kapha predominance, is seen as a root cause. In the present study, 20 female participants aged 20 to 35 years, attending the OPD and diagnosed with PCOS with insulin resistance HOMA IR above 1 and BMI between 25 to 34.9, will be selected. They will be administered Vyoshadi Guggulu, 2 tablets twice daily before food and KathakaKhadiradi Pana, 100 ml twice daily half an hour before food for 90 days. Outcome measures including insulin resistance, BMI, waist hip ratio, lipid profile, and menstrual interval will be assessed before and after treatment. Data will be analyzed statistically.