Comparative efficacy of Ayurveda treatment regimen and Letrozole along with Yoga module in the management of unexplained and anovulatory female infertility; study protocol for a randomized controlled trial

来曲唑 医学 不育 随机对照试验 养生 无排卵 生活质量(医疗保健) 妊娠率 妇科 物理疗法 怀孕 产科 内科学 三苯氧胺 乳腺癌 癌症 护理部 胰岛素抵抗 胰岛素 生物 遗传学 多囊卵巢
作者
Anubha Chandla,NALNEESH SHARMA,Kavita Vyas,Hemendar Mahajan,Varun Dutt,Arnav Bhavsar,Kirti Tripathi,Sarada Ota,Arunabh Tripathi
出处
期刊:Complementary Medicine Research [Karger Publishers]
卷期号:: 1-19
标识
DOI:10.1159/000542655
摘要

Introduction: Infertility is a significant health problem with psycho-social burden for couples. Ayurveda considers a holistic approach, including complex multimodal regimens in managing infertility. Increasing evidence has shown that Yoga as an adjuvant to infertility treatment increases pregnancy rates. Therefore, this research will investigate the comparative efficacy of Ayurveda regimen and Letrozole, along with integration of Yoga in both groups in female infertility. Methods: The primary outcome, ovulation rate, will be measured through serial transvaginal sonography (TVS) for six consecutive menstrual cycles. The secondary outcome, conception rate, will be measured by definitive signs of pregnancy. Participants' quality of life will be assessed using the Ferti Quality of Life (FertiQOL) tool. The study will randomize 160 women aged 21 to 40 years diagnosed with anovulatory or unexplained infertility into two groups using permuted block randomization. Participants in group I will receive internal oleation with Phala Ghrita (PG) and mild purgation with Gandharvahasta (GH) oil for three consecutive cycles. Standard care group II participants will receive Letrozole tablet once daily from day 3 to day 7 of the menstrual cycle for three cycles. The yoga instructor will take yoga sessions for participants of both groups for 6 months. This study will also use machine learning (ML) models to compare two regimens to predict improvements in outcome variables. The goal is to develop an online platform that aids personalized treatment planning and enhances clinical decision-making. Discussion: This will be the first study to generate evidence on the efficacy of integrated treatment regimens in female infertility, where predictive ML models will be developed.

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