Association of Free Radical Product and Polycystic Ovary Syndrome: A Systematic Review and Meta-analysis

Autoimmune thyroid disorders and polycystic ovary syndrome: Tracing links through systematic review and meta-analysis

Polycystic Ovary Syndrome (PCOS) and Autoimmune Thyroiditis (AIT) are two prevalent endocrine disorders affecting women, often coexisting within the same patient population. This meta-analysis aims to systematically assess and synthesize the existing body of literature to elucidate the intricate relationship between PCOS and AIT. A systematic literature search for relevant observational studies was conducted in electronic databases such as Web of Science, Google Scholar, PubMed, Cochrane, and Scopus until March 2023. All Statistical analyses were performed using CMA Software v3.7 in a random-effects network meta-analysis. In addition, sensitivity and meta-regression analyses were conducted to identify sources of Heterogeneity based on related risk factors. Our meta-analysis included eighteen studies with 3657 participants, which revealed significant differences between PCOS patients and control groups. In particular, a considerable association was detected between PCOS and the presence of AIT (OR = 2.38; 95% CI: 1.63-3.49; P< 0.001) and elevated levels of TSH (SMD = 0.24; 95% CI: 0.06-0.42; P= 0.01), anti-TPO (SMD = 0.36; 95% CI: 0.19-0.53; P< 0.001), anti-TG (SMD = 1.24; 95% CI: 0.37-2.10; P< 0.001), and other positive serum antibodies compared to the control groups. The findings from this meta-analysis may contribute to enhanced diagnostic strategies like complete thyroid function tests, more targeted interventions, and improved patient care for individuals presenting with both PCOS and AIT. Additionally, identifying commonalities between these conditions may pave the way for future research directions, guiding the development of novel therapeutic approaches that address the interconnected nature of PCOS and AIT.

ChatGPT's Efficacy in Queries Regarding Polycystic Ovary Syndrome and Treatment Strategies for Women Experiencing Infertility

This study assesses the efficacy of ChatGPT-4, an advanced artificial intelligence (AI) language model, in delivering precise and comprehensive answers to inquiries regarding managing polycystic ovary syndrome (PCOS)-related infertility. The research team, comprising experienced gynecologists, formulated 460 structured queries encompassing a wide range of common and intricate PCOS scenarios. The queries were: true/false (170), open-ended (165), and multiple-choice (125) and further classified as 'easy', 'moderate', and 'hard'. For true/false questions, ChatGPT-4 achieved a flawless accuracy rate of 100% initially and upon reassessment after 30 days. In the open-ended category, there was a noteworthy enhancement in accuracy, with scores increasing from 5.53 ± 0.89 initially to 5.88 ± 0.43 at the 30-day mark (p < 0.001). Completeness scores for open-ended queries also experienced a significant improvement, rising from 2.35 ± 0.58 to 2.92 ± 0.29 (p < 0.001). In the multiple-choice category, although the accuracy score exhibited a minor decline from 5.96 ± 0.44 to 5.92 ± 0.63 after 30 days (p > 0.05). Completeness scores for multiple-choice questions remained consistent, with initial and 30-day means of 2.98 ± 0.18 and 2.97 ± 0.25, respectively (p > 0.05). ChatGPT-4 demonstrated exceptional performance in true/false queries and significantly improved handling of open-ended questions during the 30 days. These findings emphasize the potential of AI, particularly ChatGPT-4, in enhancing decision-making support for healthcare professionals managing PCOS-related infertility.