Objective: This study aimed to evaluate the appropriateness of ChatGPT's responses to frequently asked queries regarding the prevention and treatment of premature ovarian insufficiency (POI). Methods: A set of 25 questions covering topics related to disease risk factors, screening, symptoms, treatment, and treatment adverse effects were posed to ChatGPT, and the responses were evaluated by two experienced obstetrician/gynecologists. Results: Of the responses given by ChatGPT, 19 of 25 (76%) were deemed appropriate, five (20%) were rated as inappropriate, and the remaining one (4%) was considered unreliable. There was no question that ChatGPT answered completely incorrectly; answers that were considered inappropriate included partially correct information. Conclusions: The study's findings suggest that ChatGPT provides patients with mostly accurate information about the POI but might present significantly inaccurate information. However, it is important to note that further research is needed to validate the use of artificial intelligence chatbots in the context of reproductive health, especially for individuals who may be highly impacted by the emotional and psychological effects of POI. In addition, given the complexity and individuality of medical care, AI chatbots should not be considered a replacement for medical professionals but rather a supplementary tool that can help patients access reliable information and support. Overall, this study contributes to the growing body of research on AI chatbots and their potential use in reproductive health, highlighting both the benefits and limitations of these technologies.

Objective: This study aimed to evaluate the prognostic value of C-reactive protein velocity (CRPv) and inflammatory burden index (IBI) as novel systemic inflammatory biomarkers in predicting the latent period in pregnancies complicated by preterm premature rupture of membranes (PPROM). We investigated the role of these markers in estimating the timing of delivery and their association with perinatal and neonatal outcomes. Methods: This retrospective cohort study included 337 singleton pregnancies diagnosed with PPROM at Ankara Etlik City Hospital between January 1, 2024, and January 1, 2025. Patients were divided into two groups based on the latency period. Maternal inflammatory markers, CRPv, and IBI, were recorded and analyzed. The relationship between these inflammatory markers and latency period was assessed, and ROC curve analysis was performed to determine optimal cutoff values. Results: CRPv and IBI values were significantly higher in patients with a latency period of less than 48 h compared to those delivering after 48 h (p < 0.001). ROC analysis revealed that CRPv > 0.17 had 70% sensitivity and 67% specificity in predicting delivery within 48 h (AUC = 0.675, p < 0.001), while IBI > 35.8 demonstrated predictive accuracy for early delivery (AUC = 0.563, p = 0.047). Conclusion: CRPv and IBI are promising inflammatory biomarkers for predicting the latency period in PPROM pregnancies. Their incorporation into clinical management may improve risk stratification, aiding in timely interventions to optimize maternal and neonatal outcomes. Further prospective studies are warranted to validate these findings and explore their integration into standard obstetric care.

Ejmi Eurasian Journal of Medical Investigation