Frontiers in endocrinology · 2025
Distribution of prolactin and its correlation with insulin resistance in women with polycystic ovary syndrome.
СтатьяНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Ghobrial Stefan, Krysiak Robert, Goldstein Tal, Patsch Antonella, Paternostro Chiara, Heinzl Florian, Marculescu Rodrig, Ott Johannes
Аннотация
INTRODUCTION: Polycystic ovary syndrome (PCOS) is often associated with insulin resistance (IR). The role of prolactin (PRL) in this context remains unclear, particularly across different PCOS phenotypes. The aim of this study was to investigate the distribution of PRL, as well as its correlation with basal IR in women with PCOS.
METHODS: 200 women with PCOS, evenly distributed across phenotypes A-D and matched for age and body mass index (BMI) were retrospectively analyzed. PRL, Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), sexual hormone binding globulin (SHBG), testosterone, and BMI were assessed. Correlation analysis and unsupervised clustering (based on PRL and HOMA-IR) were performed.
RESULTS: PRL levels were similar across phenotypes, but phenotype D had a significantly lower prevalence of HOMA-IR ≥ 2.5 (p = 0.032). PRL was inversely correlated with HOMA-IR in all groups (p < 0.05). Cluster analysis identified three distinct subgroups, independent of phenotype, differing significantly in both PRL and HOMA-IR.
CONCLUSION: PRL is inversely associated with IR in PCOS, regardless of phenotype. Cluster analysis reveals metabolic subtypes not captured by current phenotype-based classification, suggesting potential for improved risk stratification.
METHODS: 200 women with PCOS, evenly distributed across phenotypes A-D and matched for age and body mass index (BMI) were retrospectively analyzed. PRL, Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), sexual hormone binding globulin (SHBG), testosterone, and BMI were assessed. Correlation analysis and unsupervised clustering (based on PRL and HOMA-IR) were performed.
RESULTS: PRL levels were similar across phenotypes, but phenotype D had a significantly lower prevalence of HOMA-IR ≥ 2.5 (p = 0.032). PRL was inversely correlated with HOMA-IR in all groups (p < 0.05). Cluster analysis identified three distinct subgroups, independent of phenotype, differing significantly in both PRL and HOMA-IR.
CONCLUSION: PRL is inversely associated with IR in PCOS, regardless of phenotype. Cluster analysis reveals metabolic subtypes not captured by current phenotype-based classification, suggesting potential for improved risk stratification.