Effects of dysregulated glucose metabolism on the occurrence and ART outcome of endometriosis
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Endometriosis patients exhibited higher insulin levels, and a prediction model combining metabolic indexes showed promise for identifying endometriosis, with glucose and insulin levels associated with GDM in both groups.
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Abstract
Abstract Background Endometriosis is associated with systemic metabolic indicators, including body mass index (BMI), glucose metabolism and lipid metabolism, while the association between metabolic indexes and the occurrence and assisted reproductive technology (ART) outcome of endometriosis is unclear. We aimed to evaluate the characteristics of systemic metabolic indexes of endometriosis patients with infertility and their effects on pregnancy outcome after ART treatment. Methods A retrospective cohort study involve 412 endometriosis patients and 1551 controls was conducted. Primary outcome was metabolic indexes, and secondary measures consisted of the influence of metabolic indexes on the number of retrieved oocytes and ART outcomes. Results Endometriosis patients had higher insulin (INS) [6.90(5.10–9.50) vs 6.50(4.80–8.90) μU/mL, P = 0.005]. A prediction model for endometriosis combining the number of previous pregnancies, CA125, fasting blood glucose (Glu) and INS, had a sensitivity of 73.9%, specificity of 67.8% and area under curve (AUC) of 0.77. There were no significant differences in ART outcomes and complications during pregnancy. The serum levels of Glu before pregnancy were associated with GDM both in endometriosis group (aOR 12.95, 95% CI 1.69–99.42, P = 0.014) and in control group (aOR 4.15, 95% CI 1.50–11.53, P = 0.006). Conclusions We found serum Glu is related to the number of retrieved oocytes in control group, serum INS is related to the number of retrieved oocytes in endometriosis group, while serum Glu and INS before pregnancy are related to the occurrence of GDM in two groups. A prediction model based on metabolic indexes was established, representing a promising non-invasive method to predict endometriosis patients with known pregnancy history.
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