CGM metrics in with polycystic ovary syndrome with and without insulin resistance: a pilot study

Background and aims: Polycystic ovary syndrome (PCOS) is a common endocrine disorder, often associated with insulin resistance (IR). The association between insulin resistance, hyperinsulinemia with PCOS is well known, independently of obesity. PCOS is often associated with altered glucose tolerance and type 2 diabetes mellitus (T2DM). Our aim was to investigate possible differences in continuous glucose monitoring (CGM) metrics among women with PCOS with and without IR. Methods: We enrolled 34 women [age mean (standard deviation) 22.6 (5.2) years, BMI 27.5 (6.5) kg/m2]. IR was defined as Homeostatic Model Assessment for Insulin Resistance (HOMA-IR) score ≥2. All women underwent 14 days intermittent scanning CGM (isCGM). Following CGM metrics were collected: time in range (70-180 mg/dl), time in tight range (70-140 mg/dL), time above (TAR, level 1 >180 mg/dl and level 2 >250 mg/dl) or below (TBR, level 1<70 mg/dl and level 2<54 mg/dl) range and glycaemic variability (CV, coefficient of variation). Differences in CGM metrics in daytime and nighttime were specifically collected. Results: Women with IR presented higher fat mass than women without IR [37.8 (7.97) vs 27.0 (7.27), p=0.002]. Between women with and without IR there was no difference of time in range (TIR) 70-180 mg/dL [97.0 (6.10) vs 94.5 (6.93), respectively p=0.206] nor TIR 70-140 mg/dL [97.4 (2.44) vs 92.3 (15.2), p=0.227]. Women with IR presented lower coefficient of variation (CV) than women without IR [respectively, 13.7 (3.01) vs 16.2 (4.30), p=0.04]. Comparing daytime and nighttime, CV was significantly different during the daytime [12 (4)% vs 16 (5)%, p=0.04] but not during the nighttime [13 (3)% vs 15 (5)%, p=0.152] Conclusions: Although women with PCOS have not clear glycaemic alterations, higher coefficient of variation has been detected in those without insulin resistance compared to women with insulin resistance, especially in daytime. CGM could help interpreting and highlighting different phenotypes of this condition often predisposing to diabetes.