[Effect of glycemic variability on the efficacy of artificial pancreas systems: A real-world study]

The artificial pancreas system (APS) has become an important technological approach for the treatment of type 1 diabetes mellitus (T1DM). However, whether patients with different baseline levels of coefficient of variation (CV) achieve different glycemic outcomes after APS use remains unclear. This study aims to investigate the impact of baseline CV levels on the effectiveness of APS therapy.

This retrospective real-world study enrolled patients with T1DM who initiated AndroidAPS (AAPS) through online diabetes communities between January 2019 and April 2024. All participants continuously used AAPS for at least 3 months, and each open-loop interruption lasted no longer than 7 d. Original continuous glucose monitoring (CGM) data were obtained from the Nightscout cloud platform. CGM data from the first 7 d after AAPS initiation were used as baseline values, and the study period was defined as the first 3 months after AAPS initiation. According to internationally recommended cutoff values, patients were categorized into a glycemic stability group (CV≤36%) and a glycemic instability group (CV>36%) based on baseline CV. Changes in CGM metrics before and after APS therapy during the entire day, daytime (06:00-24:00), and nighttime (00:00-06:00) periods were compared between the 2 groups. The primary outcome measures were time in tight range (TITR; glucose range 70 to 140 mg/dL) and time in range (TIR; glucose range 70 to 180 mg/dL). Secondary outcome measures included time above range (TAR; classified as TAR1, TAR2, and TAR3), time below range (TBR; classified as TBR1 and TBR2), mean glucose level, CV, and estimated hemoglobin A1c (eA1c). Analysis of covariance was used to compare changes in glycemic metrics between the groups after 3 months of treatment, and multivariable linear regression models were constructed to analyze factors associated with CV.

A total of 132 patients with T1DM were included, among whom 88 (66.67%) were assigned to the glycemic stability group and 44 (33.33%) to the glycemic instability group. No statistically significant differences were observed between the 2 groups in sex, age, body mass index (BMI), disease duration, glycated hemoglobin A1c (HbA1c) at diagnosis, or chronic complications (all P>0.05). After APS therapy, overall glycemic control significantly improved in both groups compared with baseline. After adjustment for baseline levels, the improvement in all-day TITR was significantly greater in the glycemic stability group than in the glycemic instability group, and TAR1 was significantly improved compared with baseline in the glycemic stability group (all P<0.05). Neither TBR1 nor TBR2 increased significantly after APS therapy in either group, indicating that glycemic improvement in the glycemic stability group was achieved without increasing the risk of hypoglycemia. Regarding glycemic variability, the all-day CV in the glycemic instability group significantly decreased after APS therapy compared with baseline (P<0.05). During daytime periods, after adjustment for baseline levels, no statistically significant differences were observed between the two groups in the degree of improvement in TITR, TAR, TBR, or mean glucose level (all P>0.05). During nighttime periods, improvements in TITR and TIR were significantly greater in the glycemic stability group than in the glycemic instability group, while reductions in TAR1 and TAR2 were also significantly greater in the glycemic stability group (all P<0.05). No statistically significant differences were found in hypoglycemia-related indicators (all P>0.05). Multivariable linear regression analysis showed that baseline eA1c was the only significant factor associated with CV (β=4.095, P<0.001). Age showed a negative correlation trend with CV (P=0.070), whereas sex and disease duration were not significantly associated with CV (all P>0.05).

Baseline CV levels influence glycemic improvement after APS use in patients with T1DM. Patients with more stable glycemic variability are more likely to benefit from closed-loop systems without increasing hypoglycemia risk. In the promotion and clinical application of APS, baseline glycemic variability characteristics should be fully considered to optimize management and treatment strategies.