Early Postoperative Hyperglycemia After Arthroplasty in Type 2 Diabetes: Insights from Continuous Glucose Monitoring and Identification of Predictive Glycemic Parameters.

BACKGROUND: Diabetes mellitus is a well-established risk factor for surgical site infections (SSIs), particularly periprosthetic joint infections (PJIs) following joint arthroplasty. Although strict glycemic control in the early postoperative period is critical, few studies have evaluated glycemic dynamics using continuous glucose monitoring (CGM) in this setting. This study aimed to characterize early postoperative glycemic patterns using CGM in patients with type 2 diabetes mellitus undergoing lower extremity arthroplasty and to identify factors associated with postoperative hyperglycemia. METHODS: We retrospectively analyzed 41 patients with type 2 diabetes who underwent total hip or knee arthroplasty. CGM was used to monitor glucose levels continuously for 48 h after surgery. All patients received standard glycemic management based on a sliding-scale insulin protocol. Patients were classified into two groups: normoglycemia (glucose consistently < 200 mg/dL) and hyperglycemia (glucose ≥ 200 mg/dL at least once within 48 h). Univariable and multivariable logistic regression analyses were conducted to identify predictors of postoperative hyperglycemia. RESULTS: Hyperglycemia occurred in 65.9% of all patients. Univariable analysis identified fasting plasma glucose (FPG), mean postoperative glucose, number of antidiabetic medications, and glucose variability as significant predictors (p < 0.05). In multivariable analysis adjusted for HbA1c, glycoalbumin, and glucose variability, FPG [odds ratio (OR): 1.07; 95% confidence interval (CI): 1.01-1.14; p = 0.024], mean glucose (OR: 1.12; 95% CI: 1.02-1.23; p = 0.017), and glucose variability (OR: 1.19; 95% CI: 1.05-1.35; p = 0.008) remained independently associated with hyperglycemia. CONCLUSIONS: CGM revealed a high incidence of early postoperative hyperglycemia despite conventional sliding-scale insulin therapy. These findings highlight the limitations of current glycemic protocols and underscore the potential of CGM as a diagnostic tool to guide individualized glucose management. Future studies should evaluate whether CGM-guided interventions can improve surgical outcomes, particularly in reducing SSI risk among high-risk diabetic patients.