Longitudinal Evaluation of Glucose Profile and Obesity Using Continuous Glucose Monitoring, Bioelectrical Impedance Analysis, and Computed Tomography Fat Scan in a Patient Who Achieved Diabetes Remission After Laparoscopic Sleeve Gastrectomy Duodenojejunal Bypass
Year: 2025
Type: article
Study design: Case Report
Abstract: Background/Objective: Laparoscopic sleeve gastrectomy/duodenojejunal bypass (LSG/DJB) aids weight loss and improves type 2 diabetes mellitus (T2DM) in patients with obesity. Herein, we present a 1-year longitudinal evaluation using continuous glucose monitoring (CGM), bioelectrical impedance analysis (BIA), and computed tomography (CT) fat scans after LSG/DJB in a patient with obesity and T2DM. Case Presentation: Our patient was a 33-year-old female with obesity and T2DM who had been treated with intensive insulin therapy (50 units/d) before LSG/DJB. Preoperatively, the patient had uncontrolled diabetes, with a fasting blood glucose level of 252 mg/dL and HbA1c of 10.0%. Moreover, the CGM showed 1%, 99%, and 0% time-in range (TIR), time-above range, and time-below range, respectively. LSG/DJB significantly increased the 3-, 6-, and 12-month TIR to 96%, 93%, and 89%, respectively, and decreased the time-above range to 4%, 7%, and 11%, respectively, indicating high-dose insulin withdrawal and complete diabetes remission. Twelve months post-LSG/DJB, effective abdominal fat mass loss was observed on CT. Furthermore, both FM and the percentage of fat mass were reduced, and muscle mass was maintained according to the BIA. Discussion: Effective weight loss, abdominal FM loss, and complete diabetes remission were observed after LSG/DJB, according to BIA and CT. The significant increase in TIR suggests that this therapeutic approach may improve the prognosis of patients with T2DM and obesity. Conclusion: CGM, BIA, and CT fat scans are highly useful for the long-term management of obesity and diabetes after LSG/DJB surgery.
Source: AACE Endocrinology and Diabetes
Institution: Oita University
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W4416703510
