Peer-reviewed veterinary case report
Remote glucose monitoring system for diabetic dogs
By Xi, Jiri et al.·Published in BMC veterinary research·2025·Department of Gastroenterology, China·View original on PubMed →
PetCaseFinder translated the abstract of this peer-reviewed paper into plain English so pet owners can read it. We do not publish original research — every detail traces back to the citation above. How we work →
Original publication title: Glucose monitoring intelligent tracking system for remote glycemic assessment in diabetic dogs: a novel approach.
- Species:
- dog
Plain-English summary
A group of seven Beagle dogs with diabetes was monitored using a new remote glucose tracking system to help manage their blood sugar levels. The system showed promising results, providing accurate and continuous data on glucose levels, which is crucial for diabetes management. The dogs wore different types of sensors, and those with protective garments had better wear time and data accuracy. This new approach could help veterinarians better manage diabetic dogs' health by providing real-time information and improving treatment plans.
People also search for: diabetic dog glucose monitoring · Beagle diabetes management · remote glucose tracking for dogs
Abstract
Optimizing glucose control is one of the primary goals of diabetes management. This study assessed the feasibility and accuracy of a remote real-time continuous glucose monitoring system (RT-CGMS) integrated with intelligent tracking in diabetic dogs. Seven Beagle dogs were monitored using interstitial sensors across different configurations: adhesive only, adhesive with protective garments, and garments combined with an innovative glucose monitoring approach for remote transmission. Sensor wear time was slightly longer with garments (8.2 ± 6.7 vs. 5.8 ± 3.1 days; P > 0.05). Valid data acquisition was significantly higher in the remote-monitoring group [95 (84, 96)] compared to Group 1 [67 (47, 78)] and Group 2 [76 (64, 80), P < 0.001 for both]. A strong correlation was found between RT-CGMS and PBGM measurements (r = 0.904). Calibration improved accuracy at glucose levels ≥ 5.5 mmol/L, reducing MARD from 28.5 to 14.5% and increasing Bland-Altman agreement from 48 to 67%. However, MAD slightly increased in the < 5.5 mmol/L range (2.2 to 2.7 mmol/L). Frequent hyperglycemia, high variability, and glucose excursions were observed. In conclusion, RT-CGMS with intelligent tracking improved data continuity and accuracy in diabetic dogs. Future research should focus on improving the system's sensitivity under hypoglycemic conditions and exploring its broader applications, including its role in enhancing in-hospital glucose management, utilizing big data to facilitate online diagnostics and offline follow-up care, providing guidance for daily glucose stabilization, enabling personalized veterinary services, and offering subscription-based health reports for pet owners.
Find similar cases for your pet
PetCaseFinder finds other peer-reviewed reports of pets with the same symptoms, plus a plain-English summary of what was tried across them.
Search related cases →Original publication on PubMed: https://pubmed.ncbi.nlm.nih.gov/40382616/