A Processing Algorithm to Address Real-World Data Quality Issues With Continuous Glucose Monitoring Data
Authors' conclusion
Our results underscore the importance of real-world CGM data processing to maintain accurate and reliable CGM metrics for research and clinical care.
Study context
- Population
- Patients with diabetes with 2 weeks of continuous glucose monitoring (CGM) data stored in data warehouses
- Participants
- 2,038 patients
- Outcome
- Duplication errors detected by processing algorithm
Performance
As reported in the abstract
Patients with duplication errors identified
528
Of these, significant difference in ≥1 metric (TIR, CV, GMI or glycemic episode counts) between raw and processed data
25.7%
Patients crossing clinically meaningful thresholds in ≥1 metric after processing
11
Original publication
A Processing Algorithm to Address Real-World Data Quality Issues With Continuous Glucose Monitoring Data. J Diabetes Sci Technol. Published 20 February 2025. doi:10.
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