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A predictive tool for the self‐management of diabetes (Librae): evaluation using a continuous glucose monitoring system
Author(s) -
Franklin V. L.,
Wilson A. W.,
Butler R. A.,
Greene S. A.
Publication year - 2006
Publication title -
diabetic medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.474
H-Index - 145
eISSN - 1464-5491
pISSN - 0742-3071
DOI - 10.1111/j.1464-5491.2005.01770.x
Subject(s) - medicine , continuous glucose monitoring , diabetes mellitus , confidence interval , usability , blood glucose self monitoring , diabetes management , type 1 diabetes , blood glucose monitoring , insulin , self monitoring , emergency medicine , physical therapy , type 2 diabetes , endocrinology , computer science , human–computer interaction , psychology , social psychology
Aims Diabetes self‐management involves a difficult balancing act between insulin, food and exercise. The challenge is to develop innovative, validated algorithms to aid patient decision‐making and optimize glycaemic control. ‘Librae’ is a computerized diabetes simulator in diary format, developed as an educational predictive tool for patients, reducing ‘trial and error’ by allowing patients to simulate and experiment with dietary or insulin adjustments on a ‘body double’. We have evaluated the predictive ability of Librae using continuous blood glucose monitoring (CGMS). Methods Patients with Type 1 Diabetes attending the Paediatric Clinic were invited to use ‘Librae’ for 1 week and were then fitted with a CGMS for 72 h. The predictive ability of ‘Librae’ was compared with concurrent data obtained from the CGMS. Results Seven thousand nine hundred and sixty paired blood glucose values were obtained from the 11 patients who completed the study. ‘Librae’ underestimated the measured CGMS values, the error having a positive mean of 0.35 mmol/l (95% confidence interval 0.22–0.48 mmol/l). However, Librae tended to overestimate at low levels of blood glucose readings, and underestimate at high levels of blood glucose readings. Conclusion The modelled values of ‘Librae’ correlated well with the CGMS data, but clinically unacceptable errors occurred at extremes of blood glucose levels. Concurrent CGMS recordings have provided a large data set to modify and improve the existing Librae model and patient feedback has led to improvements in its usability. Librae may provide a useful tool to improve diabetes self‐management education and optimize glycaemic control.