The minimum frequency of glucose measurements from which glycemic variation can be consistently assessed.
OBJECTIVE
While there has been much debate about the clinical importance of glycemic variation (GV), little attention has been directed to the properties of data sets from which it is measured. The purpose of this study is to assess the minimum frequency of glucose measurements from which GV can be consistently and meaningfully measured.


METHODS
Forty-eight 72 h continuous glucose monitoring traces from children with type 1 diabetes were assessed. Measures of GV included standard deviation (SD), mean amplitude of glycemic excursion (MAGE), and continuous overlapping net glycemic action (CONGA1-4). Measures of GV calculated using 5 min sampling were designated as the 100% or "best estimate" value. Calculations were then repeated for each patient using glucose values spaced at increasing intervals. For each of the specified sampling frequencies, the ratio (%) of the between-subject SD based on the reduced subset of data to the estimate of the SD based on the full 5 min sampling data set was calculated.


RESULTS
As the interval between observations increased, so did the variability of the estimators of GV. Standard deviation exhibited the least systematic change at all measurement intervals, and MAGE exhibited the greatest systematic change.


CONCLUSIONS
In patients with type 1 diabetes, GV as measured by SD or CONGA4, becomes unreliable if observations are more than 2-4 h apart, and estimates of MAGE become unreliable if glucose measurements are more than 1 h apart. MAGE is more unstable and prone to random measurement error than either SD or CONGA. The frequency of glycemic measurements is thus pivotal when selecting a parameter for measurement of GV.
Public Health Research Unit, Women's and Children's Hospital, Children Youth and Women's Health Service, North Adelaide, South Australia.
Peter A
PA
Baghurst
David
D
Rodbard
Fergus J
FJ
Cameron
D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000187:drug effects / Q000378:metabolism*; D002648:Child; D002675:Child, Preschool; D003922:Diabetes Mellitus, Type 1 / Q000097:blood* / Q000188:drug therapy; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D007004:Hypoglycemic Agents / Q000008:administration & dosage; D007328:Insulin / Q000008:administration & dosage; D008991:Monitoring, Physiologic / Q000379:methods*; D011237:Predictive Value of Tests; D013997:Time Factors
D015415:Biomarkers; D001786:Blood Glucose; D006442:Glycated Hemoglobin; D007004:Hypoglycemic Agents; D007328:Insulin; C517652:hemoglobin A1c protein, human