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HBA1C and mean glucose derived from short term continuous glucose monitoring (CGM) assessment do not correlate in patients with HBA1C >8
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Yamada, Eijiro, Okada, Shuichi, Nakajima, Yasuyo, Bastie, Claire C., Vatish, Manu, Tagaya, Yuko, Osaki, Aya, Shimoda, Yoko, Shibusawa, Ryo, Saito, Tsugumichi, Okamura, Takashi, Ozawa, Atsushi and Yamada, Masanobu (2017) HBA1C and mean glucose derived from short term continuous glucose monitoring (CGM) assessment do not correlate in patients with HBA1C >8. Endocrine Practice . doi:10.4158/EP161363.OR ISSN 1530-891X.
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Official URL: http://dx.doi.org/10.4158/EP161363.OR
Abstract
Aims: Optimum therapy for patients with diabetes depends on both acute and long-term changes in plasma glucose, generally assessed by HbA1c levels. However, the correlation between HbA1c and circulating glucose has not been fully determined. Therefore, we carefully examined this correlation when glucose levels were assessed by continuous glucose monitoring (CGM).
Methods: 51 patients (70 % women, 30% male) were examined; among them were 28 type 1 patients with diabetes and 23 type 2 patients with diabetes. Clinically determined HbA1c levels were compared with blood glucose determined by CGM during a short time period.
Results: Changes of HbA1c levels up to 8.0% showed a clear and statistically strong correlation (R=0.6713, P<0.0001) with mean blood glucose levels measured by CGM, similarly to that observed in the A1c-derived Average Glucose (ADAG) study where patients were monitored for a longer period. However, we found no statistical correlation (R=0.0498, P=0.8298) between HbA1c and CGM-assessed glucose levels in our patient population when HbA1c was greater than 8.0 %
Conclusions: Short term CGM appears to be a good clinical indicator of long-term glucose control (HbA1c levels), however cautions should be taken while interpreting CGM data from patients with HbA1c levels above 8.0%. Over or under estimation of the actual mean glucose from CGM data could potentially increase the risks of inappropriate treatment. As such, our results indicate that a more accurate analysis of CGM data might be useful to adequately tailor clinical treatments.
Item Type: | Journal Article | ||||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School > Biomedical Sciences > Translational & Experimental Medicine Faculty of Science, Engineering and Medicine > Medicine > Warwick Medical School |
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Journal or Publication Title: | Endocrine Practice | ||||||||
Publisher: | American Association of Clinical Endocrinologists | ||||||||
ISSN: | 1530-891X | ||||||||
Official Date: | January 2017 | ||||||||
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DOI: | 10.4158/EP161363.OR | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access |
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