Format

Send to

Choose Destination
Diabetes Metab Syndr. 2017 Apr - Jun;11(2):119-124. doi: 10.1016/j.dsx.2016.08.023. Epub 2016 Aug 23.

Glucose variability indices predict the episodes of nocturnal hypoglycemia in elderly type 2 diabetic patients treated with insulin.

Author information

1
Professor, Laboratory of Endocrinology, Scientific Institute of Clinical and Experimental Lymphology, Timakov Str. 2, Novosibirsk 630060, Russian Federation. Electronic address: klimontov@mail.ru.
2
MD, Laboratory of Endocrinology, Scientific Institute of Clinical and Experimental Lymphology, Novosibirsk, Russian Federation.

Abstract

AIM:

O determine the applicability of glucose variability (GV) indices derived from continuous glucose monitoring (CGM) data for prediction of nocturnal hypoglycemia (NH) in elderly patients with type 2 diabetes treated with insulin.

METHODS:

We observed 83 insulin-treated in-patients, 65-80 years of age. Blinded CGM data for 176 nights were analyzed. Daytime (06:00-22:59) mean glucose, Standard Deviation (SD), 2-h Continuous Overlapping Net Glycemic Action (CONGA2) and Mean Absolute Glucose (MAG), pre-midnight (23:00-23:59) mean glucose, SD and MAG, 24-h Mean Amplitude of Glucose Excursions (MAGE), were estimated. Pre-midnight glucose trends were estimated as the absolute difference between glucose values at 23:00 and 23:59 (deltaG). Episode of interstitial glucose ≤70mg/dL observed from 0:00 to 5:59 was considered as NH.

RESULTS:

NH was present in 68 out of 176 24-h recordings (39%). Lower daytime mean glucose and CONGA2, and higher MAG values were found in patients with NH as compared to those without (p=0.0002, p=0.0001 and p=0.02, respectively). Pre-midnight mean glucose was lower, while pre-midnight deltaG was higher in patients with NH (p<0.0001 and p=0.02). Antecedent daytime hypoglycemia increased the risk of NH (p<0.0001). In logistic regression analysis, the combination of daytime MAG and pre-midnight mean glucose was the most reliable predictor of subsequent NH (accuracy 75.6%, p=0.0004).

CONCLUSION:

The analysis of CGM-derived GV parameters could improve prediction of NH in elderly patients with type 2 diabetes treated with insulin.

KEYWORDS:

Continuous glucose monitoring; Glucose variability; Hypoglycemia; Type 2 diabetes

PMID:
27569727
DOI:
10.1016/j.dsx.2016.08.023
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Elsevier Science
Loading ...
Support Center