Literature DB >> 27651425

Long-Term Prediction of Severe Hypoglycemia in Type 1 Diabetes: Is It Really Possible?

Marie Moth Henriksen1, Louise Færch2, Birger Thorsteinsson2,3, Ulrik Pedersen-Bjergaard2,3.   

Abstract

BACKGROUND: Prediction of risk of severe hypoglycemia (SH) in patients with type 1 diabetes is important to prevent future episodes, but it is unknown if it is possible to predict the long-term risk of SH. The aim of the study is to assess if long-term prediction of SH is possible in type 1 diabetes.
METHODS: A follow-up study was performed with 98 patients with type 1 diabetes. At baseline and at follow-up, the patients filled in a questionnaire about diabetes history and complications, number of SH in the preceding year and state of awareness, and HbA1c and C-peptide levels were measured.
RESULTS: During the 12 years of follow-up, there was a decrease in HbA1c, C-peptide levels, and incidence of SH (1.1 to 0.4 episodes per patient-year; P < .001). At baseline, the relative rate of SH was 3.6 (P = .001) and 10.9 (P < .0001) in patients with impaired awareness and unawareness of hypoglycemia, respectively, as compared to patients with normal awareness. At follow-up, patients with unawareness at baseline tended to have maintained an increased rate of SH (RR = 3.1; P = .07). Impaired awareness, HbA1c and C-peptide determined at baseline did not correspond with an increased rate of SH at follow-up.
CONCLUSIONS: Long-term prediction of severe hypoglycemia in type 1 diabetes was not possible, although baseline hypoglycemia unawareness tended to remain a predictor for risk of SH at follow-up. Therefore, it is important repeatedly to assess the different risk factors of SH to determine the actual risk.
© 2016 Diabetes Technology Society.

Entities:  

Keywords:  hypoglycemia awareness; prediction; severe hypoglycemia; type 1 diabetes

Mesh:

Substances:

Year:  2016        PMID: 27651425      PMCID: PMC5094341          DOI: 10.1177/1932296816664745

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


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