Abstract

Glucagon plays a pivotal role in the development of hyperglycemia in diabetes mellitus. The purpose of this study was to investigate the hypothesis that hyperglucagonemia based on measurements of pancreas-specific glucagon is present in diabetic ketosis/ketoacidosis (DK/DKA) and hyperosmolar hyperglycemic state (HHS), and if so, to explore factors contributing to that hyperglucagonemia. A total of 109 patients (92 with DK/DKA, and 17 with HHS) were investigated. Pancreas-specific glucagon levels were measured with a sandwich enzyme-linked immunosorbent assay at treatment initiation. The relationships of plasma glucagon levels, serum ketone bodies levels, and endogenous insulin secretion were assessed. The change in plasma glucagon levels after treatment was also assessed. Hyperglucagonemia was found in DK/DKA and HHS with pancreas-specific glucagon measurements. The results suggest that the causes of hyperglucagonemia differ in DK/DKA due to type 1 diabetes mellitus and HHS. The online version contains supplementary material available at 10.1007/s13340-025-00852-8.

Keywords

Computer scienceArtificial intelligence

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Publication Info

Year
2019
Type
book-chapter
Pages
1-13
Citations
1620
Access
Closed

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Cite This

F. Richard Yu, Ying He (2019). Introduction to Machine Learning. Springer briefs in electrical and computer engineering , 1-13. https://doi.org/10.1007/978-3-030-10546-4_1

Identifiers

DOI
10.1007/978-3-030-10546-4_1
PMID
41292690
PMCID
PMC12640887

Data Quality

Data completeness: 77%