Accurate diagnosis of diabetes mellitus and new paradigms of classification
Version 2 2020-04-21, 08:26
Version 1 2020-04-21, 08:25
journal contribution
posted on 2020-04-21, 08:26 authored by Sudesna Chatterjee, Melanie J DaviesA cluster analysis of five independent Swedish cohorts of people with diabetes mellitus has identified five clusters of classification based on age at diagnosis, BMI, HbA1c autoantibodies and markers of insulin resistance. Patients in each of the clusters have specific disease characteristics and unique risk profiles for complications from diabetes mellitus.
Funding
The authors acknowledge support from the National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care – East Midlands (NIHR CLAHRC – EM), the Leicester Clinical Trials Unit, and the NIHR Leicester-Loughborough Diet, Lifestyle and Physical Activity Biomedical Research Centre, which is a partnership between University Hospitals of Leicester NHS Trust, Loughborough University and the University of Leicester.
History
Citation
Chatterjee, Sudesna, and Melanie J. Davies. "Accurate diagnosis of diabetes mellitus and new paradigms of classification." Nature Reviews Endocrinology, vol. 14, no. 7, 2018, p. 386+.Version
- AM (Accepted Manuscript)
Published in
NATURE REVIEWS ENDOCRINOLOGYVolume
14Issue
7Pagination
386 - + (2)Publisher
NATURE PUBLISHING GROUPissn
1759-5029eissn
1759-5037Copyright date
2018Available date
2018-05-17Publisher DOI
Publisher version
https://www.nature.com/articles/s41574-018-0025-1Notes
This is a comment on "Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables." Lancet Diabetes Endocrinol. 2018 May;6(5):361-369.Spatial coverage
EnglandLanguage
EnglishUsage metrics
Categories
No categories selectedLicence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC