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PLoS One. 2017 Jul 7;12(7):e0180937. doi: 10.1371/journal.pone.0180937. eCollection 2017.

Defining and characterizing the critical transition state prior to the type 2 diabetes disease.

Author information

1
HBI Solutions Inc., Palo Alto, California, United States of America.
2
Stanford University, Stanford, California, United States of America.
3
School of Mathematics, South China University of Technology, Guangzhou, China.
4
Clinical and Translational Research Program, Betty Irene Moore Children's Heart Center, Lucile Packard Children's Hospital, Stanford, California, United States of America.
5
School of Electrical Engineering, Southeast University, Nanjing, China.
6
Tianjin Key Laboratory of Cardiovascular Remodeling and Target Organ Injury, Pingjin Hospital Heart Center, Tianjin, China.
7
School of Computer Science and Engineering, South China University of Technology, Guangzhou, China.
8
China Electric Power Research Institute, Beijing, China.
9
School of Medicine, Zhejiang University, Hangzhou, China.
10
Department of Oncology, the First Hospital of Shijiazhuang, Shijiazhuang, Hebei, China.
11
HealthInfoNet, Portland, Maine, United States of America.
12
Health Care Big Data Center, School of Public Health, Zhejiang University, Hangzhou, China.

Abstract

BACKGROUND:

Type 2 diabetes mellitus (T2DM), with increased risk of serious long-term complications, currently represents 8.3% of the adult population. We hypothesized that a critical transition state prior to the new onset T2DM can be revealed through the longitudinal electronic medical record (EMR) analysis.

METHOD:

We applied the transition-based network entropy methodology which previously identified a dynamic driver network (DDN) underlying the critical T2DM transition at the tissue molecular biological level. To profile pre-disease phenotypical changes that indicated a critical transition state, a cohort of 7,334 patients was assembled from the Maine State Health Information Exchange (HIE). These patients all had their first confirmative diagnosis of T2DM between January 1, 2013 and June 30, 2013. The cohort's EMRs from the 24 months preceding their date of first T2DM diagnosis were extracted.

RESULTS:

Analysis of these patients' pre-disease clinical history identified a dynamic driver network (DDN) and an associated critical transition state six months prior to their first confirmative T2DM state.

CONCLUSIONS:

This 6-month window before the disease state provides an early warning of the impending T2DM, warranting an opportunity to apply proactive interventions to prevent or delay the new onset of T2DM.

PMID:
28686739
PMCID:
PMC5501620
DOI:
10.1371/journal.pone.0180937
[Indexed for MEDLINE]
Free PMC Article

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