PMID- 37929026
OWN - NLM
STAT- MEDLINE
DCOM- 20231107
LR  - 20231107
IS  - 1664-2392 (Print)
IS  - 1664-2392 (Electronic)
IS  - 1664-2392 (Linking)
VI  - 14
DP  - 2023
TI  - Unsupervised cluster analysis of clinical and metabolite characteristics in 
      patients with chronic complications of T2DM: an observational study of real data.
PG  - 1230921
LID - 10.3389/fendo.2023.1230921 [doi]
LID - 1230921
AB  - INTRODUCTION: The aim of this study was to cluster patients with chronic 
      complications of type 2 diabetes mellitus (T2DM) by cluster analysis in Dalian, 
      China, and examine the variance in risk of different chronic complications and 
      metabolic levels among the various subclusters. METHODS: 2267 hospitalized 
      patients were included in the K-means cluster analysis based on 11 variables 
      [Body Mass Index (BMI), Systolic Blood Pressure (SBP), Diastolic Blood Pressure 
      (DBP), Glucose, Triglycerides (TG), Total Cholesterol (TC), Uric Acid (UA), 
      microalbuminuria (mAlb), Insulin, Insulin Sensitivity Index (ISI) and Homa 
      Insulin-Resistance (Homa-IR)]. The risk of various chronic complications of T2DM 
      in different subclusters was analyzed by multivariate logistic regression, and 
      the Kruskal-Wallis H test and the Nemenyi test examined the differences in 
      metabolites among different subclusters. RESULTS: Four subclusters were 
      identified by clustering analysis, and each subcluster had significant features 
      and was labeled with a different level of risk. Cluster 1 contained 1112 
      inpatients (49.05%), labeled as "Low-Risk"; cluster 2 included 859 (37.89%) 
      inpatients, the label characteristics as "Medium-Low-Risk"; cluster 3 included 
      134 (5.91%) inpatients, labeled "Medium-Risk"; cluster 4 included 162 (7.15%) 
      inpatients, and the label feature was "High-Risk". Additionally, in different 
      subclusters, the proportion of patients with multiple chronic complications was 
      different, and the risk of the same chronic complication also had significant 
      differences. Compared to the "Low-Risk" cluster, the other three clusters exhibit 
      a higher risk of microangiopathy. After additional adjustment for 20 covariates, 
      the odds ratios (ORs) and 95% confidence intervals (95%CI) of the 
      "Medium-Low-Risk" cluster, the "Medium-Risk" cluster, and the"High-Risk" cluster 
      are 1.369 (1.042, 1.799), 2.188 (1.496, 3.201), and 9.644 (5.851, 15.896) (all 
      p<0.05). Representatively, the "High-Risk" cluster had the highest risk of DN [OR 
      (95%CI): 11.510(7.139,18.557), (p<0.05)] and DR [OR (95%CI): 3.917(2.526,6.075), 
      (p<0.05)] after 20 variables adjusted. Four metabolites with statistically 
      significant distribution differences when compared with other subclusters 
      [Threonine (Thr), Tyrosine (Tyr), Glutaryl carnitine (C5DC), and Butyryl 
      carnitine (C4)]. CONCLUSION: Patients with chronic complications of T2DM had 
      significant clustering characteristics, and the risk of target organ damage in 
      different subclusters was significantly different, as were the levels of 
      metabolites. Which may become a new idea for the prevention and treatment of 
      chronic complications of T2DM.
CI  - Copyright (c) 2023 Wang, Li, Wang, Dong, Li, Wang, Lin and Zhao.
FAU - Wang, Cuicui
AU  - Wang C
AD  - Department of Health Examination Center, The Second Affiliated Hospital of Dalian 
      Medical University, Dalian, China.
AD  - Department of Gastroenterology, The 986th Hospital of Xijing Hospital, Air Force 
      Military Medical University, Xi'an, China.
FAU - Li, Yan
AU  - Li Y
AD  - State Key Laboratory of Molecular Reaction Dynamics, Dalian Institute of Chemical 
      Physics, Chinese Academy of Science, Dalian, China.
FAU - Wang, Jun
AU  - Wang J
AD  - Department of Gastroenterology, The 986th Hospital of Xijing Hospital, Air Force 
      Military Medical University, Xi'an, China.
FAU - Dong, Kunjie
AU  - Dong K
AD  - School of Computer Science & Technology, Dalian University of Technology, Dalian, 
      China.
FAU - Li, Chenxiang
AU  - Li C
AD  - School of Computer Science & Technology, Dalian University of Technology, Dalian, 
      China.
FAU - Wang, Guiyan
AU  - Wang G
AD  - School of Information Engineering, Dalian Ocean University, Dalian, China.
FAU - Lin, Xiaohui
AU  - Lin X
AD  - School of Computer Science & Technology, Dalian University of Technology, Dalian, 
      China.
FAU - Zhao, Hui
AU  - Zhao H
AD  - Department of Health Examination Center, The Second Affiliated Hospital of Dalian 
      Medical University, Dalian, China.
LA  - eng
PT  - Journal Article
PT  - Observational Study
PT  - Research Support, Non-U.S. Gov't
DEP - 20231020
PL  - Switzerland
TA  - Front Endocrinol (Lausanne)
JT  - Frontiers in endocrinology
JID - 101555782
RN  - 0 (Blood Glucose)
RN  - 0 (Insulin)
RN  - S7UI8SM58A (Carnitine)
SB  - IM
MH  - Humans
MH  - *Diabetes Mellitus, Type 2
MH  - Risk Factors
MH  - Blood Glucose/metabolism
MH  - Insulin
MH  - Carnitine
PMC - PMC10623421
OTO - NOTNLM
OT  - K-means
OT  - T2DM
OT  - chronic complications
OT  - cluster analysis
OT  - metabolite
COIS- The authors declare that the research was conducted in the absence of any 
      commercial or financial relationships that could be construed as a potential 
      conflict of interest.
EDAT- 2023/11/06 06:41
MHDA- 2023/11/07 06:46
PMCR- 2023/01/01
CRDT- 2023/11/06 04:45
PHST- 2023/05/29 00:00 [received]
PHST- 2023/09/26 00:00 [accepted]
PHST- 2023/11/07 06:46 [medline]
PHST- 2023/11/06 06:41 [pubmed]
PHST- 2023/11/06 04:45 [entrez]
PHST- 2023/01/01 00:00 [pmc-release]
AID - 10.3389/fendo.2023.1230921 [doi]
PST - epublish
SO  - Front Endocrinol (Lausanne). 2023 Oct 20;14:1230921. doi: 
      10.3389/fendo.2023.1230921. eCollection 2023.