PMID- 26336020
OWN - NLM
STAT- MEDLINE
DCOM- 20160608
LR  - 20220318
IS  - 0975-4466 (Electronic)
IS  - 0256-4947 (Print)
IS  - 0256-4947 (Linking)
VI  - 35
IP  - 2
DP  - 2015 Mar-Apr
TI  - Levels of the first-phase insulin secretion deficiency as a predictor for type 2 
      diabetes onset by using clinical-metabolic models.
PG  - 138-45
LID - 10.5144/0256-4947.2015.138 [doi]
AB  - AIMS: Type 2 diabetes mellitus (T2DM) is characterized by both decreased insulin 
      sensitivity and impaired insulin secretion. The 2 phases of insulin secretion are 
      the first-phase insulin secretion (1st ISEC) and the second-phase insulin 
      secretion. In this study, we tried to build clinical-metabolic models to predict 
      the 1st ISEC deficiency (ISEC-D) in non-diabetic subjects so that early 
      intervention could be started. DESIGN AND SETTINGS: A cross-sectional study was 
      conducted in the clinical research department of a hospital in Taiwan from 2010 
      to 2011. METHODS: A total of 89 subjects without diabetes were enrolled in the 
      study, including 49 with normal glucose tolerance and 40 pre-diabetes. A 
      frequently sampled intravenous glucose tolerance test was done to determine 
      insulin sensitivity and acute insulin response after the glucose load, which is 
      regarded as the 1st ISEC. Subjects with the lowest tertile of the 1st ISEC were 
      defined as ISEC-D. From the simplest to the most complex, 3 models were build: 
      Model 0: fasting plasma glucose (FPG); Model 1: FPG + body mass index (BMI) + 
      High-density lipoprotein cholesterol (HDL-C); Model 2: Model 1+ fasting plasma 
      insulin (FPI). The area under the receiver-operating characteristic curve (aROC 
      curve) was used to determine the predictive power among these models. An optimal 
      cut-off value was also determined. RESULTS: Among metabolic syndrome (MetS) 
      components (FPG, BMI, and HDL-C), FPG had the greatest aROC curve (70.9%). 
      Moreover, the aROC curves of Models 1 and 2 were all significantly greater than 
      that of FPG (80.4% and 82.3%, respectively). Their aROC curves were also greater 
      than that of the homeostasis model assessment b-cell (HOMA-b) function, which is 
      the most commonly used method to evaluate b-cell function. CONCLUSION: By using 
      only MetS components, ISEC-D could be predicted with an acceptable sensitivity of 
      84.0% and a specificity of 74.0%. However, after adding FPI into the Model, the 
      predictive power of Model 2 did not increase. These model-derived MetS components 
      could be widely used in clinical settings and early detection of non-diabetic 
      subjects with high risk for T2DM.
FAU - Lin, Jiunn-Diann
AU  - Lin JD
AD  - Dr. Jiunn-Diann Lin, Department of Internal Medicine,, Buddhist Xindian Tzu-Chi 
      General Hospital,, No 289, Guanguo Rd, Xindian City,, Taipei County, Taiwan 
      011886, China, T: 2-66289779, F: 0118862-66289009, jdlin1971@yahoo.com.tw.
LA  - eng
PT  - Journal Article
PL  - Saudi Arabia
TA  - Ann Saudi Med
JT  - Annals of Saudi medicine
JID - 8507355
RN  - 0 (Blood Glucose)
RN  - 0 (Insulin)
RN  - 0 (Lipoproteins, HDL)
SB  - IM
MH  - Adult
MH  - Blood Glucose/metabolism
MH  - Body Mass Index
MH  - Cross-Sectional Studies
MH  - Diabetes Mellitus, Type 2/*diagnosis/physiopathology
MH  - Female
MH  - Glucose Tolerance Test
MH  - Humans
MH  - Insulin/*metabolism
MH  - Insulin Resistance
MH  - Insulin Secretion
MH  - Lipoproteins, HDL/blood
MH  - Male
MH  - Metabolic Syndrome/*diagnosis/physiopathology
MH  - Middle Aged
MH  - Models, Biological
MH  - Prediabetic State/*diagnosis/physiopathology
MH  - Predictive Value of Tests
MH  - Sensitivity and Specificity
MH  - Taiwan
PMC - PMC6074135
EDAT- 2015/09/04 06:00
MHDA- 2016/06/09 06:00
PMCR- 2015/03/01
CRDT- 2015/09/04 06:00
PHST- 2015/09/04 06:00 [entrez]
PHST- 2015/09/04 06:00 [pubmed]
PHST- 2016/06/09 06:00 [medline]
PHST- 2015/03/01 00:00 [pmc-release]
AID - asm-2-138 [pii]
AID - 10.5144/0256-4947.2015.138 [doi]
PST - ppublish
SO  - Ann Saudi Med. 2015 Mar-Apr;35(2):138-45. doi: 10.5144/0256-4947.2015.138.