Influence of Diabetogenic Factors on Fasting and Postprandial Glucose Levels in Patients with Type 2 Diabetes Mellitus

被引:1
作者
Chang, Yuan-Tung [1 ]
Wu, Chung-Ze [1 ,2 ]
Hsieh, Chang-Hsun [3 ]
Chang, Jin-Biou [4 ]
Liang, Yao-Jen [5 ]
Chen, Yen-Lin [6 ]
Pei, Dee [7 ]
Lin, Jiunn-Diann [1 ,2 ]
机构
[1] Taipei Med Univ, Shuang Ho Hosp, Dept Internal Med, Div Endocrinol, 291 Jhongzheng Rd, New Taipei 23561, Taiwan
[2] Taipei Med Univ, Coll Med, Sch Med, Div Endocrinol & Metab,Dept Internal Med, Taipei, Taiwan
[3] Triserv Gen Hosp, Natl Def Med Sch, Dept Internal Med, Div Endocrinol & Metab, Taipei, Taiwan
[4] Natl Def Med Ctr, Triserv Gen Hosp, Dept Pathol, Div Clin Pathol, Taipei, Taiwan
[5] Fu Jen Catholic Univ, Dept & Inst Life Sci, New Taipei, Taiwan
[6] Fu Jen Catholic Univ, Cardinal Tien Hosp, Sch Med, Dept Pathol, Taipei, Taiwan
[7] Fu Jen Catholic Univ, Fu Jen Catholic Hosp, Sch Med, Dept Internal Med, Taipei, Taiwan
关键词
first-phase insulin secretion; second-phase insulin secretion; insulin resistance; glucose effectiveness; type 2 diabetes mellitus; BETA-CELL FUNCTION; PHASIC INSULIN RELEASE; RELATIVE CONTRIBUTIONS; RESISTANCE; TOLERANCE; SECRETION; 1ST-PHASE; MUSCLE; NIDDM; CLAMP;
D O I
10.1089/met.2019.0028
中图分类号
R-3 [医学研究方法]; R3 [基础医学];
学科分类号
1001 ;
摘要
Background: This study evaluated the relative influence of insulin resistance (IR), first-phase insulin secretion (FPIS), second-phase insulin secretion (SPIS), and glucose effectiveness (GE) in determining the difference between fasting plasma glucose (FPG) and postprandial plasma glucose (PPG) (Delta PG), in a Chinese population with type 2 diabetes (T2D) mellitus. Methods: In total, we enrolled 1213 participants with T2D (479 women). IR, FPIS, SPIS, and GE were estimated by using equations we built previously. Delta PG was defined as FPG - PPG. Results: The relative contribution of the four diabetogenic factors (DFs) was analyzed by multiple linear regression, and GE was the greatest contributor in the Delta PG value (beta = 0.171, P < 0.001), whereas IR had the least influence on Delta PG (beta = -0.040, P = 0.439). DFs were analyzed by using binary logistic regression to ascertain if Delta PG >= 0 (high fasting plasma glucose, HFG). Three models were built: Model 0: SPIS, Model 1: SPIS + FPIS, and Model 2: Model 1 + GE. Model 2 had the most accurate predictive power; the equation for Model 2 is P = 1/(1 - e(-x)), where x = -11.88 + 312.89 x (GE) -1.22 x log(SPIS) +1.63 x log(FPIS). In this equation, P refers to the risk of HFG. Conclusions: For Chinese patients, GE had the most profound effect in determining Delta PG, followed by FPIS, SPIS, and IR. The model suggested that participants with high FPIS, SPIS, and GE would have a high incidence of HFG.
引用
收藏
页码:465 / 471
页数:7
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