Profiles of Intraday Glucose in Type 2 Diabetes and Their Association with Complications: An Analysis of Continuous Glucose Monitoring Data

被引:16
|
作者
Varghese, Jithin Sam [1 ]
Ho, Joyce C. [2 ]
Anjana, Ranjit Mohan [3 ,4 ]
Pradeepa, Rajendra [3 ,4 ]
Patel, Shivani A. [5 ]
Jebarani, Saravanan [3 ,4 ]
Baskar, Viswanathan [3 ,4 ]
Narayan, K. M. Venkat [5 ]
Mohan, Viswanathan [3 ,4 ]
机构
[1] Emory Univ, Laney Sch Grad Studies, Nutr & Hlth Sci Doctoral Program, Atlanta, GA 30322 USA
[2] Emory Univ, Dept Comp Sci, Atlanta, GA 30322 USA
[3] Dr Mohans Diabet Special Ctr, Dept Diabetol, Chennai 600086, Tamil Nadu, India
[4] Madras Diabet Res Fdn, Chennai, Tamil Nadu, India
[5] Emory Univ, Rollins Sch Publ Hlth, Hubert Dept Global Hlth, Atlanta, GA 30322 USA
关键词
Ambulatory glucose profile; Cluster analysis; Glycemic variability; Time in range; URBAN-RURAL EPIDEMIOLOGY; BLOOD-GLUCOSE; GLYCEMIC CONTROL; CLUSTER-ANALYSIS; ASIAN INDIANS; VARIABILITY; RETINOPATHY; ADULTS; RISK; HYPOGLYCEMIA;
D O I
10.1089/dia.2020.0672
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Aims: To identify profiles of type 2 diabetes from continuous glucose monitoring (CGM) data using ambulatory glucose profile (AGP) indicators and examine the association with prevalent complications. Methods: Two weeks of CGM data, collected between 2015 and 2019, from 5901 adult type 2 diabetes patients were retrieved from a clinical database in Chennai, India. Non-negative matrix factorization was used to identify profiles as per AGP indicators. The association of profiles with existing complications was examined using multinomial and logistic regressions adjusted for glycated hemoglobin (HbA1c; %), sex, age at onset, and duration of diabetes. Results: Three profiles of glycemic variability (GV) were identified based on CGM data-Profile 1 ["TIR Profile"] (n = 2271), Profile 2 ["Hypo"] (n = 1471), and Profile 3 ["Hyper"] (n = 2159). Compared with time in range (TIR) profile, those belonging to Hyper had higher mean fasting plasma glucose (202.9 vs. 167.1, mg/dL), 2-h postprandial plasma glucose (302.1 vs. 255.6, mg/dL), and HbA1c (9.7 vs. 8.6; %). Both "Hypo profile" and "Hyper profile" had higher odds of nonproliferative diabetic retinopathy ("Hypo": 1.44, 1.20-1.73; "Hyper": 1.33, 1.11-1.58), macroalbuminuria ("Hypo": 1.58, 1.25-1.98; "Hyper": 1.37, 1.10-1.71), and diabetic kidney disease (DKD; "Hypo": 1.65, 1.18-2.31; "Hyper": 1.88, 1.37-2.58), compared with "TIR profile." Those in "Hypo profile" (vs. "TIR profile") had higher odds of proliferative diabetic retinopathy (PDR; 2.84, 1.65-2.88). Conclusions: We have identified three profiles of GV from CGM data. While both "Hypo profile" and "Hyper profile" had higher odds of prevalent DKD compared with "TIR profile," "Hypo profile" had higher odds of PDR. Our study emphasizes the clinical importance of recognizing and treating hypoglycemia (which is often unrecognized without CGM) in patients with type 2 Diabetes Mellitus.
引用
收藏
页码:555 / 564
页数:10
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