The northeast glucose drift: Stratification of post-breakfast dysglycemia among predominantly Hispanic/Latino adults at-risk or with type 2 diabetes.
The northeast glucose drift: Stratification of post-breakfast dysglycemia among predominantly Hispanic/Latino adults at-risk or with type 2 diabetes.
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DOI:
10.1016/j.eclinm.2021.101241
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发表时间:
2022-01
影响因子:
15.1
通讯作者:
Kerr D
中科院分区:
文献类型:
--
作者:
Barua S;Sabharwal A;Glantz N;Conneely C;Larez A;Bevier W;Kerr D
There is minimal experience in continuous glucose monitoring (CGM) among underserved racial/ethnic minority populations with or at risk of type 2 diabetes (T2D), and therefore a lack of CGM-driven insight for these individuals. We analyzed breakfast-related CGM profiles of free-living, predominantly Hispanic/Latino individuals at-risk of T2D, with pre-T2D, or with non-insulin treated T2D. Starting February 2019, 119 participants in Santa Barbara, CA, USA, (93 female, 87% Hispanic/Latino [predominantly Mexican-American], age 54·4 [±12·1] years), stratified by HbA1c levels into (i) at-risk of T2D, (ii) with pre-T2D, and (iii) with non-insulin treated T2D, wore blinded CGMs for two weeks. We compared valid CGM profiles from 106 of these participants representing glucose response to breakfast using four parameters. A “northeast drift” was observed in breakfast glucose responses comparing at-risk to pre-T2D to T2D participants. T2D participants had a significantly higher pre-breakfast glucose level, glucose rise, glucose incremental area under the curve (all p < 0·0001), and time to glucose peak (p < 0·05) compared to pre-T2D and at-risk participants. After adjusting for demographic and clinical covariates, pre-breakfast glucose and time to peak (p < 0·0001) were significantly associated with HbA1c. The model predicted HbA1c within (0·550·67)% of true laboratory HbA1c values. For predominantly Hispanic/Latino adults, the average two-week breakfast glucose response shows a progression of dysglycemia from at-risk of T2D to pre-T2D to T2D. CGM-based breakfast metrics have the potential to predict HbA1c levels and monitor diabetes progression. US Department of Agriculture (Grant #2018–33800–28404), a seed grant from the industry board fees of the NSF Engineering Research Center for Precise Advanced Technologies and Health Systems for Underserved Populations (PATHS-UP) (Award #1648451), and the Elsevier foundation.
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影响因子:
120.7
作者:
Cheng, Yiling J.;Kanaya, Alka M.;Imperatore, Giuseppina
通讯作者:
Imperatore, Giuseppina
影响因子:
2
作者:
Barua S;Solis L;Parra ER;Uraoka N;Jiang M;Wang H;Rodriguez-Canales J;Wistuba I;Maitra A;Sen S;Rao A
通讯作者:
Rao A
影响因子:
4.1
作者:
Bittel AJ;Bittel DC;Mittendorfer B;Patterson BW;Okunade AL;Abumrad NA;Reeds DN;Cade WT
通讯作者:
Cade WT
影响因子:
16.2
作者:
Hanefeld, M;Koehler, C;Temelkova-Kurktschiev, T
通讯作者:
Temelkova-Kurktschiev, T
影响因子:
5.6
作者:
Jakubowicz, Daniela;Wainstein, Julio;Froy, Oren
通讯作者:
Froy, Oren