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Lameijer A, Bakker JJ, Kao K, Xu Y, Gans ROB, Bilo HJG, Dunn TC, van Dijk PR. Real-life 24-week changes in glycemic parameters among European users of flash glucose monitoring with type 1 and 2 diabetes and different levels of glycemic control. Diabetes Res Clin Pract 2023:110735. [PMID: 37276981 DOI: 10.1016/j.diabres.2023.110735] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 05/05/2023] [Accepted: 05/30/2023] [Indexed: 06/07/2023]
Abstract
AIM To evaluate real-life changes of glycemic parameters among flash glucose monitoring (FLASH) users who do not meet glycemic targets. METHODS De-identified data were obtained between 2014 and 2021 from patients using FLASH uninterrupted for a 24-week period. Glycemic parameters during first and last sensor use were examined in four identifiable groups: type 1 diabetes mellitus (T1DM), type 2 diabetes mellitus (T2DM) on basal-bolus insulin, T2DM on basal insulin, and T2DM without insulin treatment. Within each group, subgroup analyses were performed in persons with initial suboptimal glycemic regulation (time in range (TIR; 3.9-10 mmol/L) <70%, time above range (TAR; >10 mmol/L) >25%, or time below range (TBR; <3.9 mmol/L) >4%). RESULTS Data were obtained from 1,909 persons with T1DM and 1,813 persons with T2DM (1,499 basal-bolus insulin, 189 basal insulin, and 125 non-insulin users). In most of the performed analyses, both overall and in the various subgroups, significant improvements were observed in virtually all predefined primary (TIR) and secondary endpoints (eHbA1c, TAR, TBR and glucose variability). CONCLUSIONS 24-weeks FLASH use in real life by persons with T1DM and T2DM with suboptimal glycemic regulation is associated with improvement of glycemic parameters, irrespective of pre-use regulation or treatment modality.
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Affiliation(s)
- Annel Lameijer
- University of Groningen, University Medical Center Groningen, Department of Endocrinology, Groningen, The Netherlands
| | - Julia J Bakker
- University of Groningen, University Medical Center Groningen, Department of Endocrinology, Groningen, The Netherlands
| | | | | | - Rijk O B Gans
- University of Groningen, University Medical Center Groningen, Department of Internal Medicine, Groningen, The Netherlands
| | - Henk J G Bilo
- University of Groningen, University Medical Center Groningen, Department of Internal Medicine, Groningen, The Netherlands; Isala, Diabetes Research Center, Zwolle, The Netherlands
| | | | - Peter R van Dijk
- University of Groningen, University Medical Center Groningen, Department of Endocrinology, Groningen, The Netherlands; Isala, Diabetes Research Center, Zwolle, The Netherlands.
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Dong S, Wang L, Zhao C, Zhang R, Gao Z, Jiang L, Guo Y, Zhou H, Xu S. Relationship between key continuous glucose monitoring-derived metrics and specific cognitive domains in patients with type 2 diabetes mellitus. BMC Neurol 2023; 23:200. [PMID: 37210479 DOI: 10.1186/s12883-023-03242-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2022] [Accepted: 05/09/2023] [Indexed: 05/22/2023] Open
Abstract
BACKGROUND Continuous glucose monitoring (CGM)-derived time in range (TIR) is closely associated with micro- and macrovascular complications in type 2 diabetes mellitus (T2DM). This study was performed to investigate the relationship between key CGM-derived metrics and specific cognitive domains in patients with T2DM. METHODS Outpatients with T2DM who were otherwise healthy were recruited for this study. A battery of neuropsychological tests was performed to evaluate cognitive function, including memory, executive functioning, visuospatial ability, attention, and language. Participants wore a blinded flash continuous glucose monitoring (FGM) system for 72 h. The key FGM-derived metrics were calculated, including TIR, time below range (TBR), time above range (TAR), glucose coefficient of variation (CV), and mean amplitude of glycemic excursions (MAGE). Furthermore, the glycemia risk index (GRI) was also calculated by the GRI formula. Binary logistic regression was used to assess risk factors for TBR, and we further analysed the associations between neuropsychological test results and key FGM-derived metrics with multiple linear regressions. RESULTS A total of 96 outpatients with T2DM were recruited for this study, with 45.8% experiencing hypoglycemia (TBR< 3.9 mmol/L). Spearman analysis results revealed that a higher TBR< 3.9 mmol/L was correlated with worse performance on the Trail Making Test A (TMTA), Clock Drawing Test (CDT), and cued recall scores (P < 0.05). Logistic regression analysis results indicated that the TMTA (OR = 1.010, P = 0.036) and CDT (OR = 0.429, P = 0.016) scores were significant factors influencing the occurrence of TBR< 3.9 mmol/L. Multiple linear regressions further demonstrated that TBR< 3.9 mmol/L (β = -0.214, P = 0.033), TAR> 13.9 mmol/L (β = -0.216, P = 0.030) and TAR10.1-13.9 mmol/L (β = 0.206, P = 0.042) were significantly correlated with cued recall scores after adjusting for confounding factors. However, TIR, GRI, CV and MAGE showed no significant correlation with the results of neuropsychological tests (P > 0.05). CONCLUSIONS A higher TBR< 3.9 mmol/L and TAR> 13.9 mmol/L were associated with worse cognitive functions (memory, visuospatial ability, and executive functioning). Conversely, a higher TAR of 10.1-13.9 mmol/L was associated with better memory performance in memory tasks.
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Affiliation(s)
- Shanshan Dong
- Department of Endocrinology and Metabolism, The First Hospital of Hebei Medical University, No.89, Donggang Road, Shijiazhuang, 050031, P. R. China
| | - Lina Wang
- Department of Endocrinology and Metabolism, The First Hospital of Hebei Medical University, No.89, Donggang Road, Shijiazhuang, 050031, P. R. China
| | - Chenxu Zhao
- Department of Endocrinology and Metabolism, The First Hospital of Hebei Medical University, No.89, Donggang Road, Shijiazhuang, 050031, P. R. China
| | - Rui Zhang
- Central Laboratory, The First Hospital of Hebei Medical University, Shijiazhuang, 050031, P. R. China
- Hebei International Joint Research Center for Brain Science, Shijiazhuang, 050031, P. R. China
- Hebei Key Laboratory of Brain Science and Psychiatric-Psychologic Disease, Shijiazhuang, 050031, P. R. China
| | - Zhaoyu Gao
- Central Laboratory, The First Hospital of Hebei Medical University, Shijiazhuang, 050031, P. R. China
- Hebei International Joint Research Center for Brain Science, Shijiazhuang, 050031, P. R. China
- Hebei Key Laboratory of Brain Science and Psychiatric-Psychologic Disease, Shijiazhuang, 050031, P. R. China
| | - Lei Jiang
- Central Laboratory, The First Hospital of Hebei Medical University, Shijiazhuang, 050031, P. R. China
- Hebei International Joint Research Center for Brain Science, Shijiazhuang, 050031, P. R. China
- Hebei Key Laboratory of Brain Science and Psychiatric-Psychologic Disease, Shijiazhuang, 050031, P. R. China
| | - Yingying Guo
- Department of Endocrinology and Metabolism, The First Hospital of Hebei Medical University, No.89, Donggang Road, Shijiazhuang, 050031, P. R. China
| | - Huimin Zhou
- Department of Endocrinology and Metabolism, The First Hospital of Hebei Medical University, No.89, Donggang Road, Shijiazhuang, 050031, P. R. China.
- Hebei International Joint Research Center for Brain Science, Shijiazhuang, 050031, P. R. China.
- Hebei Key Laboratory of Brain Science and Psychiatric-Psychologic Disease, Shijiazhuang, 050031, P. R. China.
| | - Shunjiang Xu
- Central Laboratory, The First Hospital of Hebei Medical University, Shijiazhuang, 050031, P. R. China.
- Hebei International Joint Research Center for Brain Science, Shijiazhuang, 050031, P. R. China.
- Hebei Key Laboratory of Brain Science and Psychiatric-Psychologic Disease, Shijiazhuang, 050031, P. R. China.
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Patel PM, Abaniel RM, Dogra N, Lo CB, Frazzitta MA, Virdi NS. Trends in Time in Range-Related Publications and Clinical Trials: A Bibliometric Review. Diabetes Spectr 2023; 36:337-344. [PMID: 38024223 PMCID: PMC10654124 DOI: 10.2337/ds22-0085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/01/2023]
Abstract
Objective The goal of this article was to describe trends in publications (including conference abstracts) and clinical trials that report on glycemic time in range (TIR). Data sources Reviewed databases included but were not limited to MEDLINE and Embase. Clinical trial registries were also sourced. Study selection All studies reporting TIR published between 2010 and 2021 were included. Clinical trials reporting TIR that started in or after 2010 were also included. Non-English publications, abstracts, and clinical trials were excluded. Book chapters, nonhuman studies, and studies not reporting TIR were excluded. Data extraction Manuscript/abstract category, publication year, study region, interventional versus observational role of continuous glucose monitoring (CGM), and clinical trial start and completion dates were captured. Glycemic outcomes reported in publications or trials, including TIR as a primary outcome, A1C, time below range (TBR), and time above range (TAR), were also captured. Results A total of 373 clinical trials, 531 publications, and 620 abstracts were included in the review. The number of trials, publications, and abstracts reporting TIR significantly increased, particularly between 2018 and 2021, during which time the number of clinical trials, publications, and conference abstracts reporting TIR increased by 6-fold, 12-fold, and 4.5-fold, respectively. About 35-44% of studies reported TIR as a primary outcome. Approximately 54% of clinical trials, 47% of publications, and 47% of conference abstracts reported the role of CGM to be observational. TBR was reported more often than TAR. Conclusion The marked increase in the number of trials, publications, and abstracts reporting TIR highlights the increasing significance and acceptance of TIR as an outcome measure in diabetes management.
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Osugi K, Kusunoki Y, Ohigashi M, Kusunoki K, Inoue C, Inoue M, Takagi A, Tsunoda T, Kadoya M, Konishi K, Katsuno T, Koyama H. Association between low-carbohydrate diets and continuous glucose monitoring-derived time in ranges. J Diabetes Investig 2023; 14:659-668. [PMID: 38078864 PMCID: PMC10119912 DOI: 10.1111/jdi.13999] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 01/25/2023] [Accepted: 02/13/2023] [Indexed: 03/05/2023] Open
Abstract
AIMS Low-carbohydrate diets have become popular in the general community. The mutual relationship between the percentage of total energy intake from carbohydrates (CHO/E), glycemic control indices, and diabetes complications remains unclear. MATERIALS AND METHODS This cross-sectional study included 177 patients with type 2 diabetes mellitus who regularly visited outpatient clinics. In this study, dietary questionnaires were used to assess the intake ratio of the three macronutrients, and the low-carbohydrate-diet score was calculated. We investigated the association between the low-carbohydrate-diet score, continuous glucose monitoring (CGM)-derived short-term glycemic control indices, and diabetes complications in patients with type 2 diabetes mellitus. RESULTS The results are presented as medians (interquartile ranges) unless otherwise stated. Hemoglobin A1c was 7.1% (6.6-7.7%), CGM-derived time in range (TIR) was 75.3% (62.8-87.0%), body mass index (BMI) was 24.0 (22.1-26.3) kg/m2, and CHO/E was 49.8% (44.8-55.6%). BMI, triglycerides, and CGM-derived time above range decreased significantly with increasing low-carbohydrate-diet scores. However, no significant association was found between the low-carbohydrate-diet score and glycemic control indices, including TIR, mean amplitude of glycemic excursions, and vascular complications of type 2 diabetes mellitus. CONCLUSION Moderate-carbohydrate diets positively impact weight control and lipid metabolism but may have a limited effect on short-term glycemic variability in Japanese patients with type 2 diabetes mellitus.
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Affiliation(s)
- Keiko Osugi
- Department of Diabetes, Endocrinology and Clinical Immunology, School of MedicineHyogo Medical UniversityNishinomiyaHyogoJapan
| | - Yoshiki Kusunoki
- Department of Diabetes, Endocrinology and Clinical Immunology, School of MedicineHyogo Medical UniversityNishinomiyaHyogoJapan
- Kusunoki ClinicNeyagawa, OsakaJapan
| | - Mana Ohigashi
- Department of Diabetes, Endocrinology and Clinical Immunology, School of MedicineHyogo Medical UniversityNishinomiyaHyogoJapan
| | | | - Chikako Inoue
- Department of Diabetes, Endocrinology and Clinical Immunology, School of MedicineHyogo Medical UniversityNishinomiyaHyogoJapan
| | - Maki Inoue
- Department of Diabetes, Endocrinology and Clinical Immunology, School of MedicineHyogo Medical UniversityNishinomiyaHyogoJapan
| | - Ayako Takagi
- Department of Diabetes, Endocrinology and Clinical Immunology, School of MedicineHyogo Medical UniversityNishinomiyaHyogoJapan
| | - Taku Tsunoda
- Department of Diabetes, Endocrinology and Clinical Immunology, School of MedicineHyogo Medical UniversityNishinomiyaHyogoJapan
| | - Manabu Kadoya
- Department of Diabetes, Endocrinology and Clinical Immunology, School of MedicineHyogo Medical UniversityNishinomiyaHyogoJapan
| | - Kosuke Konishi
- Department of Diabetes, Endocrinology and Clinical Immunology, School of MedicineHyogo Medical UniversityNishinomiyaHyogoJapan
| | - Tomoyuki Katsuno
- Department of Occupational Therapy, School of RehabilitationHyogo Medical UniversityNishinomiyaHyogoJapan
| | - Hidenori Koyama
- Department of Diabetes, Endocrinology and Clinical Immunology, School of MedicineHyogo Medical UniversityNishinomiyaHyogoJapan
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Bailey TS, Bode BW, Wang Q, Knights AW, Chang AM. Increased Time in Range with Ultra Rapid Lispro Treatment in Participants with Type 2 Diabetes: PRONTO-Time in Range. Diabetes Ther 2023; 14:883-897. [PMID: 37029268 PMCID: PMC10081815 DOI: 10.1007/s13300-023-01400-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 03/22/2023] [Indexed: 04/09/2023] Open
Abstract
INTRODUCTION To evaluate time in range metrics and HbA1c in people with type 2 diabetes (T2D) treated with ultra rapid lispro (URLi) using continuous glucose monitoring (CGM) for the first time in this population. METHODS This was a Phase 3b, 12-week, single-treatment study in adults with T2D on basal-bolus multiple daily injection (MDI) therapy using basal insulin glargine U-100 along with a rapid-acting insulin analog. Following a 4-week baseline period, 176 participants were newly treated with prandial URLi. Participants used unblinded CGM (Freestyle Libre). Primary endpoint was time in range (TIR) (70-180 mg/dl) during the daytime period at Week 12 compared to baseline with gated secondary endpoints of HbA1c change from baseline and 24-h TIR (70-180 mg/dl). RESULTS Improved glycemic control was observed at Week 12 versus baseline including mean daytime TIR (change from baseline [Δ] 3.8%; P = 0.007), HbA1c (Δ - 0.44%; P < 0.001), and 24-h TIR (Δ 3.3%; P = 0.016) with no significant difference in time below range (TBR). After 12 weeks, there was a statistically significant decrease in postprandial glucose incremental area under curve, overall, across all meals, within 1 h (P = 0.005) or 2 h (P < 0.001) after the start of a meal. Basal, bolus, and total insulin dose were intensified with increased bolus/total dose ratio at Week 12 (50.7%) versus baseline (44.5%; P < 0.001). There were no severe hypoglycemia events during the treatment period. CONCLUSIONS In people with T2D, URLi in an MDI regimen was efficacious with improved glycemic control including TIR, HbA1c, and postprandial glucose without increased hypoglycemia/TBR. CLINICAL TRIAL REGISTRATION NUMBER: NCT04605991.
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Affiliation(s)
| | - Bruce W Bode
- Atlanta Diabetes Associates Hospital, Atlanta, GA, USA
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Fu G, Zhou Z, Jian B, Huang S, Feng Z, Liang M, Liu Q, Huang Y, Liu K, Chen G, Wu Z. Systolic blood pressure time in target range and long-term outcomes in patients with ischemic cardiomyopathy. Am Heart J 2023; 258:177-185. [PMID: 36925271 DOI: 10.1016/j.ahj.2022.12.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 12/13/2022] [Accepted: 12/25/2022] [Indexed: 05/11/2023]
Abstract
BACKGROUND The relationship between the degree of systolic blood pressure (SBP) control and outcomes remains unclear in patients with ischemic cardiomyopathy (ICM). Current control metrics may not take into account the potential effects of SBP fluctuations over time on patients. METHODS This study was a post-hoc analysis of the surgical treatment of ischemic heart failure trial which enrolled 2,136 participants with ICM. Our SBP target range was defined as 110 to 130 mm Hg and the time in target range (TTR) was calculated by linear interpolation. RESULTS A total of 1,194 patients were included. Compared with the quartile 4 group (TTR 77.87%-100%), the adjusted hazard ratios and 95% confidence intervals of all-cause mortality were 1.32 (0.98-1.78) for quartile 3 group (TTR 54.81%-77.63%), 1.40 (1.03-1.90) for quartile 2 group (TTR 32.59%-54.67%), and 1.53 (1.14-2.04) for quartile 1 group (TTR 0%-32.56%). Per 29.28% (1-SD) decrement in TTR significantly increased the risk of all-cause mortality (1.15 [1.04-1.26]). Similar results were observed in the cardiovascular (CV) mortality and the composite outcome of all-cause mortality plus CV rehospitalization, and in the subgroup analyses of either coronary artery bypass grafting or medical therapy, and different baseline SBP. CONCLUSIONS In patients with ICM, the higher TTR was significantly associated with decreased risk of all-cause mortality, CV mortality and the composite outcome of all-cause mortality plus CV rehospitalization, regardless of whether the patient received coronary artery bypass grafting or medical therapy, and the level of baseline SBP. TTR may be a surrogate metric of long-term SBP control in patients with ICM.
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Affiliation(s)
- Guangguo Fu
- Department of Cardiac Surgery, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Zhuoming Zhou
- Department of Cardiac Surgery, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Bohao Jian
- Department of Cardiac Surgery, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Suiqing Huang
- Department of Cardiac Surgery, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Zicong Feng
- Department of Cardiac Surgery, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Mengya Liang
- Department of Cardiac Surgery, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Quan Liu
- Department of Cardiac Surgery, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Yang Huang
- Department of Cardiac Surgery, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Kaizheng Liu
- Department of Cardiac Surgery, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Guangxian Chen
- Department of Cardiac Surgery, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
| | - Zhongkai Wu
- Department of Cardiac Surgery, First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China.
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Chen K, Wu Z, Shi R, Wang Q, Yuan X, Wu G, Shi G, Li C, Chen T. Longer time in blood pressure target range improves cardiovascular outcomes among patients with Type 2 diabetes: A secondary analysis of a randomized clinical trial. Diabetes Res Clin Pract 2023; 198:110600. [PMID: 36858262 DOI: 10.1016/j.diabres.2023.110600] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 02/15/2023] [Accepted: 02/23/2023] [Indexed: 03/03/2023]
Abstract
AIMS To examine the prognostic value of time in target range (TIR) with adverse outcomes and validate it with common blood pressure (BP) metrics among patients with Type 2 diabetes mellitus. METHODS We performed a post hoc analysis of the ACCORD (Action to Control Cardiovascular Risk in Diabetes) trial. TIR for each subject was calculated using linear interpolation and an SBP target range of 110 to 130 mmHg. Cox models were used to assess the association of TIR and other BP metrics with the rate of clinical outcomes. RESULTS A higher TIR (61.9-100.0 %) was associated with a 46 % reduction in major adverse cardiovascular events (MACE) (hazard ratio [HR]:0.54; 95 % CI: 0.43, 0.67) compared with TIR 0-22.9 %. Results were similar for stroke (0.19; 0.10, 0.36), myocardial infarction (0.67; 0.51, 0.89), heart failure (0.47; 0.33, 0.66), cardiovascular death (0.63; 0.42, 0.93) and all-cause mortality (0.70; 0.54, 0.91). Further analyses suggested a curvilinear association of TIR with MACE, and this association was independent with baseline, final SBP, mean SBP, or visit-to-visit SBP variability. CONCLUSIONS Longer TIR is associated with lower cardiovascular risk and may add value as an outcome measure for hypertension control studies among patients with diabetes.
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Affiliation(s)
- KangYu Chen
- Department of Cardiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Zhenqiang Wu
- Department of Geriatric Medicine, The University of Auckland, Auckland, PO Box 93 503, New Zealand
| | - Rui Shi
- Heart Rhythm Centre, The Royal Brompton and Harefield National Health Service Foundation Trust, National Heart and Lung Institute, Imperial College London, London SW3 6NP, United Kingdom
| | - Qi Wang
- Department of Cardiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Xiaodan Yuan
- Department of Health Education, Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Jiangsu Province Academy of Traditional Chinese Medicine, Nanjing 210028, Jiangsu, China
| | - Guohong Wu
- Department of Cardiology, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei 230001, China
| | - Guoshuai Shi
- Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University Health Science Centre, Xi'an 710061, China
| | - Chao Li
- Department of Epidemiology and Health Statistics, School of Public Health, Xi'an Jiaotong University Health Science Centre, Xi'an 710061, China.
| | - Tao Chen
- Centre for Health Economics, University of York, Heslington, York YO10 5DD, United Kingdom; Department of Clinical Sciences, Liverpool School of Tropical Medicine, Pembroke Pl, Liverpool L3 5QA, United Kingdom.
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Esdaile H, Hill N, Mayet J, Oliver N. Glycaemic control in people with diabetes following acute myocardial infarction. Diabetes Res Clin Pract 2023; 199:110644. [PMID: 36997029 DOI: 10.1016/j.diabres.2023.110644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 02/09/2023] [Accepted: 03/22/2023] [Indexed: 03/31/2023]
Abstract
Diabetes is a highly prevalent disease associated with considerable cardiovascular end organ damage and mortality. Despite significant changes to the management of acute myocardial infarction over the last two decades, people with diabetes remain at risk of complications and mortality following a myocardial infarct for a multitude of reasons, including increased coronary atherosclerosis, associated coronary microvascular dysfunction, and diabetic cardiomyopathy. Dysglycaemia causes significant endothelial dysfunction and upregulation of inflammation within the vasculature and epigenetic changes mean that these deleterious effects may persist despite subsequent efforts to tighten glycaemic control. Whilst clinical guidelines advocate for the avoidance of both hyper- and hypoglcyaemia in the peri-infarct period, the evidence base is lacking, and currently there is no consensus on the benefits of glycaemic control beyond this period. Glycaemic variability contributes to the glycaemic milieu and may have prognostic importance following myocardial infarct. The use of continuous glucose monitoring means that glucose trends and parameters can now be captured and interrogated, and its use, along with newer medicines, may provide novel opportunities for intervention after myocardial infarction in people with diabetes.
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Affiliation(s)
- Harriet Esdaile
- Faculty of Medicine, Department of Metabolism, Digestion and Reproduction, Imperial Centre for Translational and Experimental Medicine, Imperial College London, Du Cane Road, London, W12 0NN, London, United Kingdom.
| | - Neil Hill
- Faculty of Medicine, Department of Metabolism, Digestion and Reproduction Imperial College London, London, United Kingdom
| | - Jamil Mayet
- Faculty of Medicine, National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Nick Oliver
- Faculty of Medicine, Department of Metabolism Digestion and Reproduction, Imperial College London, London, United Kingdom
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Affiliation(s)
- Roy W Beck
- Jaeb Center for Health Research, 15310 Amberly Drive, Suite 350, Tampa, Florida, United States, 33647;
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Wan J, Lu J, Li C, Ma X, Zhou J. Research progress in the application of time in range: more than a percentage. Chin Med J (Engl) 2023; 136:522-527. [PMID: 36939244 PMCID: PMC10106225 DOI: 10.1097/cm9.0000000000002582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Indexed: 03/21/2023] Open
Abstract
ABSTRACT Glucose monitoring is an important part of medical care in diabetes mellitus, which not only helps assess glycemic control and treatment safety, but also assists with treatment adjustment. With the development of continuous glucose monitoring (CGM), the use of CGM has increased rapidly. With the wealth of glucose data produced by CGM, new metrics are greatly needed to optimally evaluate glucose status and guide the treatment. One of the parameters that CGM provides, time in range (TIR), has been recognized as a key metric by the international consensus. Before the adoption of TIR in clinical practice, several issues including the minimum length of CGM use, the setting of the target range, and individualized TIR goals are summarized. Additionally, we discussed the mounting evidence supporting the association between TIR and diabetes-related outcomes. As a novel glucose metric, it is of interest to compare TIR with other conventional glucose markers such as glycated hemoglobin A1c. It is anticipated that the use of TIR may provide further information on the quality of glucose control and lead to improved diabetes management.
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Affiliation(s)
- Jintao Wan
- Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine; Shanghai Clinical Center for Diabetes; Shanghai Key Clinical Center for Metabolic Disease; Shanghai Diabetes Institute; Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
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Abstract
Wearable devices, such as smartwatches and activity trackers, are commonly used by patients in their everyday lives to manage their health and well-being. These devices collect and analyze long-term continuous data on measures of behavioral or physiologic function, which may provide clinicians with a more comprehensive view of a patients' health compared with the traditional sporadic measures captured by office visits and hospitalizations. Wearable devices have a wide range of potential clinical applications ranging from arrhythmia screening of high-risk individuals to remote management of chronic conditions such as heart failure or peripheral artery disease. As the use of wearable devices continues to grow, we must adopt a multifaceted approach with collaboration among all key stakeholders to effectively and safely integrate these technologies into routine clinical practice. In this Review, we summarize the features of wearable devices and associated machine learning techniques. We describe key research studies that illustrate the role of wearable devices in the screening and management of cardiovascular conditions and identify directions for future research. Last, we highlight the challenges that are currently hindering the widespread use of wearable devices in cardiovascular medicine and provide short- and long-term solutions to promote increased use of wearable devices in clinical care.
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Affiliation(s)
- Andrew Hughes
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN
| | | | - Hiral Master
- Vanderbilt Institute of Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, TN
| | - Jessilyn Dunn
- Department of Biomedical Engineering, Duke University, Durham, NC
- Department of Biostatistics & Bioinformatics, Duke University, Durham, NC
| | - Evan Brittain
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN
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Hu G, Ding J, Ryan DH. Trends in obesity prevalence and cardiometabolic risk factor control in US adults with diabetes, 1999-2020. Obesity (Silver Spring) 2023; 31:841-851. [PMID: 36697975 PMCID: PMC9974736 DOI: 10.1002/oby.23652] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 10/27/2022] [Indexed: 01/27/2023]
Abstract
OBJECTIVE Trends in obesity prevalence and trends in control of cardiometabolic risk factors among National Health and Nutrition Examination Survey participants with diabetes from 1999 through 2020 were analyzed. METHODS Adults who were 20 years or older and who reported having received a diagnosis of diabetes from a physician were included. RESULTS The prevalence of overall obesity, obesity class II, and obesity class III increased from 46.9%, 14.1%, and 10.3% in 1999 to 2002 to 58.1%, 16.6%, and 14.8% in 2015 to 2020, respectively. The prevalence of participants who achieved glycemic control (HbA1c <7%) increased from 42.5% in 1999 to 2002 to 51.8% in 2007 to 2010, then decreased to 48.0% in 2015 to 2020. The prevalence of participants who achieved blood pressure control (<140/90 mmHg) or achieved non-high-density lipoprotein cholesterol control (<130 mg/dL) increased throughout the study periods. The prevalence of participants who met all three risk factor goals increased from 8.3% in 1999 to 2002 to 21.2% in 2011 to 2014 and then decreased to 18.5 in 2015 to 2020. Participants with obesity showed worsening glycemic control and lipid control than participants with normal weight. CONCLUSIONS There were increasing trends in prevalence of obesity, blood pressure control, and lipid control from 1999 to 2002 to 2015 to 2020. Participants with obesity showed worsening glycemic control and lipid control than normal-weight participants.
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Affiliation(s)
- Gang Hu
- Pennington Biomedical Research Center, Baton Rouge, LA
| | - Jonathan Ding
- Pennington Biomedical Research Center, Baton Rouge, LA
- California Institute of Technology, Pasadena, CA
| | - Donna H. Ryan
- Pennington Biomedical Research Center, Baton Rouge, LA
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Liu L, Ke W, Xu L, Li H, Liu J, Wan X, Liu J, Deng W, Cao X, Xiao H, Li Y. Evaluating the role of time in range as a glycemic target during short-term intensive insulin therapy in patients with newly diagnosed type 2 diabetes. J Diabetes 2023; 15:133-144. [PMID: 36650669 PMCID: PMC9934958 DOI: 10.1111/1753-0407.13355] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 12/02/2022] [Accepted: 12/29/2022] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND Tight glycemic control during short-term intensive insulin therapy (SIIT) is critical for inducing diabetes remission in patients with newly diagnosed type 2 diabetes (T2D). This work aimed to investigate the role of time in range (TIR) during SIIT as a novel glycemic target by predicting clinical outcomes. METHODS SIIT was given to 116 patients with newly diagnosed T2D, with daily eight-point capillary glucose monitored. Glycemic targets (fasting/premeal glucose, 3.9-6.0 mmol/L; 2 h postprandial blood glucose, 3.9-7.8 mmol/L) were achieved and maintained for 2 weeks. TIRPIR was calculated as the percentage of glucose points within these glycemic targets during the maintenance period and was compared to TIR3.9-7.8mmol/L and TIR3.9-10.0mmol/L . Acute insulin response (AIR), HOMA-IR, HOMA-B, and disposition index (DI) were measured. Patients were followed up for 1 year to observe clinical outcomes. RESULTS TIRPIR , TIR3.9-7.8mmol/L , and TIR3.9-10.0mmol/L were 67.2 ± 11.2%, 80.8 ± 9.2%, and 90.1 ± 6.2%, respectively. After SIIT, β-cell function and insulin sensitivity improved remarkably, and the 1-year remission rate was 55.2%. △AIR and △DI were positively correlated with all the TIR values, whereas only TIRPIR was correlated with △HOMA-IR (r = -0.22, p = 0.03). Higher TIRPIR but not TIR3.9-7.8mmol/L or TIR3.9-10.0mmol/L was robustly associated with diabetes remission; patients in the lower TIRPIR tertile had an elevated risk of hyperglycemia relapse (hazard ratio 3.4, 95% confidence interval 1.6-7.2, p = .001). Only those with TIRPIR ≥ 65% had a one-year remission rate of over 60%. CONCLUSIONS These findings advocate TIRPIR ≥ 65% as a novel glycemic target during SIIT for clinical decision-making.
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Affiliation(s)
- Liehua Liu
- Department of Endocrinologythe First Affiliated Hospital of Sun Yat‐Sen UniversityGuangzhouChina
| | - Weijian Ke
- Department of Endocrinologythe First Affiliated Hospital of Sun Yat‐Sen UniversityGuangzhouChina
| | - Lijuan Xu
- Department of Endocrinologythe First Affiliated Hospital of Sun Yat‐Sen UniversityGuangzhouChina
| | - Hai Li
- Department of Endocrinologythe First Affiliated Hospital of Sun Yat‐Sen UniversityGuangzhouChina
| | - Juan Liu
- Department of Endocrinologythe First Affiliated Hospital of Sun Yat‐Sen UniversityGuangzhouChina
| | - Xuesi Wan
- Department of Endocrinologythe First Affiliated Hospital of Sun Yat‐Sen UniversityGuangzhouChina
| | - Jianbin Liu
- Endocrinology DepartmentEastern HealthMelbourneVictoriaAustralia
| | - Wanping Deng
- Department of Endocrinologythe First Affiliated Hospital of Sun Yat‐Sen UniversityGuangzhouChina
| | - Xiaopei Cao
- Department of Endocrinologythe First Affiliated Hospital of Sun Yat‐Sen UniversityGuangzhouChina
| | - Haipeng Xiao
- Department of Endocrinologythe First Affiliated Hospital of Sun Yat‐Sen UniversityGuangzhouChina
| | - Yanbing Li
- Department of Endocrinologythe First Affiliated Hospital of Sun Yat‐Sen UniversityGuangzhouChina
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Eysenbach G, Sharma A, Green CR, Norman GJ, Thomas R, Leone K. Glycemic Outcomes and Feature Set Engagement Among Real-Time Continuous Glucose Monitoring Users With Type 1 or Non-Insulin-Treated Type 2 Diabetes: Retrospective Analysis of Real-World Data. JMIR Diabetes 2023; 8:e43991. [PMID: 36602920 PMCID: PMC9947825 DOI: 10.2196/43991] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 12/15/2022] [Accepted: 01/05/2023] [Indexed: 01/06/2023] Open
Abstract
BACKGROUND The benefits of real-time continuous glucose monitoring (RT-CGM) are well established for patients with type 1 diabetes (T1D) and patients with insulin-treated type 2 diabetes (T2D). However, the usage and effectiveness of RT-CGM in the context of non-insulin-treated T2D has not been well studied. OBJECTIVE We aimed to assess glycemic metrics and rates of RT-CGM feature utilization in users with T1D and non-insulin-treated T2D. METHODS We retrospectively analyzed data from 33,685 US-based users of an RT-CGM system (Dexcom G6; Dexcom, Inc) who self-identified as having either T1D (n=26,706) or T2D and not using insulin (n=6979). Data included glucose concentrations, alarm settings, feature usage, and event logs. RESULTS The T1D cohort had lower proportions of glucose values in the 70 mg/dl to 180 mg/dl range than the T2D cohort (52.1% vs 70.8%, respectively), with more values indicating hypoglycemia or hyperglycemia and higher glycemic variability. Discretionary alarms were enabled by a large majority in both cohorts. The data sharing feature was used by 38.7% (10,327/26,706) of those with T1D and 10.4% (727/6979) of those with T2D, and the mean number of followers was higher in the T1D cohort. Large proportions of patients with T1D or T2D enabled and customized their glucose alerts. Retrospective analysis features were used by the majority in both cohorts (T1D: 15,783/26,706, 59.1%; T2D: 3751/6979, 53.8%). CONCLUSIONS Similar to patients with T1D, patients with non-insulin-treated T2D used RT-CGM system features, suggesting beneficial, routine engagement with data by patients and others involved in their care. Motivated patients with diabetes could benefit from RT-CGM coverage.
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Affiliation(s)
| | | | - Courtney R Green
- Department of Medical Affairs, Dexcom, Inc, San Diego, CA, United States
| | - Gregory J Norman
- Department of Global Access, Dexcom, Inc, San Diego, CA, United States
| | - Roy Thomas
- Department of Medical Affairs, Dexcom, Inc, San Diego, CA, United States
| | - Keri Leone
- Department of Medical Affairs, Dexcom, Inc, San Diego, CA, United States
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Battelino T, Alexander CM, Amiel SA, Arreaza-Rubin G, Beck RW, Bergenstal RM, Buckingham BA, Carroll J, Ceriello A, Chow E, Choudhary P, Close K, Danne T, Dutta S, Gabbay R, Garg S, Heverly J, Hirsch IB, Kader T, Kenney J, Kovatchev B, Laffel L, Maahs D, Mathieu C, Mauricio D, Nimri R, Nishimura R, Scharf M, Del Prato S, Renard E, Rosenstock J, Saboo B, Ueki K, Umpierrez GE, Weinzimer SA, Phillip M. Continuous glucose monitoring and metrics for clinical trials: an international consensus statement. Lancet Diabetes Endocrinol 2023; 11:42-57. [PMID: 36493795 DOI: 10.1016/s2213-8587(22)00319-9] [Citation(s) in RCA: 175] [Impact Index Per Article: 175.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 10/27/2022] [Accepted: 10/28/2022] [Indexed: 12/12/2022]
Abstract
Randomised controlled trials and other prospective clinical studies for novel medical interventions in people with diabetes have traditionally reported HbA1c as the measure of average blood glucose levels for the 3 months preceding the HbA1c test date. The use of this measure highlights the long-established correlation between HbA1c and relative risk of diabetes complications; the change in the measure, before and after the therapeutic intervention, is used by regulators for the approval of medications for diabetes. However, with the increasing use of continuous glucose monitoring (CGM) in clinical practice, prospective clinical studies are also increasingly using CGM devices to collect data and evaluate glucose profiles among study participants, complementing HbA1c findings, and further assess the effects of therapeutic interventions on HbA1c. Data is collected by CGM devices at 1-5 min intervals, which obtains data on glycaemic excursions and periods of asymptomatic hypoglycaemia or hyperglycaemia (ie, details of glycaemic control that are not provided by HbA1c concentrations alone that are measured continuously and can be analysed in daily, weekly, or monthly timeframes). These CGM-derived metrics are the subject of standardised, internationally agreed reporting formats and should, therefore, be considered for use in all clinical studies in diabetes. The purpose of this consensus statement is to recommend the ways CGM data might be used in prospective clinical studies, either as a specified study endpoint or as supportive complementary glucose metrics, to provide clinical information that can be considered by investigators, regulators, companies, clinicians, and individuals with diabetes who are stakeholders in trial outcomes. In this consensus statement, we provide recommendations on how to optimise CGM-derived glucose data collection in clinical studies, including the specific glucose metrics and specific glucose metrics that should be evaluated. These recommendations have been endorsed by the American Association of Clinical Endocrinologists, the American Diabetes Association, the Association of Diabetes Care and Education Specialists, DiabetesIndia, the European Association for the Study of Diabetes, the International Society for Pediatric and Adolescent Diabetes, the Japanese Diabetes Society, and the Juvenile Diabetes Research Foundation. A standardised approach to CGM data collection and reporting in clinical trials will encourage the use of these metrics and enhance the interpretability of CGM data, which could provide useful information other than HbA1c for informing therapeutic and treatment decisions, particularly related to hypoglycaemia, postprandial hyperglycaemia, and glucose variability.
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Affiliation(s)
- Tadej Battelino
- Department of Pediatric Endocrinology, Diabetes and Metabolism, University Children's Hospital, University Medical Centre Ljubljana, and Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
| | | | | | - Guillermo Arreaza-Rubin
- Division of Diabetes, Endocrinology and Metabolic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA
| | - Roy W Beck
- Jaeb Center for Health Research, Tampa, FL, USA
| | | | - Bruce A Buckingham
- Division of Endocrinology and Diabetes, Department of Pediatrics, Stanford Medical Center, Stanford, CA, USA
| | | | | | - Elaine Chow
- Phase 1 Clinical Trial Centre, Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Pratik Choudhary
- Leicester Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Kelly Close
- diaTribe Foundation, San Francisco, CA, USA; Close Concerns, San Francisco, CA, USA
| | - Thomas Danne
- Diabetes Centre for Children and Adolescents, Auf der Bult, Hanover, Germany
| | | | - Robert Gabbay
- American Diabetes Association, Arlington, VA, USA; Harvard Medical School, Harvard University, Boston, MA, USA
| | - Satish Garg
- Barbara Davis Centre for Diabetes, University of Colorado Denver, Aurora, CO, USA
| | | | - Irl B Hirsch
- Division of Metabolism, Endocrinology and Nutrition, University of Washington School of Medicine, University of Washington, Seattle, WA, USA
| | - Tina Kader
- Jewish General Hospital, Montreal, QC, Canada
| | | | - Boris Kovatchev
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA
| | - Lori Laffel
- Pediatric, Adolescent and Young Adult Section, Joslin Diabetes Center, Harvard Medical School, Harvard University, Boston, MA, USA
| | - David Maahs
- Department of Pediatrics, Stanford Diabetes Research Center, Stanford, CA, USA
| | - Chantal Mathieu
- Clinical and Experimental Endocrinology, KU Leuven, Leuven, Belgium
| | - Dídac Mauricio
- Department of Endocrinology and Nutrition, CIBERDEM (Instituto de Salud Carlos III), Hospital de la Santa Creu i Sant Pau, Autonomous University of Barcelona, Barcelona, Spain
| | - Revital Nimri
- National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
| | - Rimei Nishimura
- The Jikei University School of Medicine, Jikei University, Tokyo, Japan
| | - Mauro Scharf
- Centro de Diabetes Curitiba and Division of Pediatric Endocrinology, Hospital Nossa Senhora das Graças, Curitiba, Brazil
| | - Stefano Del Prato
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Eric Renard
- Department of Endocrinology, Diabetes and Nutrition, Montpellier University Hospital, Montpellier, France; Institute of Functional Genomics, University of Montpellier, Montpellier, France; INSERM Clinical Investigation Centre, Montpellier, France
| | - Julio Rosenstock
- Velocity Clinical Research, Medical City, Dallas, TX; University of Texas Southwestern Medical Center, University of Texas, Dallas, TX, USA
| | - Banshi Saboo
- Dia Care, Diabetes Care and Hormone Clinic, Ahmedabad, India
| | - Kohjiro Ueki
- Diabetes Research Center, National Center for Global Health and Medicine, Tokyo, Japan
| | | | - Stuart A Weinzimer
- Department of Pediatrics, Yale University School of Medicine, Yale University, New Haven, CT, USA
| | - Moshe Phillip
- National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel; Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
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Wei Y, Liu C, Liu Y, Zhang Z, Feng Z, Yang X, Liu J, Lei H, Zhou H, Shen Q, Lu B, Gu P, Shao J. The association between time in the glucose target range and abnormal ankle-brachial index: a cross-sectional analysis. Cardiovasc Diabetol 2022; 21:281. [PMID: 36514151 PMCID: PMC9746002 DOI: 10.1186/s12933-022-01718-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 12/04/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Time in range (TIR), a novel proxy measure of glucose control, is found closely related to diabetic microangiopathy and some other chronic complications, but the correlation between TIR and lower limb angiopathy has not been studied yet. Our purpose is to explore the relationship between TIR and abnormal ankle-brachial index(ABI) in type 2 diabetes. METHODS We retrospectively collected patients' information from the database and performed cross-sectional analysis. A total of 405 type 2 diabetes patients were enrolled in this study. ABI was measured and patients were stratified into low, normal, and high groups according to ≤ 0.9, > 0.9 and < 1.3, ≥ 1.3 ABI values. All patients underwent continuous glucose monitoring(CGM), and TIR was defined as the percentage of time in which glucose was in the range of 3.9-10 mmol/L during a 24-h period. Correlations between TIR and abnormal ABI were analyzed using Spearman analysis. And logistic regression was used to explore whether TIR is an independent risk factor for abnormal ABI. RESULTS The overall prevalence of abnormal ABI was 20.2% (low 4.9% and high 15.3%). TIR was lower in patients with abnormal ABI values (P = 0.009). The prevalence of abnormal ABI decreased with increasing quartiles of TIR (P = 0.026). Abnormal ABI was negatively correlated with TIR and positively correlated with hypertension, age, diabetes duration, UREA, Scr, ACR, TAR, MBG, and M values (P < 0.05). The logistic regression revealed a significant association between TIR and abnormal ABI, while HbA1C and blood glucose variability measures had no explicit correlation with abnormal ABI. Additionally, there was a significant difference in LDL between the low and high ABI groups (P = 0.009), and in Scr between normal and low groups (P = 0.007). And there were significant differences in TIR (P = 0.003), age (P = 0.023), UREA (P = 0.006), ACR (P = 0.004), TAR (P = 0.015), and MBG (P = 0.014) between normal and high ABI groups, and in diabetes duration between both normal and low (P = 0.023) and normal and high (P = 0.006) groups. CONCLUSIONS In type 2 diabetes patients, abnormal ABI is associated with lower TIR, and the correlation is stronger than that with HbA1C. Therefore, the role of TIR should be emphasized in the evaluation of lower limb vascular diseases.
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Affiliation(s)
- Yinghua Wei
- grid.41156.370000 0001 2314 964XDepartment of Endocrinology, Affiliated Jinling Hospital, Medical School of Nanjing University, 305 East Zhongshan Road, Nanjing, 210002 Jiangsu China
| | - Chunyan Liu
- grid.459328.10000 0004 1758 9149Department of Endocrinology, Affiliated Hospital of Jiangnan University, Wuxi, Jiangsu China
| | - Yanyu Liu
- grid.41156.370000 0001 2314 964XDepartment of Endocrinology, Affiliated Jinling Hospital, Medical School of Nanjing University, 305 East Zhongshan Road, Nanjing, 210002 Jiangsu China
| | - Zhen Zhang
- grid.284723.80000 0000 8877 7471Department of Endocrinology, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, China
| | - Zhouqin Feng
- grid.41156.370000 0001 2314 964XDepartment of Endocrinology, Affiliated Jinling Hospital, Medical School of Nanjing University, 305 East Zhongshan Road, Nanjing, 210002 Jiangsu China
| | - Xinyi Yang
- grid.41156.370000 0001 2314 964XDepartment of Endocrinology, Affiliated Jinling Hospital, Medical School of Nanjing University, 305 East Zhongshan Road, Nanjing, 210002 Jiangsu China
| | - Juan Liu
- grid.89957.3a0000 0000 9255 8984Department of Endocrinology, The affiliated Jinling Hospital of Nanjing Medical University, Nanjing, Jiangsu China
| | - Haiyan Lei
- grid.284723.80000 0000 8877 7471Department of Endocrinology, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, China
| | - Hui Zhou
- grid.284723.80000 0000 8877 7471Department of Endocrinology, Jinling Hospital, The First School of Clinical Medicine, Southern Medical University, Nanjing, China
| | - Qiuyue Shen
- grid.41156.370000 0001 2314 964XDepartment of Endocrinology, Affiliated Jinling Hospital, Medical School of Nanjing University, 305 East Zhongshan Road, Nanjing, 210002 Jiangsu China
| | - Bin Lu
- grid.41156.370000 0001 2314 964XDepartment of Endocrinology, Affiliated Jinling Hospital, Medical School of Nanjing University, 305 East Zhongshan Road, Nanjing, 210002 Jiangsu China
| | - Ping Gu
- grid.41156.370000 0001 2314 964XDepartment of Endocrinology, Affiliated Jinling Hospital, Medical School of Nanjing University, 305 East Zhongshan Road, Nanjing, 210002 Jiangsu China
| | - Jiaqing Shao
- grid.41156.370000 0001 2314 964XDepartment of Endocrinology, Affiliated Jinling Hospital, Medical School of Nanjing University, 305 East Zhongshan Road, Nanjing, 210002 Jiangsu China
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Helleputte S, Calders P, Rodenbach A, Marlier J, Verroken C, De Backer T, Lapauw B. Time-varying parameters of glycemic control and glycation in relation to arterial stiffness in patients with type 1 diabetes. Cardiovasc Diabetol 2022; 21:277. [PMID: 36494687 PMCID: PMC9737749 DOI: 10.1186/s12933-022-01717-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 12/03/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND A substantial proportion of type 1 diabetes (T1D) patients free from known cardiovascular disease (CVD) show premature arterial stiffening, with age, blood pressure, and HbA1c-as gold standard of glycemic control-as main predictors. However, the relationship of arterial stiffness with other time-varying parameters of glycemic control and glycation has been far less explored. This study investigated the relationship of arterial stiffness with several short- and long-term parameters of glycemic control and glycation in patients with T1D, such as advanced glycation end-products (AGEs) and continuous glucose monitoring (CGM)-derived parameters. METHODS Cross-sectional study at a tertiary care centre including 54 patients with T1D free from known CVD. Arterial stiffness was assessed with carotid-femoral pulse wave velocity (cf-PWV). Current level and 10-year history of HbA1c were evaluated, and skin AGEs, urinary AGEs, and serum soluble AGE-receptor (sRAGE) concentrations. CGM for 7 days was used to determine time in range, time in hyper- and hypoglycemia, and glycemic variability. RESULTS Cf-PWV was associated with current HbA1c (rs = + 0.28), mean 10-years HbA1c (rs = + 0.36), skin AGEs (rs = + 0.40) and the skin AGEs-to-sRAGE ratio (rs = + 0.40), but not with urinary AGE or serum sRAGE concentrations; and not with any of the CGM-parameters. Multiple linear regression for cf-PWV showed that the model with the best fit included age, T1D duration, 24-h mean arterial pressure and mean 10-years HbA1c (adjusted R2 = 0.645, p < 0.001). CONCLUSIONS Longer-term glycemic exposure as reflected by current and mean 10-years HbA1c is a key predictor of arterial stiffness in patients with T1D, while no relationship was found with any of the short-term CGM parameters. Our findings stress the importance of early and sustained good glycemic control to prevent premature CVD in patients with T1D and suggest that HbA1c should continue to be used in the risk assessment for diabetic complications. The role of skin glycation, as a biomarker for vascular aging, in the risk assessment for CVD is an interesting avenue for further research.
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Affiliation(s)
- Simon Helleputte
- grid.5342.00000 0001 2069 7798Faculty of Medicine and Health Sciences, Ghent University, Ghent University Hospital, Corneel Heymanslaan 10, 9000 Ghent, Belgium ,grid.434261.60000 0000 8597 7208Fonds Wetenschappelijk Onderzoek (FWO) Vlaanderen, Ghent, Belgium
| | - Patrick Calders
- grid.5342.00000 0001 2069 7798Faculty of Medicine and Health Sciences, Ghent University, Ghent University Hospital, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - Arthur Rodenbach
- grid.5342.00000 0001 2069 7798Faculty of Medicine and Health Sciences, Ghent University, Ghent University Hospital, Corneel Heymanslaan 10, 9000 Ghent, Belgium
| | - Joke Marlier
- grid.410566.00000 0004 0626 3303Department of Endocrinology, Ghent University Hospital, Ghent, Belgium
| | - Charlotte Verroken
- grid.410566.00000 0004 0626 3303Department of Endocrinology, Ghent University Hospital, Ghent, Belgium
| | - Tine De Backer
- grid.5342.00000 0001 2069 7798Faculty of Medicine and Health Sciences, Ghent University, Ghent University Hospital, Corneel Heymanslaan 10, 9000 Ghent, Belgium ,grid.410566.00000 0004 0626 3303Department of Cardiology, Ghent University Hospital, Ghent, Belgium
| | - Bruno Lapauw
- grid.5342.00000 0001 2069 7798Faculty of Medicine and Health Sciences, Ghent University, Ghent University Hospital, Corneel Heymanslaan 10, 9000 Ghent, Belgium ,grid.410566.00000 0004 0626 3303Department of Endocrinology, Ghent University Hospital, Ghent, Belgium
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Cai J, Yang Q, Lu J, Shen Y, Wang C, Chen L, Zhang L, Lu W, Zhu W, Xia T, Zhou J. Impact of the complexity of glucose time series on all-cause mortality in patients with type 2 diabetes. J Clin Endocrinol Metab 2022; 108:1093-1100. [PMID: 36458883 PMCID: PMC10099164 DOI: 10.1210/clinem/dgac692] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Revised: 11/09/2022] [Accepted: 11/29/2022] [Indexed: 12/04/2022]
Abstract
CONTEXT Previous studies suggest that the complexity of glucose time series may serve as a novel marker of glucose homeostasis. OBJECTIVE We aimed to investigate the relationship between the complexity of glucose time series and all-cause mortality in patients with type 2 diabetes. METHODS Prospective data of 6000 adult inpatients with type 2 diabetes from a single center was analyzed. The complexity of glucose time series index (CGI) based on continuous glucose monitoring (CGM) was measured at baseline with refined composite multi-scale entropy. Participants were stratified by the tertiles of CGI: < 2.15, 2.15-2.99, and ≥ 3.00. Cox proportional hazards regression models were used to assess the relationship between CGI and all-cause mortality. RESULTS During a median follow-up of 9.4 years, 1217 deaths were identified. A significant interaction between glycated hemoglobin A1c (HbA1c) and CGI in relation to all-cause mortality was noted (P for interaction = 0.016). The multivariable-adjusted hazard ratios for all-cause mortality at different CGI levels [≥ 3.00 (reference group), 2.15-2.99, and < 2.15] were 1.00, 0.76 (95% CI 0.52-1.12), and 1.47 (95% CI 1.03-2.09) in patients with HbA1c < 7.0%, while the association was nonsignificant in those with HbA1c ≥ 7.0%. The restricted cubic spline regression revealed a non-linear (P for non-linearity = 0.041) relationship between CGI and all-cause mortality in subjects with HbA1c < 7.0% only. CONCLUSIONS Lower CGI is associated with an increased risk of all-cause mortality among patients with type 2 diabetes achieving the HbA1c target. CGI may be a new indicator for the identification of residual risk of death in well-controlled type 2 diabetes.
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Affiliation(s)
- Jinghao Cai
- Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China
| | - Qing Yang
- Vital Statistical Department, Institute of Health Information, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Jingyi Lu
- Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China
| | - Yun Shen
- Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China
| | - Chunfang Wang
- Vital Statistical Department, Institute of Health Information, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Lei Chen
- Vital Statistical Department, Institute of Health Information, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Lei Zhang
- Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China
| | - Wei Lu
- Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China
| | - Wei Zhu
- Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China
| | - Tian Xia
- Vital Statistical Department, Institute of Health Information, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Jian Zhou
- Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Clinical Center for Diabetes, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China
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69
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Aroda VR, Eckel RH. Reconsidering the role of glycaemic control in cardiovascular disease risk in type 2 diabetes: A 21st century assessment. Diabetes Obes Metab 2022; 24:2297-2308. [PMID: 35929480 PMCID: PMC9804800 DOI: 10.1111/dom.14830] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 07/28/2022] [Accepted: 08/01/2022] [Indexed: 01/09/2023]
Abstract
It is well known that the multiple factors contributing to the pathogenesis of type 2 diabetes (T2D) confer an increased risk of developing cardiovascular disease (CVD). Although the relationship between hyperglycaemia and increased microvascular risk is well established, the relative contribution of hyperglycaemia to macrovascular events has been strongly debated, particularly owing to the failure of attempts to reduce CVD risk through normalizing glycaemia with traditional therapies in high-risk populations. The debate has been further fuelled by the relatively recent discovery of the cardioprotective properties of glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter-2 inhibitors. Further, as guidelines now recommend individualizing glycaemic targets, highlighting the importance of achieving glycated haemoglobin (HbA1c) goals safely, the previously observed negative influences of intensive therapy on CVD risk might not present if trials were repeated using current-day treatments and individualized HbA1c goals. Emerging longitudinal data illuminate the overall effect of excess glucose, the impacts of magnitude and duration of hyperglycaemia on disease progression and risk of CVD complications, and the importance of glycaemic control at or early after diagnosis of T2D for prevention of complications. Herein, we review the role of glucose as a modifiable cardiovascular (CV) risk factor, the role of microvascular disease in predicting macrovascular risk, and the deleterious impact of therapeutic inertia on CVD risk. We reconcile new and old data to offer a current perspective, highlighting the importance of effective, early treatment in reducing latent CV risk, and the timely use of appropriate therapy individualized to each patient's needs.
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Affiliation(s)
- Vanita R. Aroda
- Division of Endocrinology, Diabetes, and HypertensionBrigham and Women's HospitalBostonMassachusetts
| | - Robert H. Eckel
- Division of Endocrinology, Metabolism, and Diabetes, and the Division of CardiologyUniversity of Colorado School of MedicineAuroraColorado
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70
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Bao Y, Zhu D. Clinical application guidelines for blood glucose monitoring in China (2022 edition). Diabetes Metab Res Rev 2022; 38:e3581. [PMID: 36251516 PMCID: PMC9786627 DOI: 10.1002/dmrr.3581] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 08/01/2022] [Accepted: 10/05/2022] [Indexed: 12/30/2022]
Abstract
Glucose monitoring is an important component of diabetes management. The Chinese Diabetes Society (CDS) has been producing evidence-based guidelines on the optimal use of glucose monitoring since 2011. In recent years, new technologies in glucose monitoring and more clinical evidence, especially those derived from Chinese populations, have emerged. In this context, the CDS organised experts to revise the Clinical application guidelines for blood glucose monitoring in China in 2021. In this guideline, we focus on four methods of glucose monitoring that are commonly used in clinical practice, including capillary glucose monitoring, glycated haemoglobin A1c, glycated albumin, and continuous glucose monitoring. We describe the definitions and technical characteristics of these methods, the factor that may interfere with the measurement, the advantages and caveats in clinical practice, the interpretation of glucose metrics, and the relevant supporting evidence. The recommendations for the use of these methods are also provided. The various methods of glucose monitoring have their strengths and limitations and cannot be replaced by one another. We hope that these guidelines could aid in the optimal application of common methods of glucose monitoring in clinical practice for better diabetes care.
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Affiliation(s)
- Yuqian Bao
- Department of Endocrinology and MetabolismShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Dalong Zhu
- Department of EndocrinologyDrum Tower Hospital Affiliated to Nanjing University Medical SchoolNanjingChina
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71
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Wang Y, Lu J, Shen Y, Ni J, Zhang L, Lu W, Zhu W, Bao Y, Zhou J. Comparison of glucose time in range and area under curve in range in relation to risk of diabetic retinopathy in type 2 diabetes patients. J Diabetes Investig 2022; 13:1543-1550. [PMID: 35435323 PMCID: PMC9434583 DOI: 10.1111/jdi.13811] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 04/07/2022] [Accepted: 04/13/2022] [Indexed: 11/29/2022] Open
Abstract
AIMS/INTRODUCTION We proposed a novel continuous glucose monitoring (CGM)-based metric, area under the curve in range (AucIR), for integrating both the amplitude and duration of dysglycemia, and further compared AucIR with the emerging key CGM-derived metric, time in range (TIR). MATERIALS AND METHODS A total of 2,030 adult patients with type 2 diabetes were enrolled during May 2020 to October 2021. AucIR and TIR were measured with 7-day CGM data. Logistic regression analysis and the C-statistic was carried out to assess the association of AucIR and TIR with diabetic retinopathy (DR). RESULTS Both AucIR (r = -0.89) and TIR (r = -0.95) were strongly correlated with mean glucose levels. Compared with TIR, AucIR showed a tighter relationship with parameters of glycemic variability, including the coefficient of variation (r = -0.56), standard deviation (r = -0.89) and mean amplitude of glycemic excursions (r = -0.70). For each absolute 10% decrease in AucIR, the risk of DR was increased by 7% (95% confidence interval 1.02-1.13) after adjustment for confounders. With respect to TIR, each absolute 10% decrease was associated with an 8% (95% confidence interval 1.03-1.14) increased risk of DR. The model discrimination for DR, as measured by C-statistic, did not differ significantly between the two metrics (P > 0.05). CONCLUSIONS AucIR did not provide added benefit over TIR in the assessment of DR risk among patients with type 2 diabetes. The potential value of AucIR needs to be explored in future studies.
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Affiliation(s)
- Yaxin Wang
- Shanghai Key Laboratory of Diabetes MellitusShanghai Clinical Center for DiabetesShanghai Diabetes InstituteDepartment of Endocrinology and MetabolismShanghai Jiao Tong University School of Medicine Affiliated Sixth People's HospitalShanghaiChina
| | - Jingyi Lu
- Shanghai Key Laboratory of Diabetes MellitusShanghai Clinical Center for DiabetesShanghai Diabetes InstituteDepartment of Endocrinology and MetabolismShanghai Jiao Tong University School of Medicine Affiliated Sixth People's HospitalShanghaiChina
| | - Yun Shen
- Shanghai Key Laboratory of Diabetes MellitusShanghai Clinical Center for DiabetesShanghai Diabetes InstituteDepartment of Endocrinology and MetabolismShanghai Jiao Tong University School of Medicine Affiliated Sixth People's HospitalShanghaiChina
| | - Jiaying Ni
- Shanghai Key Laboratory of Diabetes MellitusShanghai Clinical Center for DiabetesShanghai Diabetes InstituteDepartment of Endocrinology and MetabolismShanghai Jiao Tong University School of Medicine Affiliated Sixth People's HospitalShanghaiChina
| | - Lei Zhang
- Shanghai Key Laboratory of Diabetes MellitusShanghai Clinical Center for DiabetesShanghai Diabetes InstituteDepartment of Endocrinology and MetabolismShanghai Jiao Tong University School of Medicine Affiliated Sixth People's HospitalShanghaiChina
| | - Wei Lu
- Shanghai Key Laboratory of Diabetes MellitusShanghai Clinical Center for DiabetesShanghai Diabetes InstituteDepartment of Endocrinology and MetabolismShanghai Jiao Tong University School of Medicine Affiliated Sixth People's HospitalShanghaiChina
| | - Wei Zhu
- Shanghai Key Laboratory of Diabetes MellitusShanghai Clinical Center for DiabetesShanghai Diabetes InstituteDepartment of Endocrinology and MetabolismShanghai Jiao Tong University School of Medicine Affiliated Sixth People's HospitalShanghaiChina
| | - Yuqian Bao
- Shanghai Key Laboratory of Diabetes MellitusShanghai Clinical Center for DiabetesShanghai Diabetes InstituteDepartment of Endocrinology and MetabolismShanghai Jiao Tong University School of Medicine Affiliated Sixth People's HospitalShanghaiChina
| | - Jian Zhou
- Shanghai Key Laboratory of Diabetes MellitusShanghai Clinical Center for DiabetesShanghai Diabetes InstituteDepartment of Endocrinology and MetabolismShanghai Jiao Tong University School of Medicine Affiliated Sixth People's HospitalShanghaiChina
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72
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Zhao W, Lu J, Zhang L, Lu W, Zhu W, Bao Y, Zhou J. Relationship between time in range and corneal nerve fiber loss in asymptomatic patients with type 2 diabetes. Chin Med J (Engl) 2022; 135:1978-1985. [PMID: 36070458 PMCID: PMC9746728 DOI: 10.1097/cm9.0000000000002140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Corneal confocal microscopy (CCM) is a noninvasive technique to detect early nerve damage of diabetic sensorimotor polyneuropathy (DSPN). Time in range (TIR) is an emerging metric of glycemic control which was reported to be associated with diabetic complications. We sought to explore the relationship between TIR and corneal nerve parameters in asymptomatic patients with type 2 diabetes (T2DM). METHODS In this cross-sectional study, 206 asymptomatic inpatients with T2DM were recruited. After 7 days of continuous glucose monitoring, the TIR was calculated as the percentage of time in the glucose range of 3.9 to 10.0 mmol/L. CCM was performed to determine corneal nerve fiber density, corneal nerve branch density, and corneal nerve fiber length (CNFL). Abnormal CNFL was defined as ≤15.30 mm/mm 2 . RESULTS Abnormal CNFL was found in 30.6% (63/206) of asymptomatic subjects. Linear regression analyses revealed that TIR was positively correlated with CCM parameters both in the crude and adjusted models (all P < 0.05). Each 10% increase in TIR was associated with a 28.2% (95% CI: 0.595-0.866, P = 0.001) decreased risk of abnormal CNFL after adjusting for covariates. With the increase of TIR quartiles, corneal nerve fiber parameters increased significantly (all P for trend <0.01). The receiver operating characteristic curve indicated that the optimal cutoff point of TIR was 77.5% for predicting abnormal CNFL in asymptomatic patients. CONCLUSIONS There is a significant independent correlation between TIR and corneal nerve fiber loss in asymptomatic T2DM patients. TIR may be a useful surrogate marker for early diagnosis of DSPN.
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Affiliation(s)
- Weijing Zhao
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital; Shanghai Clinical Center for Diabetes; Shanghai Key Clinical Center for Metabolic Disease; Shanghai Diabetes Institute; Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
| | - Jingyi Lu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital; Shanghai Clinical Center for Diabetes; Shanghai Key Clinical Center for Metabolic Disease; Shanghai Diabetes Institute; Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
- Shanghai Clinical Center for Metabolic Diseases, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Diabetes Institute, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Lei Zhang
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital; Shanghai Clinical Center for Diabetes; Shanghai Key Clinical Center for Metabolic Disease; Shanghai Diabetes Institute; Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
| | - Wei Lu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital; Shanghai Clinical Center for Diabetes; Shanghai Key Clinical Center for Metabolic Disease; Shanghai Diabetes Institute; Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
| | - Wei Zhu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital; Shanghai Clinical Center for Diabetes; Shanghai Key Clinical Center for Metabolic Disease; Shanghai Diabetes Institute; Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
| | - Yuqian Bao
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital; Shanghai Clinical Center for Diabetes; Shanghai Key Clinical Center for Metabolic Disease; Shanghai Diabetes Institute; Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
| | - Jian Zhou
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital; Shanghai Clinical Center for Diabetes; Shanghai Key Clinical Center for Metabolic Disease; Shanghai Diabetes Institute; Shanghai Key Laboratory of Diabetes Mellitus, Shanghai 200233, China
- Department of Endocrinology and Metabolism, Jinshan Branch of Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 201500, China
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73
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Hu L, Xia X, Zong Y, Gu Y, Wei L, Yin J. Calorie Restriction Enhanced Glycogen Metabolism to Compensate for Lipid Insufficiency. Mol Nutr Food Res 2022; 66:e2200182. [PMID: 35972028 DOI: 10.1002/mnfr.202200182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 08/07/2022] [Indexed: 11/11/2022]
Abstract
SCOPE This study aimed to investigate the metabolic phenotype and mechanism of 40% calorie restriction (CR) in mice. METHODS AND RESULTS CR mice exhibited super-stable blood glucose, as evidenced by increased fasting blood glucose (FBG), decreased postprandial blood glucose, and reduced glucose fluctuations. Additionally, both fasting plasma insulin and the homeostasis model assessment of insulin resistance increased significantly in CR mice. Compared with control, the phosphorylation of insulin receptor substrates-1 and serine/threonine kinase decreased in liver and fat but increased in muscle of CR mice after insulin administration, indicating hepatic and adipose insulin resistance, and muscle insulin sensitization. CR reduced visceral fat much more than subcutaneous fat. The elevated FBG was negatively correlated with low-level fasting β-hydroxybutyrate, which may result from insufficient free fatty acids and diminished ketogenic ability in CR mice. Furthermore, liver glycogen increased dramatically in CR mice. Analysis of glycogen metabolism related proteins indicated active glycogen synthesis and decomposition. Additionally, CR elevated plasma corticosterone and hypothalamic orexigenic gene expression. CONCLUSION CR induced lipid insufficiency and stress, resulting in global physiological insulin resistance except muscle and enhanced glycogen metabolism, culminating in the stability of blood glucose manifested in increased FBG, which compensated for insufficient blood ketones. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Lili Hu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai Clinical Center for Metabolic Diseases, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Diabetes Institute, Shanghai, 200233, China
| | - Xinyi Xia
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai Clinical Center for Metabolic Diseases, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Diabetes Institute, Shanghai, 200233, China
| | - Yue Zong
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai Clinical Center for Metabolic Diseases, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Diabetes Institute, Shanghai, 200233, China.,Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin-Buch, Germany
| | - Yunjie Gu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai Clinical Center for Metabolic Diseases, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Diabetes Institute, Shanghai, 200233, China
| | - Li Wei
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai Clinical Center for Metabolic Diseases, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Diabetes Institute, Shanghai, 200233, China
| | - Jun Yin
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University School of Medicine Affiliated Sixth People's Hospital, Shanghai Clinical Center for Metabolic Diseases, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Diabetes Institute, Shanghai, 200233, China.,Department of Endocrinology and Metabolism, Shanghai Eighth People's Hospital, Shanghai, 200233, China
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74
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Szmuilowicz ED, Aleppo G. Stepwise approach to continuous glucose monitoring interpretation for internists and family physicians. Postgrad Med 2022; 134:743-751. [PMID: 35930313 DOI: 10.1080/00325481.2022.2110507] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/16/2022]
Abstract
Continuous glucose monitoring (CGM) use has expanded rapidly in recent years among people with both type 1 and type 2 diabetes. In concert with the globally increasing prevalence of type 2 diabetes, the majority of whom receive diabetes care from internists or family physicians rather than specialists, it is becoming increasingly incumbent upon physicians within internal medicine and family practice to interpret and utilize CGM data in real-world clinical practice. It is therefore of paramount importance that internists and family physicians have access to the tools which will enable them to (1) interpret CGM data, and (2) utilize CGM data to guide therapeutic modifications for their patients with type 2 diabetes. Given the limited amount of time available to internists and family physicians to address multiple complex topics in a typical office visit, a pragmatic, simple, and systematic approach to CGM interpretation is crucial. This article aims to provide internists and family physicians with a simplified and systematic approach to CGM interpretation that can be easily and efficiently implemented in a brief office visit.
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Affiliation(s)
- Emily D Szmuilowicz
- Division of Endocrinology, Metabolism and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine
| | - Grazia Aleppo
- Division of Endocrinology, Metabolism and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine
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75
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Schroeder PH, Brenner LN, Kaur V, Cromer SJ, Armstrong K, LaRocque RC, Ryan ET, Meigs JB, Florez JC, Charles RC, Mercader JM, Leong A. Proteomic analysis of cardiometabolic biomarkers and predictive modeling of severe outcomes in patients hospitalized with COVID-19. Cardiovasc Diabetol 2022; 21:136. [PMID: 35864532 PMCID: PMC9301894 DOI: 10.1186/s12933-022-01569-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Accepted: 07/08/2022] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND The high heterogeneity in the symptoms and severity of COVID-19 makes it challenging to identify high-risk patients early in the disease. Cardiometabolic comorbidities have shown strong associations with COVID-19 severity in epidemiologic studies. Cardiometabolic protein biomarkers, therefore, may provide predictive insight regarding which patients are most susceptible to severe illness from COVID-19. METHODS In plasma samples collected from 343 patients hospitalized with COVID-19 during the first wave of the pandemic, we measured 92 circulating protein biomarkers previously implicated in cardiometabolic disease. We performed proteomic analysis and developed predictive models for severe outcomes. We then used these models to predict the outcomes of out-of-sample patients hospitalized with COVID-19 later in the surge (N = 194). RESULTS We identified a set of seven protein biomarkers predictive of admission to the intensive care unit and/or death (ICU/death) within 28 days of presentation to care. Two of the biomarkers, ADAMTS13 and VEGFD, were associated with a lower risk of ICU/death. The remaining biomarkers, ACE2, IL-1RA, IL6, KIM1, and CTSL1, were associated with higher risk. When used to predict the outcomes of the future, out-of-sample patients, the predictive models built with these protein biomarkers outperformed all models built from standard clinical data, including known COVID-19 risk factors. CONCLUSIONS These findings suggest that proteomic profiling can inform the early clinical impression of a patient's likelihood of developing severe COVID-19 outcomes and, ultimately, accelerate the recognition and treatment of high-risk patients.
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Affiliation(s)
- Philip H Schroeder
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Laura N Brenner
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Division of Pulmonary and Critical Care Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Varinderpal Kaur
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Sara J Cromer
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Katrina Armstrong
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Regina C LaRocque
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA.,Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Edward T Ryan
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA.,Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - James B Meigs
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA.,Division of General Internal Medicine, Department of Medicine, Massachusetts General Hospital, 100 Cambridge St 16th Floor, Boston, MA, 02114, USA
| | - Jose C Florez
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Richelle C Charles
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA.,Division of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Josep M Mercader
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.,Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.,Harvard Medical School, Boston, MA, USA
| | - Aaron Leong
- Diabetes Unit, Endocrine Division, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA. .,Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA. .,Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA. .,Department of Medicine, Massachusetts General Hospital, Boston, MA, USA. .,Harvard Medical School, Boston, MA, USA. .,Division of General Internal Medicine, Department of Medicine, Massachusetts General Hospital, 100 Cambridge St 16th Floor, Boston, MA, 02114, USA.
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76
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Luo Y, Wang J, Sun L, Gu W, Zong G, Song B, Shen C, Zhou P, Chen Y, Wu Y, Lin H, Zheng H, Ni M, Yang X, Chen Y, Xu X, Zhang J, Shi J, Zhang R, Hu J, Hou H, Lu L, Xu X, Liang L, Liu R, Liu X, Li H, Hong J, Wang W, Lin X, Ning G. Isocaloric-restricted Mediterranean Diet and Chinese Diets High or Low in Plants in Adults With Prediabetes. J Clin Endocrinol Metab 2022; 107:2216-2227. [PMID: 35579171 PMCID: PMC9282247 DOI: 10.1210/clinem/dgac303] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/28/2022] [Indexed: 12/02/2022]
Abstract
CONTEXT Calorie restriction plus dietary advice is suggested as a preventive strategy for individuals with obesity and prediabetes; however, optimal diet is still debatable. We aimed to compare the effects of Mediterranean diet (MD) and Chinese diets high or low in plants on body weight and glucose homeostasis among high-risk Chinese. SUBJECTS AND METHODS In this parallel-arm randomized controlled trial, 253 Chinese adults aged 25 to 60 years with a body mass index ≥ 24.0 kg/m2 and fasting blood glucose ≥ 5.6 mmol/L were randomly assigned to 3 isocaloric-restricted diets: MD (n = 84), a traditional Jiangnan diet high in plants (TJD, n = 85), or a control diet low in plants (CD, n = 84). During the 6-month trial, a 5-weekday full-feeding regimen was followed, along with mobile app-based monitoring. Abdominal fat measurement (magnetic resonance imaging), oral glucose tolerance test (OGTT), and continuous glucose monitoring (CGM) were conducted at baseline and 3 and 6 months. RESULTS With a 25% calorie restriction for 6 months, weight deduction was 5.72 kg (95% confidence interval, 5.03-6.40) for MD, 5.05 kg (4.38-5.73) for TJD, and 5.38 kg (4.70-6.06) for CD (Ptime < 0.0001). No between-group differences were found for fasting glucose, insulin, and the Matsuda index from OGTT. Notably, CD had significantly longer time below range (glucose < 3.9 mmol/L) than MD (0.81% [0.21-1.40], P = 0.024) and marginally longer time than TJD (0.56% [-0.03 to 1.15], P = 0.065), as measured by CGM. CONCLUSIONS With the 6-month isocaloric-restricted feeding, TJD and MD achieved comparable weight deduction and improved glucose homeostasis, whereas CD showed a higher risk for hypoglycemia.
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Affiliation(s)
| | - Jiqiu Wang
- Jiqiu Wang, MD, PhD, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Department of Endocrine and Metabolic Diseases, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, 197 Rui-Jin 2nd Rd, Shanghai, 200025, China.
| | | | | | - Geng Zong
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Boyu Song
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Chongrong Shen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Puchen Zhou
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yufei Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yanpu Wu
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Huibin Lin
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - He Zheng
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Mengshan Ni
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xiaowei Yang
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Yanru Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xinming Xu
- Shanghai Medical College, Fudan University, Shanghai, 200032, China
| | - Juan Zhang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Juan Shi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Ru Zhang
- SAIC Volkswagen Automotive Company Limited, Shanghai, 201805, China
| | - Jinfen Hu
- SAIC Volkswagen Automotive Company Limited, Shanghai, 201805, China
| | - Hong Hou
- SAIC Volkswagen Automotive Company Limited, Shanghai, 201805, China
| | - Ling Lu
- Key Laboratory of Systems Health Science of Zhejiang Province, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, 310024, China
- Key Laboratory of Systems Biology, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Hangzhou, 310024, China
| | | | - Liming Liang
- Department of Epidemiology and Department of Biostatistics, Harvard T H Chan School of Public Health, Boston, MA, 02115, USA
| | - Ruixin Liu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xiaoran Liu
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Huaixing Li
- Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China
| | - Jie Hong
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xu Lin
- Xu Lin, MD, PhD, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, 320 Yue-yang Rd., Shanghai, 200031, China.
| | - Guang Ning
- Correspondence: Guang Ning, MD, PhD, Key Laboratory for Endocrine and Metabolic Diseases of Ministry of Health, Department of Endocrine and Metabolic Diseases, Rui-Jin Hospital, Shanghai Jiao-Tong University School of Medicine, 197 Rui-Jin 2nd Rd, Shanghai, 200025, China.
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Ji SH, Dong C, Chen R, Shen CC, Xiao J, Gu YJ, Gao JL. Effects of Variability in Glycemic Indices on Longevity in Chinese Centenarians. Front Nutr 2022; 9:955101. [PMID: 35879983 PMCID: PMC9307500 DOI: 10.3389/fnut.2022.955101] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Accepted: 06/20/2022] [Indexed: 12/11/2022] Open
Abstract
Background Large fluctuations in blood glucose levels greatly impact the health and life span of elderly individuals. This study describes the characteristics of variability in glycemic indices in centenarians with the aim of emphasizing the importance of glycemic variability in elderly people. Methods We recruited individuals from Rugao City, Jiangsu Province, China from April 2020 to May 2021. The study cohort included 60 centenarians and 60 first-generation offspring, as well as 20 randomly selected non-cohabitant control individuals aged 60–80 years. A FreeStyle Libre H (hospital version) continuous glucose monitoring (CGM) device (Abbott Ireland UK) was used to measure glycemic variability. The indices measured included the time in target glucose range (TIR), time below target glucose range (TBR), time above target glucose range (TAR), mean amplitude of glycemic excursions (MAGE), mean of daily differences (MODD), coefficient of variation (CV), standard deviation of blood glucose (SDBG), continuous overlapping net glycemic action (CONGA), glucose management indicator (GMI) and estimated glycated hemoglobin (eHbA1c). Logistic regression was used to analyze the association between glycemic variability and longevity. Results Mean blood glucose (MBG), eHbA1c, GMI, mean fasting plasma glucose (M-FPG) and CONGA were lower in the centenarian group (p all < 0.05). PPGE-2 was higher in the control group than that measured in the centenarian and first-generation offspring groups (p < 0.05). There were no differences between the groups in MAGE, MODD, MAG, or TIR (p > 0.05). The risk of not achieving longevity increased with each one unit increase in MBG by 126% [2.26 (1.05–4.91)], eHbA1c by 67% [1.67 (1.03–2.72)], GMI by 568% [6.68 (1.11–40.30)], M-FPG by 365% [4.65 (1.57–13.75)], M-PPG1h by 98% [1.98 (1.18–3.31)], CONGA1 by 102% [2.02 (1.01–4.06)], Li by 200% [3.00 (1.04–8.61)], and PPGE-2 by 150% [2.50 (1.39–4.50)]. However, the risk of achieving longevity decreased with each unit increase of LBGI by 53% [0.47 (0.28–0.80)], ADRR by 60% [0.40 (0.18–0.86)], and TBR by 11% [0.89 (0.80–0.98)]. Conclusion Fluctuation in blood glucose levels in centenarians is relatively small. Maintaining an average blood glucose level and keeping blood glucose fluctuations in the normal range is conducive to longevity.
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Affiliation(s)
- Sheng-han Ji
- Department of Endocrinology and Metabolism, Affiliated Hospital of Nantong University, Nantong, China
- Medical School of Nantong University, Nantong University, Nantong, China
| | - Chen Dong
- Research Center of Gerontology and Longevity, Affiliated Hospital of Nantong University, Nantong, China
| | - Rou Chen
- Department of Endocrinology and Metabolism, Affiliated Hospital of Nantong University, Nantong, China
- Medical School of Nantong University, Nantong University, Nantong, China
| | - Chen-chen Shen
- Department of Cardiology, Rugao Bo'ai Branch of Nantong University Affiliated Hospital, Nantong, China
| | - Jing Xiao
- Department of Epidemiology and Medical Statistics, School of Public Health, Nantong University, Nantong, China
| | - Yun-juan Gu
- Department of Endocrinology and Metabolism, Affiliated Hospital of Nantong University, Nantong, China
- Department of Health Medicine, Affiliated Hospital of Nantong University, Nantong, China
- *Correspondence: Yun-juan Gu
| | - Jian-lin Gao
- Research Center of Gerontology and Longevity, Affiliated Hospital of Nantong University, Nantong, China
- Jian-lin Gao
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Mo Y, Wang C, Lu J, Shen Y, Chen L, Zhang L, Lu W, Zhu W, Xia T, Zhou J. Impact of short-term glycemic variability on risk of all-cause mortality in type 2 diabetes patients with well-controlled glucose profile by continuous glucose monitoring: A prospective cohort study. Diabetes Res Clin Pract 2022; 189:109940. [PMID: 35662611 DOI: 10.1016/j.diabres.2022.109940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 05/12/2022] [Accepted: 05/30/2022] [Indexed: 11/25/2022]
Abstract
AIMS To investigate the association between short-term glycemic variability (GV) and all-cause mortality in type 2 diabetes with well-controlled glucose profile by continuous glucose monitoring (CGM). METHODS In this prospective study, 1839 diabetes patients who reached percentage of time in the target glucose range of 3.9-10 mmol/L > 70%, percentage of time above range of 10 mmol/L < 25% and percentage of time below range of 3.9 mmol/L < 4% on CGM were enrolled and were classified into five groups by coefficient of variation for glucose (%CV) level: ≤20%, 20-25%, 25-30%, 30-35%, and > 35%. Cox proportional hazard models were used to estimate hazard ratios (HRs) of all-cause mortality risk associated with the different %CV categories. RESULTS At baseline, participants had mean age of 60.9 years and mean HbA1c of 7.3% (56 mmol/mol). A total of 165 deaths were identified during a median follow-up of 6.9 years. In multivariate Cox regression analysis, HRs associated with %CV categories were 1.00, 1.16 (95% CI 0.78-1.73), 1.38 (95% CI 0.89-2.15), 1.33 (95% CI 0.77-2.29) and 2.26 (95% CI 1.13-4.52) for all-cause mortality. CONCLUSIONS Greater %CV was associated with increased risk for all-cause mortality even among patients with seemingly well-controlled glucose status.
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Affiliation(s)
- Yifei Mo
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China
| | - Chunfang Wang
- Vital Statistical Department, Institute of Health Information, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Jingyi Lu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China
| | - Yun Shen
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China
| | - Lei Chen
- Vital Statistical Department, Institute of Health Information, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Lei Zhang
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China
| | - Wei Lu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China
| | - Wei Zhu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China
| | - Tian Xia
- Vital Statistical Department, Institute of Health Information, Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China.
| | - Jian Zhou
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, China.
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Mesa A, Giménez M, Pueyo I, Perea V, Viñals C, Blanco J, Vinagre I, Serés-Noriega T, Boswell L, Esmatjes E, Conget I, Amor AJ. Hyperglycemia and hypoglycemia exposure are differentially associated with micro- and macrovascular complications in adults with Type 1 Diabetes. Diabetes Res Clin Pract 2022; 189:109938. [PMID: 35662616 DOI: 10.1016/j.diabres.2022.109938] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 05/10/2022] [Accepted: 05/30/2022] [Indexed: 11/03/2022]
Abstract
AIMS Evaluate the relationship between high and low exposure continuous glucose monitoring (CGM)-derived glucometrics and micro- and macrovascular complications in type 1 diabetes (T1D). METHODS Cross-sectional study in T1D without cardiovascular disease (CVD) and with ≥ 1 of the following: ≥40 years, diabetic nephropathy, or ≥ 10 years of diabetes duration with CVD risk factors. Glucometrics were obtained over 14 consecutive days: glucose management indicator (GMI) and proportion of time < 54 (TBR < 54), <70, 70-180 (TIR), >180 (TAR). Carotid plaque was evaluated by ultrasonography. Logistic regression models adjusted for age, sex, and other risk factors were constructed to test the independent associations with chronic complications. RESULTS We included 152 patients (54.6% men, 48.7 ± 10.0 years-old). Sixty-seven patients had plaque and n = 71 microvascular complications. TAR (OR 1.28 [1.09-1.51]) and GMI (OR 3.05 [1.46-6.36]) were directly associated with the presence of microvascular complications, while TIR had an inverse relationship (OR 0.79 [0.66-0.93]). TBR < 54 was directly associated with the presence of plaque, even after adjusting for 5-year mean HbA1c (OR 1.51 [1.07-2.13]). CONCLUSIONS High-glucose glucometrics were independently associated with microvascular complications. Only low-glucose exposure glucometrics was significantly associated with preclinical atherosclerosis. Our data support the role of hypoglycemia in the development of CVD in this population.
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Affiliation(s)
- Alex Mesa
- Diabetes Unit, Endocrinology and Nutrition Department, ICMDM, Hospital Clínic de Barcelona, Spain
| | - Marga Giménez
- Diabetes Unit, Endocrinology and Nutrition Department, ICMDM, Hospital Clínic de Barcelona, Spain; IDIBAPS (Institut d'investigacions biomèdiques August Pi i Sunyer), Barcelona, Spain; CIBERDEM (Centro de Investigación en Red de Diabetes y Enfermedades Metabólicas), Madrid, Spain.
| | - Irene Pueyo
- Diabetes Unit, Endocrinology and Nutrition Department, ICMDM, Hospital Clínic de Barcelona, Spain
| | - Verónica Perea
- Endocrinology and Nutrition Department, Hospital Universitari Mútua Terrassa, Terrassa, Spain
| | - Clara Viñals
- Diabetes Unit, Endocrinology and Nutrition Department, ICMDM, Hospital Clínic de Barcelona, Spain
| | - Jesús Blanco
- Diabetes Unit, Endocrinology and Nutrition Department, ICMDM, Hospital Clínic de Barcelona, Spain; IDIBAPS (Institut d'investigacions biomèdiques August Pi i Sunyer), Barcelona, Spain
| | - Irene Vinagre
- Diabetes Unit, Endocrinology and Nutrition Department, ICMDM, Hospital Clínic de Barcelona, Spain; IDIBAPS (Institut d'investigacions biomèdiques August Pi i Sunyer), Barcelona, Spain
| | - Tonet Serés-Noriega
- Diabetes Unit, Endocrinology and Nutrition Department, ICMDM, Hospital Clínic de Barcelona, Spain
| | - Laura Boswell
- Diabetes Unit, Endocrinology and Nutrition Department, ICMDM, Hospital Clínic de Barcelona, Spain; Endocrinology and Nutrition Department, Althaia - Xarxa Assistencial Universitària de Manresa, Manresa, Spain
| | - Enric Esmatjes
- Diabetes Unit, Endocrinology and Nutrition Department, ICMDM, Hospital Clínic de Barcelona, Spain; IDIBAPS (Institut d'investigacions biomèdiques August Pi i Sunyer), Barcelona, Spain; CIBERDEM (Centro de Investigación en Red de Diabetes y Enfermedades Metabólicas), Madrid, Spain
| | - Ignacio Conget
- Diabetes Unit, Endocrinology and Nutrition Department, ICMDM, Hospital Clínic de Barcelona, Spain; IDIBAPS (Institut d'investigacions biomèdiques August Pi i Sunyer), Barcelona, Spain; CIBERDEM (Centro de Investigación en Red de Diabetes y Enfermedades Metabólicas), Madrid, Spain
| | - Antonio J Amor
- Diabetes Unit, Endocrinology and Nutrition Department, ICMDM, Hospital Clínic de Barcelona, Spain.
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Ye J, Deng J, Liang W, Luo H, Wen M, Liu L, Wang M, Shu Y. Time in Range Assessed by Capillary Blood Glucose in Relation to Insulin Sensitivity and β-Cell Function in Patients with Type 2 Diabetes Mellitus: A Cross-Sectional Study in China. J Diabetes Investig 2022; 13:1825-1833. [PMID: 35739637 DOI: 10.1111/jdi.13876] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 06/06/2022] [Accepted: 06/13/2022] [Indexed: 11/29/2022] Open
Abstract
AIMS This study investigated the association of capillary blood glucose (CBG)-assessed time in range (TIR) (3.9-10.0 mmol/L) with insulin sensitivity and islet β-cell function (BCF). MATERIALS AND METHODS We recruited 455 patients with type 2 diabetes mellitus. Seven-point glucose-profile data (pre- and 120-min post-main meals, bedtime) were collected over three consecutive days. Plasma glucose and serum insulin concentrations were measured at 0, 60, and 120 min after a 100-g standard steamed bread meal test. The homeostasis model assessment of insulin resistance (HOMA-IR) and Matsuda index were computed to evaluate insulin resistance (IR). HOMA of β-cell function (HOMA-β) and the area under the curve between insulin and blood glucose (IAUC0-120 /GAUC0-120 ) were used to estimate BCF. RESULTS TIR was positively correlated with 60- and 120-min insulin values, IAUC0-120 , the Matsuda index, HOMA-β, and IAUC0-120 /GAUC0-120 (rs : 0.154, 0.129, 0.137, 0.194, 0.341, and 0.334, respectively; P <0.05) but inversely correlated with HOMA-IR (rs : -0.239, P <0.001). After adjusting for confounders, multinomial multiple logistic regression analysis revealed that the odds ratios (ORs) of achieving the target TIR (>70%) increased by 12% (95% confidence interval [CI]: 3-21%), 7% (95% CI: 1-14%), 10% (95% CI: 5-16%), and 45% (95% CI: 25-68%) for each 10-mIU/L increase in 60- and 120-min insulin value, 10-unit increase in HOMA-β, and unit increase in IAUC0-120 /GAUC0-120 , respectively (P <0.05). Nevertheless, the OR decreased by 10% (95% CI: 1-18%) for each unit increase in HOMA-IR (P <0.05). CONCLUSIONS IR and BCF are related to CBG-assessed TIR.
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Affiliation(s)
- Jingwen Ye
- Department of Endocrinology,the Sixth Affiliated Hospital, South China University of Technology, Guidan Road 120, Foshan, 528200, Guangdong Province, China
| | - Jiajin Deng
- Department of Ophthalmology,the Sixth Affiliated Hospital, South China University of Technology, Guidan Road 120, Foshan, 528200, Guangdong Province, China
| | - Weiqiang Liang
- Department of Endocrinology,the Sixth Affiliated Hospital, South China University of Technology, Guidan Road 120, Foshan, 528200, Guangdong Province, China
| | - Haizhao Luo
- Department of Endocrinology,the Sixth Affiliated Hospital, South China University of Technology, Guidan Road 120, Foshan, 528200, Guangdong Province, China
| | - Mei Wen
- Department of Endocrinology,the Sixth Affiliated Hospital, South China University of Technology, Guidan Road 120, Foshan, 528200, Guangdong Province, China
| | - Lei Liu
- Department of Endocrinology,the Sixth Affiliated Hospital, South China University of Technology, Guidan Road 120, Foshan, 528200, Guangdong Province, China
| | - Mingzhu Wang
- Department of Endocrinology,the Sixth Affiliated Hospital, South China University of Technology, Guidan Road 120, Foshan, 528200, Guangdong Province, China
| | - Yi Shu
- Department of Endocrinology,the Sixth Affiliated Hospital, South China University of Technology, Guidan Road 120, Foshan, 528200, Guangdong Province, China
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Shen Y, Chen L, Zhou J, Wang C, Gao F, Zhu W, Hu G, Ma X, Xia H, Bao Y. Low total osteocalcin levels are associated with all-cause and cardiovascular mortality among patients with type 2 diabetes: a real-world study. Cardiovasc Diabetol 2022; 21:98. [PMID: 35681236 PMCID: PMC9185881 DOI: 10.1186/s12933-022-01539-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/03/2022] [Accepted: 05/25/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The association between osteocalcin and mortality has been scantly studied. We aimed to investigate the association between osteocalcin along with its trajectories and mortality based on long-term longitudinal data. METHODS We performed a retrospective cohort study of 9413 type 2 diabetic patients with at least three measurements of total serum osteocalcin within 3 years since their first inpatient diagnosis of type 2 diabetes. Baseline, mean values of osteocalcin levels and their trajectories were used as exposures. A multivariable-adjusted Cox proportional hazards model was used to estimate the association of osteocalcin levels and their trajectories with mortality. RESULTS During a mean follow-up of 5.37 years, 1638 patients died, of whom 588 were due to cardiovascular events. Multivariable-adjusted hazard ratios (HRs) across quintiles of baseline osteocalcin levels were 2.88 (95% confidence interval (CI) 2.42-3.42), 1.65 (95% CI 1.37-1.99), 1.17 (95% CI 0.96-1.42), 1.00, and 1.92 (95% CI 1.60-2.30) for all-cause mortality, and 3.52 (95% CI 2.63-4.71), 2.00 (95% CI 1.46-2.73), 1.03 (95% CI 0.72-1.47), 1.00, 1.67 (95% CI 1.21-2.31) for CVD mortality, respectively. When we used the mean values of osteocalcin as the exposure, U-shaped associations were also found. These U-shaped associations were consistent among patients of different baseline characteristics. Patients with a stable or even increasing trajectory of osteocalcin may have a lower risk of both all-cause and CVD mortality. CONCLUSIONS A U-shape association between baseline osteocalcin and mortality was observed among patients with type 2 diabetes. Patients with lower levels of serum osteocalcin during follow-ups had higher risks for all-cause and cardiovascular mortality.
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Affiliation(s)
- Yun Shen
- Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China.,Chronic Disease Epidemiology, Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA
| | - Lei Chen
- Division of Vital Statistics, Institute of Health Information, Shanghai Municipal Center for Disease Control and Prevention, 1380 West Zhongshan Road, Shanghai, 200336, China
| | - Jian Zhou
- Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Chunfang Wang
- Division of Vital Statistics, Institute of Health Information, Shanghai Municipal Center for Disease Control and Prevention, 1380 West Zhongshan Road, Shanghai, 200336, China
| | - Fei Gao
- Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Wei Zhu
- Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Gang Hu
- Chronic Disease Epidemiology, Pennington Biomedical Research Center, Baton Rouge, LA, 70808, USA
| | - Xiaojing Ma
- Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China.
| | - Han Xia
- Division of Vital Statistics, Institute of Health Information, Shanghai Municipal Center for Disease Control and Prevention, 1380 West Zhongshan Road, Shanghai, 200336, China.
| | - Yuqian Bao
- Department of Endocrinology and Metabolism, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China.
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Rojano-Toimil A, Rivera-Esteban J, Manzano-Nuñez R, Bañares J, Martinez Selva D, Gabriel-Medina P, Ferrer R, Pericàs JM, Ciudin A. When Sugar Reaches the Liver: Phenotypes of Patients with Diabetes and NAFLD. J Clin Med 2022; 11:jcm11123286. [PMID: 35743358 PMCID: PMC9225139 DOI: 10.3390/jcm11123286] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Revised: 06/03/2022] [Accepted: 06/06/2022] [Indexed: 01/27/2023] Open
Abstract
Type 2 diabetes mellitus (T2DM) and non-alcoholic fatty liver disease (NAFLD) have been traditionally linked to one another. Recent studies suggest that NAFLD may be increasingly common in other types of diabetes such as type 1 diabetes (T1DM) and less frequently ketone-prone and Maturity-onset Diabetes of the Young (MODY) diabetes. In this review, we address the relationship between hyperglycemia and insulin resistance and the onset and progression of NAFLD. In addition, despite the high rate of patients with T2DM and other diabetes phenotypes that can alter liver metabolism and consequently develop steatosis, fibrosis, and cirrhosis, NALFD screening is not still implemented in the daily care routine. Incorporating a clinical algorithm created around a simple, non-invasive, cost-effective model would identify high-risk patients. The principle behind managing these patients is to improve insulin resistance and hyperglycemia states with lifestyle changes, weight loss, and new drug therapies.
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Affiliation(s)
- Alba Rojano-Toimil
- Endocrinology Department, Vall d’Hebron University Hospital, 08035 Barcelona, Spain;
- Vall d’Hebron Institut de Recerca (VHIR), 08035 Barcelona, Spain; (J.R.-E.); (R.M.-N.); (J.B.); (D.M.S.)
| | - Jesús Rivera-Esteban
- Vall d’Hebron Institut de Recerca (VHIR), 08035 Barcelona, Spain; (J.R.-E.); (R.M.-N.); (J.B.); (D.M.S.)
- Medicine Department Bellaterra, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
- Liver Unit, Vall d’Hebron University Hospital, 08035 Barcelona, Spain
| | - Ramiro Manzano-Nuñez
- Vall d’Hebron Institut de Recerca (VHIR), 08035 Barcelona, Spain; (J.R.-E.); (R.M.-N.); (J.B.); (D.M.S.)
- Liver Unit, Vall d’Hebron University Hospital, 08035 Barcelona, Spain
| | - Juan Bañares
- Vall d’Hebron Institut de Recerca (VHIR), 08035 Barcelona, Spain; (J.R.-E.); (R.M.-N.); (J.B.); (D.M.S.)
- Liver Unit, Vall d’Hebron University Hospital, 08035 Barcelona, Spain
| | - David Martinez Selva
- Vall d’Hebron Institut de Recerca (VHIR), 08035 Barcelona, Spain; (J.R.-E.); (R.M.-N.); (J.B.); (D.M.S.)
- Spanish Network of Biomedical Research Centers, Diabetes and Metabolic Associated Disorders (CIBERdem), 28029 Madrid, Spain
| | - Pablo Gabriel-Medina
- Biochemistry Department, Vall d’Hebron University Hospital, 08035 Barcelona, Spain; (P.G.-M.); (R.F.)
- Biochemistry and Molecular Biology Department, Universitat Autònoma de Barcelona (UAB), Bellaterra, 08193 Barcelona, Spain
| | - Roser Ferrer
- Biochemistry Department, Vall d’Hebron University Hospital, 08035 Barcelona, Spain; (P.G.-M.); (R.F.)
| | - Juan M Pericàs
- Vall d’Hebron Institut de Recerca (VHIR), 08035 Barcelona, Spain; (J.R.-E.); (R.M.-N.); (J.B.); (D.M.S.)
- Liver Unit, Vall d’Hebron University Hospital, 08035 Barcelona, Spain
- Spanish Network of Biomedical Research Centers, Liver and Digestive Diseases (CIBERehd), 28801 Madrid, Spain
- Correspondence: (J.M.P.); (A.C.)
| | - Andreea Ciudin
- Endocrinology Department, Vall d’Hebron University Hospital, 08035 Barcelona, Spain;
- Vall d’Hebron Institut de Recerca (VHIR), 08035 Barcelona, Spain; (J.R.-E.); (R.M.-N.); (J.B.); (D.M.S.)
- Medicine Department Bellaterra, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
- Spanish Network of Biomedical Research Centers, Diabetes and Metabolic Associated Disorders (CIBERdem), 28029 Madrid, Spain
- Correspondence: (J.M.P.); (A.C.)
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Battelino T, Bergenstal RM, Rodríguez A, Fernández Landó L, Bray R, Tong Z, Brown K. Efficacy of once-weekly tirzepatide versus once-daily insulin degludec on glycaemic control measured by continuous glucose monitoring in adults with type 2 diabetes (SURPASS-3 CGM): a substudy of the randomised, open-label, parallel-group, phase 3 SURPASS-3 trial. Lancet Diabetes Endocrinol 2022; 10:407-417. [PMID: 35468321 DOI: 10.1016/s2213-8587(22)00077-8] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 02/21/2022] [Accepted: 02/22/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND Tirzepatide is a novel dual glucose-dependent insulinotropic polypeptide (GIP) and GLP-1 receptor agonist under development for the treatment of type 2 diabetes. In this study, we used continuous glucose monitoring (CGM) to compare the 24 h glucose profile for participants given tirzepatide compared with those given insulin degludec. METHODS This substudy of the open-label, parallel-group, phase 3 SURPASS-3 trial, was done at 45 sites across six countries (Hungary, Poland, Romania, Spain, Ukraine, and the USA). Eligible participants in the main study were adults with type 2 diabetes, a baseline HbA1c of 7·0-10·5% (53-91 mmol/mol), and a BMI of 25 kg/m2 or more, who were insulin-naive, and treated with metformin alone or in combination with a SGLT2 inhibitor for at least 3 months before screening. Participants in the main study were randomly assigned (1:1:1:1) to receive once-weekly subcutaneous injection of tirzepatide 5 mg, 10 mg, or 15 mg, or once-daily subcutaneous injection of titrated insulin degludec (100 U/mL), using an interactive web-response system. Participants were stratified by country, HbA1c concentration, and concomitant oral antihyperglycaemic medication. A subset of these patients with a normal wake-sleep cycle were enrolled into this substudy, and interstitial glucose values were collected by CGM for approximately 7 days at baseline, 24 weeks, and 52 weeks. The primary outcome was to compare pooled participants assigned to 10 mg and 15 mg tirzepatide versus insulin degludec for the proportion of time that CGM values were in the tight target range (71-140 mg/dL) at 52 weeks, assessed in all randomly assigned participants who received at least one dose of study drug and had an evaluable CGM session at either baseline or after baseline. The secondary outcomes were to compare tirzepatide (5 mg, 10 mg, and 15 mg) versus insulin degludec for the proportion and duration of time in tight target range at 24 and 52 weeks. This was a substudy of the trial registered with ClinicalTrials.gov, NCT03882970, and is complete. FINDINGS From April 1 to Nov 27, 2019, 313 participants were screened for eligibility, 243 of whom were enrolled in CGM substudy (tirzepatide 5 mg, n=64; tirzepatide 10 mg, n=51; tirzepatide 15 mg, n=73; and insulin degludec, n=55). Patients given once-weekly tirzepatide (pooled 10 mg and 15 mg groups) had a greater proportion of time in tight target range compared with patients given insulin degludec (estimated treatment difference 25% [95% CI 16-33]; p<0·0001). Participants assigned to tirzepatide spent significantly more time in tight target range at 52 weeks compared with those assigned to insulin degludec (5 mg 12% [1-22], p=0·031; 10 mg 24% [13-35], p<0·0001; and 15 mg 25% [14-35], p<0·0001). Participants assigned to tirzepatide 10 mg and 15 mg, but not to tirzepatide 5 mg, spent significantly more time in tight target range at 24 weeks compared with insulin degludec (10 mg 19% [8-30], p=0·0008; 15 mg 21% [11-31], p<0·0001). INTERPRETATION Once-weekly treatment with tirzepatide showed superior glycaemic control measured using CGM compared with insulin degludec in participants with type 2 diabetes on metformin, with or without a SGLT2 inhibitor. These new data provide additional evidence to the effect of tirzepatide and potential for achieving glycaemic targets without increase of hypoglycaemic risk compared with a basal insulin. FUNDING Eli Lilly and Company.
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Affiliation(s)
- Tadej Battelino
- Faculty of Medicine, University of Ljubljana, and University Medical Center Ljubljana, Ljubljana, Slovenia
| | | | | | | | - Ross Bray
- Eli Lilly and Company, Indianapolis, IN, USA
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84
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Forst T. Paradigmenwechsel in der Glukosekontrolle: Urin-, Blut-, interstitielle Glukosemessung. DIABETOL STOFFWECHS 2022. [DOI: 10.1055/a-1225-8678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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85
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Kommentar zu Kontinuierliche Glukosemessung: am besten dauerhaft beibehalten! DIABETOL STOFFWECHS 2022. [DOI: 10.1055/a-1732-8882] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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Yapanis M, James S, Craig ME, O’Neal D, Ekinci EI. Complications of Diabetes and Metrics of Glycemic Management Derived From Continuous Glucose Monitoring. J Clin Endocrinol Metab 2022; 107:e2221-e2236. [PMID: 35094087 PMCID: PMC9113815 DOI: 10.1210/clinem/dgac034] [Citation(s) in RCA: 77] [Impact Index Per Article: 38.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Indexed: 11/19/2022]
Abstract
CONTEXT Although glycated hemoglobin A1c is currently the best parameter used clinically to assess risk for the development of diabetes complications, it does not provide insight into short-term fluctuations in glucose levels. This review summarizes the relationship between continuous glucose monitoring (CGM)-derived metrics of glycemic variability and diabetes-related complications. EVIDENCE ACQUISITION PubMed and Embase databases were searched from January 1, 2010 to August 22, 2020, using the terms type 1 diabetes, type 2 diabetes, diabetes-related microvascular and macrovascular complications, and measures of glycaemic variability. Exclusion criteria were studies that did not use CGM and studies involving participants who were not diabetic, acutely unwell (post stroke, post surgery), pregnant, or using insulin pumps. EVIDENCE SYNTHESIS A total of 1636 records were identified, and 1602 were excluded, leaving 34 publications in the final review. Of the 20 852 total participants, 663 had type 1 diabetes (T1D) and 19 909 had type 2 diabetes (T2D). Glycemic variability and low time in range (TIR) showed associations with all studied microvascular and macrovascular complications of diabetes. Notably, higher TIR was associated with reduced risk of albuminuria, retinopathy, cardiovascular disease mortality, all-cause mortality, and abnormal carotid intima-media thickness. Peripheral neuropathy was predominantly associated with standard deviation of blood glucose levels (SD) and mean amplitude of glycemic excursions (MAGE). CONCLUSION The evidence supports the association between diabetes complications and CGM-derived measures of intraday glycemic variability. TIR emerged as the most consistent measure, supporting its emerging role in clinical practice. More longitudinal studies and trials are required to confirm these associations, particularly for T1D, for which there are limited data.
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Affiliation(s)
- Michael Yapanis
- Department of Medicine, the University of Melbourne, Parkville 3052, Victoria, Australia
- Department of Endocrinology, Austin Health, Heidelberg 3084, Victoria, Australia
| | - Steven James
- School of Nursing, Midwifery and Paramedicine, the University of the Sunshine Coast, Petrie 4052, Queensland, Australia
| | - Maria E Craig
- School of Clinical Medicine, UNSW Medicine and Health, Discipline of Paediatrics and Child Health, UNSW 2052, NSW, Australia
- The University of Sydney Children’s Hospital Westmead Clinical School, Westmead 2145, NSW, Australia
| | - David O’Neal
- Department of Medicine, the University of Melbourne, Parkville 3052, Victoria, Australia
- Department of Endocrinology, St Vincent’s Hospital, Fitzroy 3065, Victoria, Australia
| | - Elif I Ekinci
- Department of Medicine, the University of Melbourne, Parkville 3052, Victoria, Australia
- Department of Endocrinology, Austin Health, Heidelberg 3084, Victoria, Australia
- Correspondence: Elif I. Ekinci, PhD, Level 1 Centaur Building, Heidelberg Repatriation Hospital, 330 Waterdale Rd, Heidelberg Heights 3081, Victoria, Australia.
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87
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Di Molfetta S, Rossi A, Assaloni R, Cherubini V, Consoli A, Di Bartolo P, Guardasole V, Laurenzi A, Lombardo F, Maffeis C, Scaramuzza A, Irace C. A guide for the use of LibreView digital diabetes platform in clinical practice: Expert paper of the Italian Working Group on Diabetes and Technology. Diabetes Res Clin Pract 2022; 187:109867. [PMID: 35405166 DOI: 10.1016/j.diabres.2022.109867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Revised: 03/16/2022] [Accepted: 04/04/2022] [Indexed: 11/22/2022]
Abstract
Wider access to continuous glucose monitoring systems, including flash glucose monitoring, has enabled people with diabetes to achieve lower HbA1c levels and reduce the amount of time they spend in hypoglycaemia or hyperglycaemia, and has improved their quality of life. An International Consensus Panel proposed different target glucose ranges and recommendations according to different ages and situations (adults, young people and children with type 1 or type 2 diabetes, as well as elderly people who are at higher risk of hypoglycaemia, and women with diabetes during pregnancy). In this expert opinion, we interpret the international recommendations in the context of established clinical practice for diabetes care, and propose three different step-by-step algorithms to help the healthcare professionals use the most innovative glucose metrics, including time in glucose ranges, glucose management indicator, coefficient of variation, and ambulatory glucose profile. In detail, we focus on glucose metrics as measured by the FreeStyle Libre system and as visualized on the LibreView digital diabetes platform to support appropriate interpretation of flash glucose monitoring data. This is specifically structured for healthcare professionals and general practitioners who may have a low level of confidence with diabetes technology, with the aim of optimizing diabetes management, ensuring effective use of healthcare resources and to maximise outcomes for people with diabetes.
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Affiliation(s)
- Sergio Di Molfetta
- Section of Internal Medicine, Endocrinology, Andrology and Metabolic Diseases, Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Bari, Italy
| | - Antonio Rossi
- Division of Endocrinology, ASST Fatebenefratelli-Sacco, Milan, Italy
| | - Roberta Assaloni
- Diabetes Unit ASS2 Bassa-Friulana Isontina, Udine, Monfalcone, GO, Italy
| | - Valentino Cherubini
- Department of Women's and Children's Health, G. Salesi Hospital, Ancona, Italy
| | - Agostino Consoli
- Endocrinology and Metabolic Diseases, University of Chieti-Pescara, Chieti, Italy
| | | | - Vincenzo Guardasole
- Department of Translational Medical Sciences, University Federico II, Naples, Italy
| | - Andrea Laurenzi
- San Raffaele Diabetes Research Institute, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Fortunato Lombardo
- Department of Human Pathology in Adult and Developmental Age "Gaetano Barresi", University of Messina, Messina, Italy
| | - Claudio Maffeis
- Pediatric Diabetes and Metabolic Disorders Unit, Regional Center for Pediatric Diabetes, University City Hospital of Verona, Verona, Italy
| | - Andrea Scaramuzza
- Division of Pediatrics, ASST Cremona, "Ospedale Maggiore di Cremona", Cremona, Italy
| | - Concetta Irace
- Department of Health Science, University Magna Graecia, Catanzaro, Italy
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88
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Schnell O, Battelino T, Bergenstal R, Blüher M, Böhm M, Brosius F, Carr RD, Ceriello A, Forst T, Giorgino F, Guerci B, Heerspink HJL, Itzhak B, Ji L, Kosiborod M, Lalić N, Lehrke M, Marx N, Nauck M, Rodbard HW, Rosano GMC, Rossing P, Rydén L, Santilli F, Schumm-Draeger PM, Vandvik PO, Vilsbøll T, Wanner C, Wysham C, Standl E. Report from the CVOT Summit 2021: new cardiovascular, renal, and glycemic outcomes. Cardiovasc Diabetol 2022; 21:50. [PMID: 35395808 PMCID: PMC8990484 DOI: 10.1186/s12933-022-01481-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 03/14/2022] [Indexed: 02/07/2023] Open
Abstract
The 7th Cardiovascular Outcome Trial (CVOT) Summit on Cardiovascular, Renal, and Glycemic Outcomes, was held virtually on November 18-19, 2021. Pursuing the tradition of the previous summits, this reference congress served as a platform for in-depth discussion and exchange on recently completed CVOTs. This year's focus was placed on the outcomes of EMPEROR-Preserved, FIGARO-DKD, AMPLITUDE-O, SURPASS 1-5, and STEP 1-5. Trial implications for diabetes and obesity management and the impact on new treatment algorithms were highlighted for endocrinologists, diabetologists, cardiologists, nephrologists, and general practitioners. Discussions evolved from outcome trials using SGLT2 inhibitors as therapy for heart failure, to CVOTs with nonsteroidal mineralocorticoid receptor antagonists and GLP-1 receptor agonists. Furthermore, trials for glycemic and overweight/obesity management, challenges in diabetes management in COVID-19, and novel guidelines and treatment strategies were discussed.Trial registration The 8th Cardiovascular Outcome Trial Summit will be held virtually on November 10-11, 2022 ( http://www.cvot.org ).
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Affiliation(s)
- Oliver Schnell
- Forschergruppe Diabetes e. V., Helmholtz Center Munich, Ingolstaedter Landstraße 1, 85764 Munich, Germany
| | - Tadej Battelino
- University Medical Center, Ljubljana, Slovenia
- University Children’s Hospital, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Richard Bergenstal
- International Diabetes Center at Park Nicollet, Health Partners, Minneapolis, MN USA
| | - Matthias Blüher
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | - Michael Böhm
- Klinik für Innere Medizin III, Universitätsklinikum des Saarlandes, Saarland University, Homburg, Germany
| | - Frank Brosius
- College of Medicine, University of Arizona, Tuscon, AZ USA
| | | | | | - Thomas Forst
- CRS Clinical Research Services Mannheim GmbH, Mannheim, Germany
| | - Francesco Giorgino
- Department of Emergency and Organ Transplantation, University of Bari Aldo Moro, Bari, Italy
| | - Bruno Guerci
- Department of Endocrinology Diabetology and Nutrition, Nancy University Hospital, Nancy, France
- Faculty of Medicine, University of Lorraine, Vandoeuvre-lès-Nancy, France
| | - Hiddo J. L. Heerspink
- Department of Clinical Pharmacy and Pharmacology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Baruch Itzhak
- Clalit Health Services and Technion Faculty of Medicine, Haifa, Israel
| | - Linong Ji
- Peking University People’s Hospital, Xicheng District, Beijing, China
| | - Mikhail Kosiborod
- Cardiometabolic Center of Excellence, University of Missouri-Kansas City, Kansas City, MO USA
| | - Nebojša Lalić
- Faculty of Medicine, Clinic for Endocrinology, Diabetes and Metabolic Diseases, University Clinical Center of Serbia, University of Belgrade, Belgrade, Serbia
| | - Michael Lehrke
- Department of Internal Medicine I, University Hospital Aachen, Aachen, Germany
| | - Nikolaus Marx
- Department of Internal Medicine I, University Hospital Aachen, Aachen, Germany
| | - Michael Nauck
- Diabetes Division, Katholisches Klinikum Bochum, St. Josef-Hospital, Ruhr University Bochum, Bochum, Germany
| | | | | | - Peter Rossing
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - Lars Rydén
- Department of Medicine K2, Karolinska Institute, Stockholm, Sweden
| | - Francesca Santilli
- Department of Medicine and Aging, Hospital and, University of Chieti, Chieti, Italy
| | | | - Per Olav Vandvik
- Department of Medicine, Lovisenberg Diaconal Hospital, Oslo, Norway
| | - Tina Vilsbøll
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- Center for Diabetes Research, Gentofte Hospital, University of Copenhagen, Hellerupn, Denmark
| | | | - Carol Wysham
- Section of Endocrinology and Metabolism, MultiCare Rockwood Clinic, Spokane, WA USA
| | - Eberhard Standl
- Forschergruppe Diabetes e. V., Helmholtz Center Munich, Ingolstaedter Landstraße 1, 85764 Munich, Germany
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Czupryniak L, Dzida G, Fichna P, Jarosz-Chobot P, Gumprecht J, Klupa T, Mysliwiec M, Szadkowska A, Bomba-Opon D, Czajkowski K, Malecki MT, Zozulinska-Ziolkiewicz DA. Ambulatory Glucose Profile (AGP) Report in Daily Care of Patients with Diabetes: Practical Tips and Recommendations. Diabetes Ther 2022; 13:811-821. [PMID: 35278195 PMCID: PMC8991298 DOI: 10.1007/s13300-022-01229-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 02/08/2022] [Indexed: 12/01/2022] Open
Abstract
The ambulatory glucose profile (AGP) is now established as the standardised, practical one-page report for graphically presenting a summary of glycaemic control status in patients with diabetes who use continuous glucose monitoring (CGM) systems as part of their daily diabetes care. The AGP report provides both a visual and a statistical summary of the glucose metrics that, as agreed in the 2019 international consensus for assessing glycaemic control, should be analysed in all people with diabetes who are using CGM systems. The AGP report can be analysed in a systematic fashion to understand current glycaemic control and to monitor, in real time, the impact of adjustments to therapy in both type 1 diabetes and type 2 diabetes. Here we provide a practical guide to the glycaemic measures that are summarised in the AGP Report and illustrate the essential components of an AGP review in a series of hypothetical, real-world, patient-centred case studies (see Supplementary Materials).
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Affiliation(s)
- Leszek Czupryniak
- Department of Diabetology and Internal Medicine, Medical University of Warsaw, Warsaw, Poland
| | - Grzegorz Dzida
- Department of Internal Diseases, Medical University of Lublin, Lublin, Poland
| | - Piotr Fichna
- Department of Pediatric Diabetes, Auxology and Obesity, Poznan University of Medical Sciences, Poznan, Poland
| | | | - Janusz Gumprecht
- Department of Internal Medicine, Diabetology and Nephrology, Medical University of Silesia, Katowice, Poland
| | - Tomasz Klupa
- Department of Metabolic Diseases, Jagiellonian University Medical College, Krakow, Poland
| | - Malgorzata Mysliwiec
- Department of Pediatrics, Diabetology and Endocrinology, Medical University of Gdansk, Gdansk, Poland
| | - Agnieszka Szadkowska
- Department of Pediatrics, Diabetology, Endocrinology and Nephrology, Medical University of Lodz, Lodz, Poland
| | - Dorota Bomba-Opon
- 1st Department of Obstetrics and Gynecology, Medical University of Warsaw, Warsaw, Poland
| | - Krzysztof Czajkowski
- 2nd Department of Obstetrics and Gynecology, Medical University of Warsaw, Warsaw, Poland
| | - Maciej T Malecki
- Department of Metabolic Diseases, Jagiellonian University Medical College, Krakow, Poland
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90
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Kurozumi A, Okada Y, Mita T, Wakasugi S, Katakami N, Yoshii H, Kanda K, Nishida K, Mine S, Tanaka Y, Gosho M, Shimomura I, Watada H. Associations between continuous glucose monitoring-derived metrics and HbA1c in patients with type 2 diabetes mellitus. Diabetes Res Clin Pract 2022; 186:109836. [PMID: 35314256 DOI: 10.1016/j.diabres.2022.109836] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Revised: 03/10/2022] [Accepted: 03/16/2022] [Indexed: 12/20/2022]
Abstract
AIMS The aim of this study was to define the relationship between time in range (TIR) and hemoglobin A1c (HbA1c) levels in patients with type 2 diabetes mellitus (T2DM). METHODS The glycemic profile of 999 Japanese patients was analyzed with FreeStyle Libre Pro Continuous Glucose Monitoring (FLP-CGM) while they continued their prescribed glucose-lowering medications. FLP-CGM data recorded over 8 consecutive days were analyzed. RESULTS The regression model for HbA1c on TIR was HbA1c = 9.4966-0.0309 × TIR. The predicted HbA1c level for TIR of 70% was 7.33% and is higher than reports subjecting mostly T1DM. The TIR corresponding to HbA1c 7.0% was 80.64%. The patients with low TIR tended to have long duration of diabetes, used high dose of daily insulin, high body mass index, high HbA1c, liver dysfunction and high triglyceride. Relatively higher percentages of patients of this group used sulfonylureas, glucagon like peptide-1 receptor agonists and insulin. CONCLUSIONS Our data showed predicted HbA1c corresponding to TIR is largely depends on study population, thus is not uniform. Our results provide new insights on the management of T2DM. However, caution should be exercised in extending the HbA1C-TIR relationship using FLP-CGM to any other sensors since there could be a risk of hypoglycemia in doing so.
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Affiliation(s)
- Akira Kurozumi
- First Department of Internal Medicine, School of Medicine, University of Occupational and Environmental Health, Japan, 1-1 Iseigaoka, Yahatanishi-ku, Kitakyushu 807-8555, Japan
| | - Yosuke Okada
- First Department of Internal Medicine, School of Medicine, University of Occupational and Environmental Health, Japan, 1-1 Iseigaoka, Yahatanishi-ku, Kitakyushu 807-8555, Japan; Clinical Research Center, Hospital of the University of Occupational and Environmental Health, Japan, 1-1 Iseigaoka, Yahatanishi-ku, Kitakyushu 807-8555, Japan.
| | - Tomoya Mita
- Department of Metabolism & Endocrinology, Juntendo University Graduate School of Medicine, 2-1-1 Bunkyo-ku, Tokyo, Japan.
| | - Satomi Wakasugi
- Department of Metabolism & Endocrinology, Juntendo University Graduate School of Medicine, 2-1-1 Bunkyo-ku, Tokyo, Japan
| | - Naoto Katakami
- Department of Metabolic Medicine, Osaka University Graduate School of Medicine, 2-2, Yamadaoka, Suita, Osaka, Japan; Department of Metabolism and Atherosclerosis, Osaka University Graduate School of Medicine, 2-2, Yamadaoka, Suita, Osaka 565-0871, Japan
| | - Hidenori Yoshii
- Department of Medicine, Diabetology & Endocrinology, Juntendo Tokyo Koto Geriatric Medical Center, Shinsuna 3-3-20, Koto-ku, Tokyo 136-0075, Japan
| | - Kazuko Kanda
- Tobata General Hospital, 1-3-33, Fukuryugi, Tobata-ku, Kitakyushu 804-0025, Japan
| | - Keiko Nishida
- Nishida Keiko Diabetes Clinic, 1-3-26, Mitsusadadai, Yahatanishi-ku, Kitakyushu 807-0805, Japan
| | - Shinichiro Mine
- Sasaki Hospital, 9-36, Kisshoujimachi, Yahatanishi-ku, Kitakyushu 807-1114, Japan
| | - Yoshiya Tanaka
- First Department of Internal Medicine, School of Medicine, University of Occupational and Environmental Health, Japan, 1-1 Iseigaoka, Yahatanishi-ku, Kitakyushu 807-8555, Japan
| | - Masahiko Gosho
- Department of Biostatistics, Faculty of Medicine, University of Tsukuba, 1-1-1, Tennodai, Tsukuba, Ibaraki 305-8575, Japan
| | - Iichiro Shimomura
- Department of Metabolic Medicine, Osaka University Graduate School of Medicine, 2-2, Yamadaoka, Suita, Osaka, Japan
| | - Hirotaka Watada
- Department of Metabolism & Endocrinology, Juntendo University Graduate School of Medicine, 2-1-1 Bunkyo-ku, Tokyo, Japan
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91
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Abstract
The goal of diabetes treatment is to maintain good glycemic control, prevent the development and progression of diabetic complications, and ensure the same quality of life and life expectancy as healthy people. Hemoglobin A1c (HbA1c) is used as an index of glycemic control, but strict glycemic control using HbA1c as an index may lead to severe hypoglycemia and cardiovascular death. Glycemic variability (GV), such as excessive hyperglycemia and hypoglycemia, is associated with diabetic vascular complications and has been recognized as an important index of glycemic control. Here, we reviewed the definition and evaluated the clinical usefulness of GV, and its relationship with diabetic complications and therapeutic strategies to reduce GV.
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Affiliation(s)
- Yoshiki Kusunoki
- Department of Diabetes, Endocrinology and Clinical Immunology, Hyogo College of Medicine, Japan
| | - Kosuke Konishi
- Department of Diabetes, Endocrinology and Clinical Immunology, Hyogo College of Medicine, Japan
| | - Taku Tsunoda
- Department of Diabetes, Endocrinology and Clinical Immunology, Hyogo College of Medicine, Japan
| | - Hidenori Koyama
- Department of Diabetes, Endocrinology and Clinical Immunology, Hyogo College of Medicine, Japan
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92
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Xie P, Deng B, Zhang X, Li Y, Du C, Rui S, Deng W, Boey J, Armstrong DG, Ma Y, Deng W. Time in range in relation to amputation and all-cause mortality in hospitalised patients with diabetic foot ulcers. Diabetes Metab Res Rev 2022; 38:e3498. [PMID: 34587332 DOI: 10.1002/dmrr.3498] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 09/13/2021] [Indexed: 12/16/2022]
Abstract
AIMS The aim of this study was to evaluate the association of time in range (TIR) with amputation and all-cause mortality in hospitalised patients with diabetic foot ulcers (DFUs). MATERIALS AND METHODS A retrospective analysis was performed on 303 hospitalised patients with DFUs. During hospitalisation, TIR, mean blood glucose (MBG), coefficient of variation (CV), time above range (TAR) and time below range (TBR) of patients were determined from seven-point blood glucose profiles. Participants were grouped based on their clinical outcomes (i.e., amputation and death). Logistic regression was employed to analyse the association of TIR with amputation and all-cause mortality of inpatients with DFUs. RESULTS Among the 303 enrolled patients, 50 (16.5%) had undergone amputation whereas seven (2.3%) were deceased. Blood glucose was determined in 41,012 samples obtained from all participants. Patients who underwent amputation had significantly lower TIR and higher MBG, CV, level 2 TAR and level 1 TBR whereas deceased patients had significantly lower TIR and higher MBG and level 2 TAR. Both amputation and all-cause mortality rate declined with an increase in TIR quartiles. Logistic regression showed association of TIR with amputation (p = 0.034) and all-cause mortality (p = 0.013) after controlling for 15 confounders. This association was similarly significant in all-cause mortality after further adjustment for CV (p = 0.022) and level 1 TBR (p = 0.021), respectively. CONCLUSIONS TIR is inversely associated with amputation and all-cause mortality of hospitalised patients with DFUs. Further prospective studies are warranted to establish a causal relationship between TIR and clinical outcomes in patients with DFUs.
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Affiliation(s)
- Puguang Xie
- Department of Endocrinology, College of Medicine, College of Bioengineering, Chongqing Emergency Medical Center, Chongqing University Central Hospital, Chongqing University, Chongqing, China
| | - Bo Deng
- Department of Endocrinology, College of Medicine, College of Bioengineering, Chongqing Emergency Medical Center, Chongqing University Central Hospital, Chongqing University, Chongqing, China
| | - Xi Zhang
- Department of Endocrinology, College of Medicine, College of Bioengineering, Chongqing Emergency Medical Center, Chongqing University Central Hospital, Chongqing University, Chongqing, China
| | - Yuyao Li
- Department of Endocrinology, College of Medicine, College of Bioengineering, Chongqing Emergency Medical Center, Chongqing University Central Hospital, Chongqing University, Chongqing, China
| | - Chenzhen Du
- Department of Endocrinology, College of Medicine, College of Bioengineering, Chongqing Emergency Medical Center, Chongqing University Central Hospital, Chongqing University, Chongqing, China
| | - Shunli Rui
- Department of Endocrinology, College of Medicine, College of Bioengineering, Chongqing Emergency Medical Center, Chongqing University Central Hospital, Chongqing University, Chongqing, China
| | - Wu Deng
- College of Electronic Information and Automation, Civil Aviation University of China, Tianjin, China
| | - Johnson Boey
- Department of Podiatry, National University Hospital, Singapore
| | - David G Armstrong
- Department of Surgery, Keck School of Medicine of University of Southern California, Los Angeles, California, USA
| | - Yu Ma
- Department of Endocrinology, College of Medicine, College of Bioengineering, Chongqing Emergency Medical Center, Chongqing University Central Hospital, Chongqing University, Chongqing, China
| | - Wuquan Deng
- Department of Endocrinology, College of Medicine, College of Bioengineering, Chongqing Emergency Medical Center, Chongqing University Central Hospital, Chongqing University, Chongqing, China
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93
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Glennie JL, Berard L, Levrat-Guillen F. Sensor-Based Technology: Bringing Value to People with Diabetes and the Healthcare System in an Evolving World. Clinicoecon Outcomes Res 2022; 14:75-90. [PMID: 35177913 PMCID: PMC8843785 DOI: 10.2147/ceor.s346736] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Accepted: 01/15/2022] [Indexed: 02/06/2023]
Affiliation(s)
| | - Lori Berard
- Nurse Consultant, Pink Pearls Inc, Winnipeg, Manitoba, Canada
| | - Fleur Levrat-Guillen
- Abbott Diabetes Care, Maidenhead, UK
- Correspondence: Fleur Levrat-Guillen, Abbott Laboratories Ltd, Abbott House, Vanwall Business Park, Maidenhead, Berkshire, SL6 4XE, UK, Tel +44 7584108032, Email
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94
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El Malahi A, Van Elsen M, Charleer S, Dirinck E, Ledeganck K, Keymeulen B, Crenier L, Radermecker R, Taes Y, Vercammen C, Nobels F, Mathieu C, Gillard P, De Block C. Relationship Between Time in Range, Glycemic Variability, HbA1c, and Complications in Adults With Type 1 Diabetes Mellitus. J Clin Endocrinol Metab 2022; 107:e570-e581. [PMID: 34534297 DOI: 10.1210/clinem/dgab688] [Citation(s) in RCA: 45] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Indexed: 11/19/2022]
Abstract
PURPOSE Real-time continuous glucose monitoring (RT-CGM) provides information on glycemic variability (GV), time in range (TIR), and guidance to avoid hypoglycemia, thereby complimenting HbA1c for diabetes management. We investigated whether GV and TIR were independently associated with chronic and acute diabetes complications. METHODS Between September 2014 and January 2017, 515 subjects with type 1 diabetes using sensor-augmented pump therapy were followed for 24 months. The link between baseline HbA1c and CGM-derived glucometrics (TIR [70-180 mg/dL], coefficient of variation [CV], and SD) obtained from the first 2 weeks of RT-CGM use and the presence of complications was investigated. Complications were defined as: composite microvascular complications (presence of neuropathy, retinopathy, or nephropathy), macrovascular complications, and hospitalization for hypoglycemia and/or ketoacidosis. RESULTS Individuals with microvascular complications were older (P < 0.001), had a longer diabetes duration (P < 0.001), a higher HbA1c (7.8 ± 0.9 vs 7.5 ± 0.9%, P < 0.001), and spent less time in range (60.4 ± 12.2 vs 63.9 ± 13.8%, P = 0.022) compared with those without microvascular complication. Diabetes duration (odds ratio [OR] = 1.12 [1.09-1.15], P < 0.001) and TIR (OR = 0.97 [0.95-0.99], P = 0.005) were independent risk factors for composite microvascular complications, whereas SD and CV were not. Age (OR = 1.08 [1.03-1.14], P = 0.003) and HbA1c (OR = 1.80 [1.02-3.14], P = 0.044) were risk factors for macrovascular complications. TIR (OR = 0.97 [0.95-0.99], P = 0.021) was the only independent risk factor for hospitalizations for hypoglycemia or ketoacidosis. CONCLUSIONS Lower TIR was associated with the presence of composite microvascular complications and with hospitalization for hypoglycemia or ketoacidosis. TIR, SD, and CV were not associated with macrovascular complications.
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Affiliation(s)
- Anass El Malahi
- Endocrinology-Diabetology, University Hospital Antwerp, 2650 Edegem, Belgium
| | - Michiel Van Elsen
- Endocrinology-Diabetology, University Hospital Antwerp, 2650 Edegem, Belgium
| | - Sara Charleer
- Endocrinology, University Hospitals Leuven - KU Leuven, 3000 Leuven, Belgium
| | - Eveline Dirinck
- Endocrinology-Diabetology, University Hospital Antwerp, 2650 Edegem, Belgium
- Laboratorium of Experimental Medicine and Pediatrics and member of the Infla-Med Centre of Excellence, University of Antwerp, Faculty of Medicine & Health Sciences, 2610 Antwerp, Belgium
| | - Kristien Ledeganck
- Laboratorium of Experimental Medicine and Pediatrics and member of the Infla-Med Centre of Excellence, University of Antwerp, Faculty of Medicine & Health Sciences, 2610 Antwerp, Belgium
| | - Bart Keymeulen
- Diabetology, University Hospital Brussels, 1090 Brussels, Belgium
| | - Laurent Crenier
- Endocrinology, Université Libre de Bruxelles - Hôpital Erasme, 1070 Brussels, Belgium
| | - Régis Radermecker
- Diabetes, Nutrition and Metabolic disorders, CHU Liège, Clinical Pharmacology, Liège University, 4000 Liège, Belgium
| | - Youri Taes
- Endocrinology, AZ Sint-Jan Brugge, 8000 Bruges, Belgium
| | | | - Frank Nobels
- Endocrinology, OLV Hospital Aalst, 9300 Aalst, Belgium
| | - Chantal Mathieu
- Endocrinology, University Hospitals Leuven - KU Leuven, 3000 Leuven, Belgium
| | - Pieter Gillard
- Endocrinology, University Hospitals Leuven - KU Leuven, 3000 Leuven, Belgium
| | - Christophe De Block
- Endocrinology-Diabetology, University Hospital Antwerp, 2650 Edegem, Belgium
- Laboratorium of Experimental Medicine and Pediatrics and member of the Infla-Med Centre of Excellence, University of Antwerp, Faculty of Medicine & Health Sciences, 2610 Antwerp, Belgium
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95
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Lu J, Pan Y, Tu Y, Zhang P, Zhou J, Yu H. Contribution of glycemic variability to hypoglycemia, and a new marker for diabetes remission after Roux-en-Y Gastric bypass surgery. Surg Obes Relat Dis 2022; 18:666-673. [DOI: 10.1016/j.soard.2022.01.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 12/01/2021] [Accepted: 01/12/2022] [Indexed: 11/26/2022]
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96
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Aleppo G, Bode B, Carlson AL. Can Faster Aspart Be Used to Optimize Glycemic Control With Insulin Pump Therapy? From Expectations to Lessons Learned After a Year of Use in the United States. Clin Diabetes 2022; 40:413-424. [PMID: 36381308 PMCID: PMC9606564 DOI: 10.2337/cd21-0056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Fast-acting insulin aspart (faster aspart) is an ultra-rapid-acting formulation of insulin aspart developed to more closely match the prandial endogenous insulin profile, and its accelerated absorption kinetics are expected to provide clinical benefits for patients using insulin pump therapy. A head-to-head trial versus the original insulin aspart formulation in pump therapy did not demonstrate superiority of faster aspart in terms of A1C reduction, but pump settings were not optimized for the pharmacokinetic/pharmacodynamic profile of faster aspart. Nevertheless, meal test and continuous glucose monitoring data suggest that faster aspart is beneficial for postprandial glucose control, and a case study is presented illustrating excellent results using this insulin in pump therapy. Frequent blood glucose monitoring and appropriate patient education are vital for success.
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Affiliation(s)
- Grazia Aleppo
- Division of Endocrinology, Metabolism and Molecular Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
- Corresponding author: Grazia Aleppo,
| | - Bruce Bode
- Atlanta Diabetes Associates, Atlanta, GA
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97
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Doupis J, Horton ES. Utilizing the New Glucometrics: A Practical Guide to Ambulatory Glucose Profile Interpretation. Endocrinology 2022; 18:20-26. [PMID: 35949362 PMCID: PMC9354515 DOI: 10.17925/ee.2022.18.1.20] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 05/03/2022] [Indexed: 11/24/2022]
Abstract
Traditional continuous glucose monitoring and flash glucose monitoring systems are proven to lower glycated haemoglobin levels, decrease the time and impact of hypoglycaemia or hyperglycaemia and, consequently, improve the quality of life for children and adults with type 1 diabetes mellitus (T1DM) and adults with type 2 diabetes mellitus (T2DM). These glucose-sensing devices can generate large amounts of glucose data that can be used to define a detailed glycaemic profile for each user, which can be compared with targets for glucose control set by an International Consensus Panel of diabetes experts. Targets have been agreed upon for adults, children and adolescents with T1DM and adults with T2DM; separate targets have been agreed upon for older adults with diabetes, who are at higher risk of hypoglycaemia, and women with pregestational T1DM during pregnancy. Along with the objective measures and targets identified by the International Consensus Panel, the dense glucose data delivered by traditional continuous glucose monitoring and flash glucose monitoring systems is used to generate an ambulatory glucose profile, which summarizes the data in a visually impactful format that can be used to identify patterns and trends in daily glucose control, including those that raise clinical concerns. In this article, we provide a practical guide on how to interpret these new glucometrics using a straightforward algorithm, and clear visual examples that demystify the process of reviewing the glycaemic health of people with T1DM or T2DM such that forward-looking goals for diabetes management can be agreed.
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Affiliation(s)
- John Doupis
- Department of Internal Medicine and Diabetes, Salamis Naval and Veterans Hospital, Salamis, Attiki, Greece
- Iatriko Paleou Falirou Medical Center, Diabetes Clinic, Athens, Greece
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98
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Zhou H, Wang W, Shen Q, Feng Z, Zhang Z, Lei H, Yang X, Liu J, Lu B, Shao J, Gu P. Time in range, assessed with continuous glucose monitoring, is associated with brachial-ankle pulse wave velocity in type 2 diabetes: A retrospective single-center analysis. Front Endocrinol (Lausanne) 2022; 13:1014568. [PMID: 36325447 PMCID: PMC9618671 DOI: 10.3389/fendo.2022.1014568] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 09/22/2022] [Indexed: 11/17/2022] Open
Abstract
AIMS The aim of this retrospective single-center is to research the relationship between time in range(TIR), an important novel metric of glycemic control, assessed with continuous glucose monitoring(CGM) and brachial-ankle pulse wave velocity(BaPWV), a unique index of systemic arterial stiffness in type 2 diabetes. METHODS Study participants included 469 hospitalized patients with type 2 diabetes and no history of serious cardiovascular disease who underwent CGM and BaPWV measurements. TIR of 3.9-10.0 mmol/L was evaluated with CGM. BaPWV was measured by non-invasive arteriosclerosis detector and high baPWV was defined as a mean baPWV≧1800m/s. The spearman correlation and the partial correlation analysis were applied to analyze the correlation between TIR and baPWV. The binary logistic regression was used to examine the independent association of TIR and high BaPWV. RESULTS The presence of high baPWV was 32.2%. Compared with patients of low baPWV, those with high baPWV had significantly reduced TIR(P<0.001). With the increase of TIR tertiles, the prevalence of high BaPWV progressively decreased. Correlation analysis showed that TIR is inversely correlated with BaPWV. In a fully adjusted model controlling for traditional risk factor of CVD, TIR is associated with the presence of high BaPWV independent of HbA1c. CONCLUSION TIR is correlated with BaPWV independent of HbA1c in patients with type 2 diabetes, confirming a link between TIR and arterial stiffness.
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Affiliation(s)
- Hui Zhou
- Department of Endocrinology, Jinling Hospital, Southern Medical University, Nanjing, China
| | - Wei Wang
- Department of Endocrinology, Jinling Hospital, School of Medicine, Nanjing University, Nanjing, China
| | - Qiuyue Shen
- Department of Endocrinology, Jinling Hospital, School of Medicine, Nanjing University, Nanjing, China
| | - Zhouqin Feng
- Department of Endocrinology, Jinling Hospital, Southern Medical University, Nanjing, China
| | - Zhen Zhang
- Department of Endocrinology, Jinling Hospital, Southern Medical University, Nanjing, China
| | - Haiyan Lei
- Department of Endocrinology, Jinling Hospital, Southern Medical University, Nanjing, China
| | - Xinyi Yang
- Department of Endocrinology, Jinling Hospital, School of Medicine, Nanjing University, Nanjing, China
| | - Jun Liu
- Department of Endocrinology, Jinling Hospital, Nanjing Medical University, Nanjing, China
| | - Bin Lu
- Department of Endocrinology, Jinling Hospital, School of Medicine, Nanjing University, Nanjing, China
| | - Jiaqing Shao
- Department of Endocrinology, Jinling Hospital, Southern Medical University, Nanjing, China
- *Correspondence: Jiaqing Shao, ;Ping Gu,
| | - Ping Gu
- Department of Endocrinology, Jinling Hospital, School of Medicine, Nanjing University, Nanjing, China
- *Correspondence: Jiaqing Shao, ;Ping Gu,
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Ceriello A, Prattichizzo F, Phillip M, Hirsch IB, Mathieu C, Battelino T. Glycaemic management in diabetes: old and new approaches. Lancet Diabetes Endocrinol 2022; 10:75-84. [PMID: 34793722 DOI: 10.1016/s2213-8587(21)00245-x] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 08/13/2021] [Accepted: 08/20/2021] [Indexed: 12/12/2022]
Abstract
HbA1c is the most used parameter to assess glycaemic control. However, evidence suggests that the concept of hyperglycaemia has profoundly changed and that different facets of hyperglycaemia must be considered. A modern approach to glycaemic control should focus not only on reaching and maintaining optimal HbA1c concentrations as early as possible, but to also do so by reducing postprandial hyperglycaemia, glycaemic variability, and to extend as much as possible the time in range in near-normoglycaemia. These goals should be achieved while avoiding hypoglycaemia, which, should it occur, should be reverted to normoglycaemia. Modern technology, such as intermittently scanned glucose monitoring and continuous glucose monitoring, together with new drug therapies (eg, ultra-fast insulins, SGLT2 inhibitors, and GLP-1 receptor agonists), could help to change the landscape of glycaemia management based on HbA1c in favour of a more holistic approach that considers all the different aspects of this commonly oversimplified pathophysiological feature of diabetes.
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Affiliation(s)
| | | | - Moshe Phillip
- Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel; Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel
| | - Irl B Hirsch
- University of Washington School of Medicine, Seattle, WA, USA
| | - Chantal Mathieu
- Department of Endocrinology, UZ Gasthuisberg KU Leuven, Leuven, Belgium
| | - Tadej Battelino
- University Medical Center Ljubljana, University Children's Hospital, Ljubljana, Slovenia; Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
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100
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Aleppo G, Beck RW, Bailey R, Ruedy KJ, Calhoun P, Peters AL, Pop-Busui R, Philis-Tsimikas A, Bao S, Umpierrez G, Davis G, Kruger D, Bhargava A, Young L, Buse JB, McGill JB, Martens T, Nguyen QT, Orozco I, Biggs W, Lucas KJ, Polonsky WH, Price D, Bergenstal RM. The Effect of Discontinuing Continuous Glucose Monitoring in Adults With Type 2 Diabetes Treated With Basal Insulin. Diabetes Care 2021; 44:2729-2737. [PMID: 34588210 PMCID: PMC8669539 DOI: 10.2337/dc21-1304] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Accepted: 09/07/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To explore the effect of discontinuing continuous glucose monitoring (CGM) after 8 months of CGM use in adults with type 2 diabetes treated with basal without bolus insulin. RESEARCH DESIGN AND METHODS This multicenter trial had an initial randomization to either real-time CGM or blood glucose monitoring (BGM) for 8 months followed by 6 months in which the BGM group continued to use BGM (n = 57) and the CGM group was randomly reassigned either to continue CGM (n = 53) or discontinue CGM with resumption of BGM for glucose monitoring (n = 53). RESULTS In the group that discontinued CGM, mean time in range (TIR) 70-180 mg/dL, which improved from 38% before initiating CGM to 62% after 8 months of CGM, decreased after discontinuing CGM to 50% at 14 months (mean change from 8 to 14 months -12% [95% CI -21% to -3%], P = 0.01). In the group that continued CGM use, little change was found in TIR from 8 to 14 months (baseline 44%, 8 months 56%, 14 months 57%, mean change from 8 to 14 months 1% [95% CI -11% to 12%], P = 0.89). Comparing the two groups at 14 months, the adjusted treatment group difference in mean TIR was -6% (95% CI -16% to 4%, P = 0.20). CONCLUSIONS In adults with type 2 diabetes treated with basal insulin who had been using real-time CGM for 8 months, discontinuing CGM resulted in a loss of about one-half of the initial gain in TIR that had been achieved during CGM use.
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Affiliation(s)
- Grazia Aleppo
- Feinberg School of Medicine, Northwestern University, Chicago, IL
| | - Roy W Beck
- Jaeb Center for Health Research, Tampa, FL
| | | | | | | | - Anne L Peters
- Keck School of Medicine of the University of Southern California, Los Angeles, CA
| | | | | | - Shichun Bao
- Vanderbilt University Medical Center, Nashville, TN
| | | | | | | | | | - Laura Young
- University of North Carolina School of Medicine, Chapel Hill, NC
| | - John B Buse
- University of North Carolina School of Medicine, Chapel Hill, NC
| | | | - Thomas Martens
- International Diabetes Center, Park Nicollet Internal Medicine, Minneapolis, MN
| | | | - Ian Orozco
- Carteret Medical Group, Morehead City, NC
| | | | - K Jean Lucas
- Diabetes and Endocrinology Consultants, PC, Morehead City, NC
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