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Kulzer B, Freckmann G, Ziegler R, Schnell O, Glatzer T, Heinemann L. Nocturnal Hypoglycemia in the Era of Continuous Glucose Monitoring. J Diabetes Sci Technol 2024; 18:1052-1060. [PMID: 39158988 DOI: 10.1177/19322968241267823] [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] [Indexed: 08/21/2024]
Abstract
Nocturnal hypoglycemia is a common acute complication of people with diabetes on insulin therapy. In particular, the inability to control glucose levels during sleep, the impact of external factors such as exercise, or alcohol and the influence of hormones are the main causes. Nocturnal hypoglycemia has several negative somatic, psychological, and social effects for people with diabetes, which are summarized in this article. With the advent of continuous glucose monitoring (CGM), it has been shown that the number of nocturnal hypoglycemic events was significantly underestimated when traditional blood glucose monitoring was used. The CGM can reduce the number of nocturnal hypoglycemia episodes with the help of alarms, trend arrows, and evaluation routines. In combination with CGM with an insulin pump and an algorithm, automatic glucose adjustment (AID) systems have their particular strength in nocturnal glucose regulation and the prevention of nocturnal hypoglycemia. Nevertheless, the problem of nocturnal hypoglycemia has not yet been solved completely with the technologies currently available. The CGM systems that use predictive models to warn of hypoglycemia, improved AID systems that recognize hypoglycemia patterns even better, and the increasing integration of artificial intelligence methods are promising approaches in the future to significantly minimize the risk of a side effect of insulin therapy that is burdensome for people with diabetes.
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Affiliation(s)
- Bernhard Kulzer
- Research Institute Diabetes Academy Mergentheim, Bad Mergentheim, Germany
- Diabetes Center Mergentheim, Bad Mergentheim, Germany
- Department of Clinical Psychology and Psychotherapy, University of Bamberg, Bamberg, Germany
| | - Guido Freckmann
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Ralph Ziegler
- Diabetes Clinic for Children and Adolescents, Muenster, Germany
| | - Oliver Schnell
- Forschergruppe Diabetes e.V., Helmholtz Zentrum, Munich, Germany
| | | | - Lutz Heinemann
- Science Consulting in Diabetes GmbH, Düsseldorf, Germany
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Molavizadeh D, Cheraghloo N, Tohidi M, Azizi F, Hadaegh F. The association between index-year, average, and variability of the triglyceride-glucose index with health outcomes: more than a decade of follow-up in Tehran lipid and glucose study. Cardiovasc Diabetol 2024; 23:321. [PMID: 39217401 PMCID: PMC11365227 DOI: 10.1186/s12933-024-02387-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2024] [Accepted: 08/01/2024] [Indexed: 09/04/2024] Open
Abstract
BACKGROUND The association between baseline triglyceride glucose index (TyG index) and incident non-communicable diseases, mainly in Asian populations, has been reported. In the current study, we aimed to evaluate the association between index-year, average, and visit-to-visit variability (VVV) of the TyG index with incident type 2 diabetes mellitus (T2DM), hypertension, cardiovascular disease (CVD), and all-cause mortality among the Iranian population. METHODS The study population included 5220 participants (2195 men) aged ≥ 30 years. TyG index was calculated as Ln (fasting triglycerides (mg/dL) × fasting plasma glucose (mg/dL)/2). Average values of the TyG index and also VVV (assessed by the standard deviation (SD) and variability independent of mean) were derived during the exposure period from 2002 to 2011 (index-year). Multivariable Cox proportional hazards regression models were used to estimate the hazard ratio (HR) and 95% confidence interval (CI) of the TyG index for incident different health outcomes. RESULTS During more than 6 years of follow-up after the index year, 290, 560, 361, and 280 events of T2DM, hypertension, CVD, and all-cause mortality occurred. 1-SD increase in the TyG index values at the index-year was independently associated with the incident T2DM [HR (95% CI) 2.50 (2.13-2.93)]; the corresponding values for the average of TyG index were 2.37 (2.03-2.76), 1.12 (0.99-1.26, pvalue = 0.05), 1.18 (1.01-1.36), and 1.29 (1.08-1.53) for incident T2DM, hypertension, CVD, and all-cause mortality, respectively. Compared to the first tertile, tertile 3 of VVV of the TyG index was independently associated with incident hypertension [1.33 (1.07-1.64), Ptrend <0.01]. Likewise, a 1-SD increase in VVV of the TyG index was associated with an 11% excess risk of incident hypertension [1.11 (1.02-1.21)]. However, no association was found between the VVV of the TyG index and other outcomes. Moreover, the impact of index-year and average values of the TyG index was more prominent among women regarding incident CVD (P for interactions < 0.05). CONCLUSION Although the higher TyG index at index-year and its VVV were only associated with the incident T2DM and hypertension, respectively, its average value was capable of capturing the risk for all of the health outcomes.
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Affiliation(s)
- Danial Molavizadeh
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19395-4763, Tehran, Islamic Republic of Iran
- School of Medicine, Kashan University of Medical Sciences, Kashan, Islamic Republic of Iran
| | - Neda Cheraghloo
- Department of Epidemiology and Biostatistics, School of Public Health, Tehran University of Medical Science, Tehran, Islamic Republic of Iran
| | - Maryam Tohidi
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19395-4763, Tehran, Islamic Republic of Iran
| | - Fereidoun Azizi
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Islamic Republic of Iran
| | - Farzad Hadaegh
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, P.O. Box 19395-4763, Tehran, Islamic Republic of Iran.
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Chen B, Shen C, Sun B. Current landscape and comprehensive management of glycemic variability in diabetic retinopathy. J Transl Med 2024; 22:700. [PMID: 39075573 PMCID: PMC11287919 DOI: 10.1186/s12967-024-05516-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2024] [Accepted: 07/18/2024] [Indexed: 07/31/2024] Open
Abstract
Diabetic retinopathy (DR), a well-known microvascular complication of diabetes mellitus, remains the main cause of vision loss in working-age adults worldwide. Up to now, there is a shortage of information in the study regarding the contributing factors of DR in diabetes. Accumulating evidence has identified glycemic variability (GV), referred to fluctuations of blood glucose levels, as a risk factor for diabetes-related complications. Recent reports demonstrate that GV plays an important role in accounting for the susceptibility to DR development. However, its exact role in the pathogenesis of DR is still not fully understood. In this review, we highlight the current landscape and relevant mechanisms of GV in DR, as well as address the mechanism-based therapeutic strategies, aiming at better improving the quality of DR management in clinical practice.
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Affiliation(s)
- Bo Chen
- Department of Pharmacy, The Central Hospital of Yongzhou, Yongzhou, China
| | - Chaozan Shen
- Department of Clinical Pharmacy, The Second People's Hospital of Huaihua, Lulin Road, Huaihua, Hunan, 418000, China.
| | - Bao Sun
- Department of Pharmacy, The Second Xiangya Hospital, Central South University, No.139 Middle Renmin Road, Changsha, Hunan, 410011, China.
- Institute of Clinical Pharmacy, Central South University, Changsha, China.
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Salinero-Fort MA, San Andrés-Rebollo FJ, Cárdenas-Valladolid J, Mostaza J, Lahoz C, Rodriguez-Artalejo F, Gómez-Campelo P, Vich-Pérez P, Jiménez-García R, de-Miguel-Yanes JM, Maroto-Rodriguez J, Taulero-Escalera B, Campo VI. Effect of glucose variability on the mortality of adults aged 75 years and over during the first year of the COVID-19 pandemic. BMC Geriatr 2024; 24:533. [PMID: 38902647 PMCID: PMC11188234 DOI: 10.1186/s12877-024-05149-0] [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: 10/05/2023] [Accepted: 06/13/2024] [Indexed: 06/22/2024] Open
Abstract
BACKGROUND To our knowledge, only one study has examined the association between glucose variability (GV) and mortality in the elderly population with diabetes. GV was assessed by HbA1c, and a J-shaped curve was observed in the relationship between HbA1c thresholds and mortality. No study of GV was conducted during the COVID-19 pandemic and its lockdown. This study aims to evaluate whether GV is an independent predictor of all-cause mortality in patients aged 75 years or older with and without COVID-19 who were followed during the first year of the COVID-19 pandemic and its lockdown measures. METHODS This was a retrospective cohort study of 407,492 patients from the AGED-MADRID dataset aged 83.5 (SD 5.8) years; 63.2% were women, and 29.3% had diabetes. GV was measured by the coefficient of variation of fasting plasma glucose (CV-FPG) over 6 years of follow-up (2015-2020). The outcome measure was all-cause mortality in 2020. Four models of logistic regression were performed, from simple (age, sex) to fully adjusted, to assess the effect of CV-FPG on all-cause mortality. RESULTS During follow-up, 34,925 patients died (14,999 women and 19,926 men), with an all-cause mortality rate of 822.3 per 10,000 person-years (95% confidence interval (CI), 813.7 to 822.3) (739 per 10,000; 95% CI 728.7 to 739.0 in women and 967.1 per 10,000; 95% CI 951.7 to 967.2 in men). The highest quartile of CV-FPG was significantly more common in the deceased group (40.1% vs. 23.6%; p < 0.001). In the fully adjusted model including dementia (Alzheimer's disease) and basal FPG, the odds ratio for mortality ranged from 1.88 to 2.06 in patients with T2DM and from 2.30 to 2.61 in patients with normoglycaemia, according to different sensitivity analyses. CONCLUSIONS GV has clear implications for clinical practice, as its assessment as a risk prediction tool should be included in the routine follow-up of the elderly and in a comprehensive geriatric assessment. Electronic health records can incorporate tools that allow its calculation, and with this information, clinicians will have a broader view of the medium- and long-term prognosis of their patients.
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Affiliation(s)
- Miguel A Salinero-Fort
- Department of Health, Foundation for Biosanitary Research and Innovation in Primary Care, The Hospital La Paz Institute for Health Research (IdiPAZ), Alfonso X El Sabio University, Research Network On Chronicity, Primary Care and Health Promotion -RICAPPS-(RICORS), General Subdirectorate of Research and Documentation, Madrid, Spain.
- Subdirección General de Investigación Sanitaria, Consejería de Sanidad, Madrid, Spain.
| | - F Javier San Andrés-Rebollo
- Foundation for Biosanitary Research and Innovation in Primary Care, Las Calesas Health Center, Madrid, Spain
| | - Juan Cárdenas-Valladolid
- Foundation for Biosanitary Research and Innovation in Primary Care, Information Systems Department, Primary Health Care Management of Madrid, Alfonso X El Sabio University, The Hospital La Paz Institute for Health Research (IdiPAZ), Madrid, Spain
| | - José Mostaza
- Lipids and Vascular Risk Unit, Internal Medicine, University Hospital La Paz-Cantoblanco-Carlos III, The Hospital La Paz Institute for Health Research (IdiPAZ), Madrid, Spain
| | - Carlos Lahoz
- Lipids and Vascular Risk Unit, Internal Medicine, University Hospital La Paz-Cantoblanco-Carlos III, The Hospital La Paz Institute for Health Research (IdiPAZ), Madrid, Spain
| | - Fernando Rodriguez-Artalejo
- Department of Preventive Medicine and Public Health, Universidad Autónoma de Madrid-IdIPAZ, CIBERESP (CIBER of Epidemiology and Public Health), and IMDEA-Food Institute, CEI UAM+CSIC, Madrid, Spain
| | - Paloma Gómez-Campelo
- Foundation for Biomedical Research of La Paz University Hospital (FIBHULP), The Hospital La Paz Institute for Health Research (IdiPAZ), Madrid, Spain
| | - Pilar Vich-Pérez
- Foundation for Biosanitary Research and Innovation in Primary Care, Los Alpes Health Center, Madrid, Spain
| | - Rodrigo Jiménez-García
- Department of Public Health & Maternal and Child Health, Faculty of Medicine, Universidad Complutense de Madrid, Madrid, 28040, Spain
| | - José M de-Miguel-Yanes
- School of Medicine, Internal Medicine Department, Complutense University of Madrid, Gregorio Marañón General University Hospital, Gregorio Marañón Health Research Institute (IiSGM), Madrid, Spain
| | - Javier Maroto-Rodriguez
- Department of Preventive Medicine and Public Health, School of Medicine, Universidad Autónoma de Madrid, Calle del Arzobispo Morcillo 4, Madrid, 28029, Spain
| | | | - Víctor Iriarte Campo
- Foundation for Biosanitary Research and Innovation in Primary Care, Madrid, Spain
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Kamaraj N, Velumani K, Guru A, Issac PK. Antihyperglycemic activity of 14-deoxy, 11, 12-didehydro andrographolide on streptozotocin-nicotinamide induced type 2 diabetic rats. Mol Biol Rep 2023; 50:9875-9886. [PMID: 37856062 DOI: 10.1007/s11033-023-08878-4] [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: 05/30/2023] [Accepted: 10/02/2023] [Indexed: 10/20/2023]
Abstract
BACKGROUND Diabetic Mellitus is characterized by a lack or failure of insulin to bind to its target receptor or failure of the pancreas to yield insulin. This study evaluated the antihyperglycemic activity of 14-deoxy, 11, 12-didehydro andrographolide on streptozotocin-nicotinamide-induced type 2 diabetic rats. Diabetic conditions were induced by administering streptozotocin at a dosage of 45 mg/kg body weight and nicotinamide at a dosage of 110 mg/kg body weight through intraperitoneal injection. MATERIALS AND METHODS Diabetic-induced rats were treated with 14-deoxy, 11, 12-didehydro andrographolide concentrations between 10 and 500 mg/kg body weight. The blood glucose level and body weight of the rats were periodically examined. The pancreas was isolated and the histopathological staining was performed after making fine sections of the pancreas using a microtome. The influence of 14-deoxy, 11, 12-didehydro andrographolide on the expression level of various insulin signaling cascades was determined with q-PCR and western blotting. RESULTS The blood glucose level of the diabetic-induced rats was significantly (p < 0.05) higher when compared with the control group and resulted in a drop in the blood glucose level of the diabetic rats. Oral glucose level was also reduced in the treatment group and no significant reduction was noted in the untreated. The lipid profiling revealed that the atherogenic index and cholesterol ratio was increased in the diabetic group over the control group. Upregulation of the insulin cascades like IRTK and GLUT4 was observed by the q-PCR and upregulation of GLUT4 and IR-β was observed by the western blot analysis. CONCLUSION Overall, the finding indicates that 14-deoxy, 11, 12-didehydro andrographolide exhibited antihyperglycemic activity by modulating the expression of insulin cascades.
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Affiliation(s)
- Nagalakshmi Kamaraj
- Department of Biotechnology, Karpaga Vinayaga College of Engineering and Technology, Padalam, Chengalpattu, Tamil Nadu, 603308, India
| | - Kadhirmathiyan Velumani
- Institute of Biotechnology, Department of Medical Biotechnology and Integrative Physiology, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Thandalam, Chennai, 602105, Tamil Nadu, India
| | - Ajay Guru
- Department of Cariology, Saveetha Dental College and Hospitals, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, India.
| | - Praveen Kumar Issac
- Institute of Biotechnology, Department of Medical Biotechnology and Integrative Physiology, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Thandalam, Chennai, 602105, Tamil Nadu, India.
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Diao T, Liu K, Wang Q, Lyu J, Zhou L, Yuan Y, Wang H, Yang H, Wu T, Zhang X. Bedtime, sleep pattern, and incident cardiovascular disease in middle-aged and older Chinese adults: The dongfeng-tongji cohort study. Sleep Med 2023; 110:82-88. [PMID: 37544277 DOI: 10.1016/j.sleep.2023.08.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 07/12/2023] [Accepted: 08/01/2023] [Indexed: 08/08/2023]
Abstract
OBJECTIVES To investigate the associations of bedtime and a low-risk sleep pattern with incident cardiovascular disease (CVD). METHODS A total of 31,500 retirees were included from the Dongfeng-Tongji cohort in 2008-2010 and 2013. Sleep information was collected by questionnaires. CVD events were identified through the health care system until December 31, 2018. Cox proportional hazards regression models were performed to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). RESULTS During an average follow-up of 7.2 years, 8324 cases of incident CVD, including 6557 coronary heart disease (CHD) and 1767 stroke, were documented. U-shaped associations of bedtime with the risks of incident CVD and stroke were observed. Compared with bedtime between 10:01 p.m.-11:00 p.m., the HR (95% CI) for CVD was 1.10 (1.01-1.20) for ≤9:00 p.m., 1.07 (1.01-1.13) for 9:01 p.m.-10:00 p.m., and 1.32 (1.11-1.58) for >12:00 a.m., respectively, mainly driven by stroke risk (22%, 14%, and 70% higher for ≤9:00 p.m., 9:01 p.m.-10:00 p.m., and >12:00 a.m., respectively). The number of low-risk sleep factors, namely bedtime between 10:01 p.m.-12:00 a.m., sleep duration of 7-< 8 h/night, good/fair sleep quality, and midday napping ≤60 min, exhibited dose-dependent relationships with CVD, CHD, and stroke risks. Participants with 4 low-risk sleep factors had a respective 24%, 21%, and 30% lower risk of CVD, CHD, and stroke than those with 0-1 low-risk sleep factor. CONCLUSIONS Individuals with early or late bedtimes had a higher CVD risk, especially stroke. Having low-risk sleep habits is associated with lower CVD risks.
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Affiliation(s)
- Tingyue Diao
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kang Liu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; School of Public Health, Guangzhou Medical University, Guangzhou, China
| | - Qiuhong Wang
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Junrui Lyu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lue Zhou
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yu Yuan
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hao Wang
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Handong Yang
- Department of Cardiovascular Diseases, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan, China
| | - Tangchun Wu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
| | - Xiaomin Zhang
- Department of Occupational and Environmental Health, Key Laboratory of Environment and Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Fang Q, Shi J, Zhang J, Peng Y, Liu C, Wei X, Hu Z, Sun L, Hong J, Gu W, Wang W, Zhang Y. Visit-to-visit HbA1c variability is associated with aortic stiffness progression in participants with type 2 diabetes. Cardiovasc Diabetol 2023; 22:167. [PMID: 37415203 PMCID: PMC10324236 DOI: 10.1186/s12933-023-01884-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Accepted: 06/11/2023] [Indexed: 07/08/2023] Open
Abstract
BACKGROUND Glycemic variability plays an important role in the development of cardiovascular disease (CVD). This study aims to determine whether long-term visit-to-visit glycemic variability is associated with aortic stiffness progression in participants with type 2 diabetes (T2D). METHODS Prospective data were obtained from 2115 T2D participants in the National Metabolic Management Center (MMC) from June 2017 to December 2022. Two brachial-ankle pulse wave velocity (ba-PWV) measurements were performed to assess aortic stiffness over a mean follow-up period of 2.6 years. A multivariate latent class growth mixed model was applied to identify trajectories of blood glucose. Logistic regression models were used to determine the odds ratio (OR) for aortic stiffness associated with glycemic variability evaluated by the coefficient of variation (CV), variability independent of the mean (VIM), average real variability (ARV), and successive variation (SV) of blood glucose. RESULTS Four distinct trajectories of glycated hemoglobin (HbA1c) or fasting blood glucose (FBG) were identified. In the U-shape class of HbA1c and FBG, the adjusted ORs were 2.17 and 1.21 for having increased/persistently high ba-PWV, respectively. Additionally, HbA1c variability (CV, VIM, SV) was significantly associated with aortic stiffness progression, with ORs ranging from 1.20 to 1.24. Cross-tabulation analysis indicated that the third tertile of the HbA1c mean and VIM conferred a 78% (95% confidence interval [CI] 1.23-2.58) higher odds of aortic stiffness progression. Sensitivity analysis demonstrated that the SD of HbA1c and the highest HbA1c variability score (HVS) were significantly associated with the adverse outcomes independent of the mean of HbA1c during the follow-up. CONCLUSIONS Long-term visit-to-visit HbA1c variability was independently associated with aortic stiffness progression, suggesting that HbA1c variability was a strong predictor of subclinical atherosclerosis in T2D participants.
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Affiliation(s)
- Qianhua Fang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 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 Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 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, 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 Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jia Zhang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 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 Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ying Peng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 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 Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Cong Liu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 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 Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xing Wei
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 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 Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhuomeng Hu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 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 Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Lin Sun
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 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 Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 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, 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 Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weiqiong Gu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 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 Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 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, 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 Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Yifei Zhang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 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 Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Deravi N, Sharifi Y, Koohi F, Zadeh SST, Masrouri S, Azizi F, Hadaegh F. The association between fasting plasma glucose variability and incident eGFR decline: evidence from two cohort studies. BMC Public Health 2023; 23:565. [PMID: 36973769 PMCID: PMC10041700 DOI: 10.1186/s12889-023-15463-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 03/17/2023] [Indexed: 03/29/2023] Open
Abstract
BACKGROUND Glycemic variability (GV) is developing as a marker of glycemic control, which can be utilized as a promising predictor of complications. To determine whether long-term GV is associated with incident eGFR decline in two cohorts of Tehran Lipid and Glucose Study (TLGS) and Multi-Ethnic Study of Atherosclerosis (MESA) during a median follow-up of 12.2 years. METHODS Study participants included 4422 Iranian adults (including 528 patients with T2D) aged ≥ 20 years from TLGS and 4290 American adults (including 521 patients with T2D) aged ≥ 45 years from MESA. The Multivariate Cox proportional hazard models were used to assess the risk of incident eGFR decline for each of the fasting plasma glucose (FPG) variability measures including standard deviation (SD), coefficient of variation (CV), average real variability (ARV), and variability independent of the mean (VIM) both as continuous and categorical variables. The time of start for eGFR decline and FPG variability assessment was the same, but the event cases were excluded during the exposure period. RESULTS In TLGS participants without T2D, for each unit change in FPG variability measures, the hazards (HRs) and 95% confidence intervals (CI) for eGFR decline ≥ 40% of SD, CV, and VIM were 1.07(1.01-1.13), 1.06(1.01-1.11), and 1.07(1.01-1.13), respectively. Moreover, the third tertile of FPG-SD and FPG-VIM parameters was significantly associated with a 60 and 69% higher risk for eGFR decline ≥ 40%, respectively. In MESA participants with T2D, each unit change in FPG variability measures was significantly associated with a higher risk for eGFR decline ≥ 40%.Regarding eGFR decline ≥ 30% as the outcome, in the TLGS, regardless of diabetes status, no association was shown between FPG variability measures and risk of eGFR decline in any of the models; however, in the MESA the results were in line with those of GFR decline ≥ 40%.Using pooled data from the two cohorts we found that generally FPG variability were associated with higher risk of eGFR decline ≥ 40% only among non-T2D individuals. CONCLUSIONS Higher FPG variability was associated with an increased risk of eGFR decline in the diabetic American population; however, this unfavorable impact was found only among the non-diabetic Iranian population.
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Affiliation(s)
- Niloofar Deravi
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, No. 24, Parvaneh Street, Velenjak, Tehran, 19395-4763, Iran
- Student Research Committee, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Yasaman Sharifi
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, No. 24, Parvaneh Street, Velenjak, Tehran, 19395-4763, Iran
- Department of Radiology, School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Koohi
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, No. 24, Parvaneh Street, Velenjak, Tehran, 19395-4763, Iran
| | - Seyed Saeed Tamehri Zadeh
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, No. 24, Parvaneh Street, Velenjak, Tehran, 19395-4763, Iran
| | - Soroush Masrouri
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, No. 24, Parvaneh Street, Velenjak, Tehran, 19395-4763, Iran
| | - Fereidoun Azizi
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Farzad Hadaegh
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, No. 24, Parvaneh Street, Velenjak, Tehran, 19395-4763, Iran.
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Fu L, Tai S, Sun J, Zhang N, Zhou Y, Xing Z, Wang Y, Zhou S. Remnant Cholesterol and Its Visit-to-Visit Variability Predict Cardiovascular Outcomes in Patients With Type 2 Diabetes: Findings From the ACCORD Cohort. Diabetes Care 2022; 45:2136-2143. [PMID: 35834242 PMCID: PMC9472497 DOI: 10.2337/dc21-2511] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Accepted: 05/31/2022] [Indexed: 02/03/2023]
Abstract
OBJECTIVE Remnant cholesterol (remnant-C) predicts atherosclerotic cardiovascular disease, regardless of LDL-cholesterol (LDL-C) levels. This study assessed the associations between remnant-C and cardiovascular outcomes in type 2 diabetes. RESEARCH DESIGN AND METHODS This post hoc analysis of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial used patient (type 2 diabetes >3 months) remnant-C and major adverse cardiovascular event (MACE) data from the study database. The associations between remnant-C and MACEs were evaluated using Cox proportional hazards regression analyses. We examined the relative MACE risk in remnant-C versus LDL-C discordant/concordant groups using clinically relevant LDL-C targets by discordance analyses. RESULTS The baseline analysis included 10,196 participants, with further visit-to-visit variability analysis including 9,650 participants. During follow-up (median, 8.8 years), 1,815 patients (17.8%) developed MACEs. After adjusting for traditional cardiovascular risk factors, each 1-SD increase in remnant-C was associated with a 7% higher MACE risk (hazard ratio [HR] 1.07, 95% CI 1.02-1.12, P = 0.004). In the fully adjusted model, the visit-to-visit remnant-C variability calculated using logSD (HR 1.41, 95% CI 1.18-1.69, P < 0.001) and logARV (HR 1.45, 95% CI 1.22-1.73, P < 0.001) was associated with MACEs. Residual lipid risk (remnant-C ≥31 mg/dL) recognized individuals at a higher MACE risk, regardless of LDL-C concentrations. Within each LDL-C subgroup (>100 or ≤100 mg/dL), high baseline remnant-C was associated with a higher MACE risk (HR 1.37, 95% CI 1.09-1.73, P = 0.007; HR 1.22, 95% CI 1.04-1.41, P = 0.015, respectively). CONCLUSIONS Remnant-C levels were associated with MACEs in patients with type 2 diabetes independent of LDL-C, and visit-to-visit remnant-C variability helped identify those with higher cardiovascular risk.
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Affiliation(s)
- Liyao Fu
- Department of Blood Transfusion, The Second Xiangya Hospital of Central South University, Changsha, China.,Department of Cardiovascular Medicine, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Shi Tai
- Department of Cardiovascular Medicine, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Jiaxing Sun
- Department of Cardiovascular Medicine, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Ningjie Zhang
- Department of Blood Transfusion, The Second Xiangya Hospital of Central South University, Changsha, China.,Department of Cardiovascular Medicine, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Ying Zhou
- Department of Blood Transfusion, The Second Xiangya Hospital of Central South University, Changsha, China.,Department of Cardiovascular Medicine, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Zhenhua Xing
- Department of Cardiovascular Medicine, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Yongjun Wang
- Department of Blood Transfusion, The Second Xiangya Hospital of Central South University, Changsha, China
| | - Shenghua Zhou
- Department of Cardiovascular Medicine, The Second Xiangya Hospital of Central South University, Changsha, China
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10
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Long C, Tang Y, Huang J, Liu S, Xing Z. Association of long-term visit-to-visit variability of HbA1c and fasting glycemia with hypoglycemia in type 2 diabetes mellitus. Front Endocrinol (Lausanne) 2022; 13:975468. [PMID: 36034445 PMCID: PMC9402888 DOI: 10.3389/fendo.2022.975468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 07/21/2022] [Indexed: 11/14/2022] Open
Abstract
Background Self-management of blood glucose levels to avoid hypoglycemia is vital for patients with type 2 diabetes mellitus (T2DM). The association between specific metrics of glycemic variability (glycosylated hemoglobin A1c [HbA1c] and fasting plasma glucose [FPG]) and severe hypoglycemia has not been fully studied in patients with T2DM. Methods In this post hoc analysis, patients with established T2DM with a high risk of cardiovascular disease were included in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) study. The Cox proportional hazards model was used to investigate the relationship between glycemic variability and hypoglycemia requiring medical assistance (HMA) and hypoglycemia requiring any third-party assistance (HAA). The prognostic value of HbA1c/FPG variability for our predefined outcomes was compared using Harrell's C method. Results After adjusting for confounders, each increase in HbA1c variability of 1 standard deviation (SD) indicated a higher risk of HAA (hazard ratio [HR]: 1.10; 95% confidence interval [CI]: 1.03-1.16; P < 0.01) and HMA events (HR: 1.11; 95% CI: 1.03-1.20; P < 0.01). Meanwhile, each increase in FPG variability of 1 SD increased the risk of HAA (HR: 1.40; 95% CI: 1.31-1.49; P < 0.01) and HMA events (HR: 1.46; 95% CI: 1.35-1.57; P < 0.01). Meanwhile, models, including FPG variability, had better prognostic value for our predefined outcomes than HbA1c variability (P < 0.01). Conclusions Increased visit-to-visit variability in HbA1c and fasting glycemia is associated with a greater risk of severe hypoglycemic events in T2DM patients. FPG variability is a more sensitive indicator than HbA1c variability. Trial registration http://www.clinicaltrials.gov. Unique identifier: NCT00000620.
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Affiliation(s)
- Chen Long
- Department of General Surgery, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yaling Tang
- Department of General Surgery, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Jiangsheng Huang
- Department of General Surgery, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Suo Liu
- Department of Cardiothoracic Surgery, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Zhenhua Xing
- Department of Emergency Medicine, The Second Xiangya Hospital, Central South University, Changsha, China
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11
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Andersen A, Bagger JI, Sørensen SK, Baldassarre MPA, Pedersen-Bjergaard U, Forman JL, Gislason G, Lindhardt TB, Knop FK, Vilsbøll T. Associations of hypoglycemia, glycemic variability and risk of cardiac arrhythmias in insulin-treated patients with type 2 diabetes: a prospective, observational study. Cardiovasc Diabetol 2021; 20:241. [PMID: 34952579 PMCID: PMC8710000 DOI: 10.1186/s12933-021-01425-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 12/03/2021] [Indexed: 12/20/2022] Open
Abstract
Background Insulin-treated patients with type 2 diabetes (T2D) are at risk of hypoglycemia, which is associated with an increased risk of cardiovascular disease and mortality. Using a long-term monitoring approach, we investigated the association between episodes of hypoglycemia, glycemic variability and cardiac arrhythmias in a real-life setting. Methods Insulin-treated patients with T2D (N = 21, [mean ± SD] age 66.8 ± 9.6 years, BMI 30.1 ± 4.5 kg/m2, HbA1c 6.8 ± 0.4% [51.0 ± 4.8 mmol/mol]) were included for a one-year observational study. Patients were monitored with continuous glucose monitoring ([mean ± SD] 118 ± 6 days) and an implantable cardiac monitor (ICM) during the study period. Results Time spend in hypoglycemia was higher during nighttime than during daytime ([median and interquartile range] 0.7% [0.7–2.7] vs. 0.4% [0.2–0.8]). The ICMs detected 724 episodes of potentially clinically significant arrhythmias in 12 (57%) participants, with atrial fibrillation and pauses accounting for 99% of the episodes. No association between hypoglycemia and cardiac arrhythmia was found during daytime. During nighttime, subject-specific hourly incidence of cardiac arrhythmias tended to increase with the occurrence of hypoglycemia (incident rate ratio [IRR] 1.70 [95% CI 0.36–8.01]) but only slightly with increasing time in hypoglycemia (IRR 1.04 [95% CI 0.89–1.22] per 5 min). Subject-specific incidence of cardiac arrhythmias during nighttime increased with increasing glycemic variability as estimated by coefficient of variation whereas it decreased during daytime (IRR 1.33 [95% CI 1.05–1.67] and IRR 0.77 [95% CI 0.59–0.99] per 5% absolute increase, respectively). Conclusions Cardiac arrhythmias were common in insulin-treated patients with T2D and were associated with glycemic variability, whereas arrhythmias were not strongly associated with hypoglycemia. Trial registration: NCT03150030, ClinicalTrials.gov, registered May 11, 2017. https://clinicaltrials.gov/ct2/show/NCT03150030 Supplementary Information The online version contains supplementary material available at 10.1186/s12933-021-01425-0.
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Affiliation(s)
- Andreas Andersen
- Clinical Research, Steno Diabetes Center Copenhagen, University of Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark.,Center for Clinical Metabolic Research, Herlev and Gentofte Hospital, University of Copenhagen, Hellerup, Denmark
| | - Jonatan I Bagger
- Clinical Research, Steno Diabetes Center Copenhagen, University of Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark.,Center for Clinical Metabolic Research, Herlev and Gentofte Hospital, University of Copenhagen, Hellerup, Denmark
| | - Samuel K Sørensen
- Department of Cardiology, Herlev and Gentofte Hospital, University of Copenhagen, Hellerup, Denmark
| | - Maria P A Baldassarre
- Center for Clinical Metabolic Research, Herlev and Gentofte Hospital, University of Copenhagen, Hellerup, Denmark.,Department of Medicine and Aging Sciences, G. d'Annunzio University, Chieti, Italy
| | - Ulrik Pedersen-Bjergaard
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.,Department of Endocrinology and Nephrology, Nordsjællands Hospital Hillerød, University of Copenhagen, Hillerød, Denmark
| | - Julie L Forman
- Deparment of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Gunnar Gislason
- Department of Cardiology, Herlev and Gentofte Hospital, University of Copenhagen, Hellerup, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.,The Danish Heart Foundation, Copenhagen, Denmark
| | - Tommi B Lindhardt
- Department of Cardiology, Herlev and Gentofte Hospital, University of Copenhagen, Hellerup, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Filip K Knop
- Clinical Research, Steno Diabetes Center Copenhagen, University of Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark.,Center for Clinical Metabolic Research, Herlev and Gentofte Hospital, University of Copenhagen, Hellerup, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.,Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Tina Vilsbøll
- Clinical Research, Steno Diabetes Center Copenhagen, University of Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark. .,Center for Clinical Metabolic Research, Herlev and Gentofte Hospital, University of Copenhagen, Hellerup, Denmark. .,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
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