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Ajjan RA, Battelino T, Cos X, Del Prato S, Philips JC, Meyer L, Seufert J, Seidu S. Continuous glucose monitoring for the routine care of type 2 diabetes mellitus. Nat Rev Endocrinol 2024; 20:426-440. [PMID: 38589493 DOI: 10.1038/s41574-024-00973-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/29/2024] [Indexed: 04/10/2024]
Abstract
Although continuous glucose monitoring (CGM) devices are now considered the standard of care for people with type 1 diabetes mellitus, the uptake among people with type 2 diabetes mellitus (T2DM) has been slower and is focused on those receiving intensive insulin therapy. However, increasing evidence now supports the inclusion of CGM in the routine care of people with T2DM who are on basal insulin-only regimens or are managed with other medications. Expanding CGM to these groups could minimize hypoglycaemia while allowing efficient adaptation and escalation of therapies. Increasing evidence from randomized controlled trials and observational studies indicates that CGM is of clinical value in people with T2DM on non-intensive treatment regimens. If further studies confirm this finding, CGM could soon become a part of routine care for T2DM. In this Perspective we explore the potential benefits of widening the application of CGM in T2DM, along with the challenges that must be overcome for the evidence-based benefits of this technology to be delivered for all people with T2DM.
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Affiliation(s)
- Ramzi A Ajjan
- The LIGHT Laboratories, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK
| | - Tadej Battelino
- Faculty of Medicine, University of Ljubljana Medical Centre, Ljubljana, Slovenia
| | - Xavier Cos
- DAP Cat Research Group, Foundation University Institute for Primary Health Care Research Jordi Gol i Gorina, Barcelona, Spain
| | - Stefano Del Prato
- Section of Diabetes and Metabolic Diseases, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | | | - Laurent Meyer
- Department of Endocrinology, Diabetes and Nutrition, University Hospital, Strasbourg, France
| | - Jochen Seufert
- Division of Endocrinology and Diabetology, Department of Medicine II, Medical Centre, University of Freiburg, Freiburg, Germany
| | - Samuel Seidu
- Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, UK.
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Atmaca A, Ketenci A, Sahin I, Sengun IS, Oner RI, Erdem Tilki H, Adas M, Soyleli H, Demir T. Expert opinion on screening, diagnosis and management of diabetic peripheral neuropathy: a multidisciplinary approach. Front Endocrinol (Lausanne) 2024; 15:1380929. [PMID: 38952393 PMCID: PMC11215140 DOI: 10.3389/fendo.2024.1380929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 05/15/2024] [Indexed: 07/03/2024] Open
Abstract
The proposed expert opinion aimed to address the current knowledge on conceptual, clinical, and therapeutic aspects of diabetic peripheral neuropathy (DPN) and to provide a guidance document to assist clinicians for the best practice in DPN care. The participating experts consider the suspicion of the disease by clinicians as a key factor in early recognition and diagnosis, emphasizing an improved awareness of the disease by the first-admission or referring physicians. The proposed "screening and diagnostic" algorithm involves the consideration of DPN in a patient with prediabetes or diabetes who presents with neuropathic symptoms and/or signs of neuropathy in the presence of DPN risk factors, with careful consideration of laboratory testing to rule out other causes of distal symmetric peripheral neuropathy and referral for a detailed neurological work-up for a confirmative test of either small or large nerve fiber dysfunction in atypical cases. Although, the first-line interventions for DPN are currently represented by optimized glycemic control (mainly for type 1 diabetes) and multifactorial intervention (mainly for type 2 diabetes), there is a need for individualized pathogenesis-directed treatment approaches for DPN. Alpha-lipoic acid (ALA) seems to be an important first-line pathogenesis-directed agent, given that it is a direct and indirect antioxidant that works with a strategy targeted directly against reactive oxygen species and indirectly in favor of endogenous antioxidant capacity for improving DPN conditions. There is still a gap in existing research in the field, necessitating well-designed, robust, multicenter clinical trials with sensitive endpoints and standardized protocols to facilitate the diagnosis of DPN via a simple and effective algorithm and to track progression of disease and treatment response. Identification of biomarkers/predictors that would allow an individualized approach from a potentially disease-modifying perspective may provide opportunities for novel treatments that would be efficacious in early stages of DPN, and may modify the natural course of the disease. This expert opinion document is expected to increase awareness among physicians about conceptual, clinical, and therapeutic aspects of DPN and to assist them in timely recognition of DPN and translating this information into their clinical practice for best practice in the management of patients with DPN.
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Affiliation(s)
- Aysegul Atmaca
- Department of Endocrinology and Metabolism, Ondokuz Mayis University Faculty of Medicine, Samsun, Türkiye
| | - Aysegul Ketenci
- Department of Physical Medicine and Rehabilitation, Koc University Faculty of Medicine, Istanbul, Türkiye
| | - Ibrahim Sahin
- Department of Endocrinology and Metabolism, Inonu University Faculty of Medicine, Malatya, Türkiye
| | - Ihsan Sukru Sengun
- Department of Neurology, Dokuz Eylul University Faculty of Medicine, Izmir, Türkiye
| | - Ramazan Ilyas Oner
- Department of Internal Medicine, Adiyaman University Faculty of Medicine, Adiyaman, Türkiye
| | - Hacer Erdem Tilki
- Department of Neurology, Ondokuz Mayis University Faculty of Medicine, Samsun, Türkiye
| | - Mine Adas
- Department of Endocrinology, Prof. Dr. Cemil Tascioglu City Hospital, Istanbul, Türkiye
| | - Hatice Soyleli
- Department of Medical Affairs, Abdi Ibrahim Pharmaceuticals, Istanbul, Türkiye
| | - Tevfik Demir
- Department of Endocrinology and Metabolism, Dokuz Eylul University Faculty of Medicine, Izmir, Türkiye
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Morita M, Sada K, Hidaka S, Ogawa M, Shibata H. Glycemic variability is associated with sural nerve conduction velocity in outpatients with type 2 diabetes: Usefulness of a new point-of-care device for nerve conduction studies. J Diabetes Investig 2024. [PMID: 38685597 DOI: 10.1111/jdi.14211] [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: 12/20/2023] [Revised: 02/28/2024] [Accepted: 03/24/2024] [Indexed: 05/02/2024] Open
Abstract
AIMS/INTRODUCTION Although several studies have shown the association between continuous glucose monitoring (CGM)-derived glycemic variability (GV) and diabetic peripheral neuropathy, no studies have focused on outpatients or used NC-stat®/DPNCheck™, a new point-of-care device for nerve conduction study (NCS). We investigated the association between CGM-derived GV and NCS using DPNCheck™ in outpatients with type 2 diabetes, and further analyzed the difference in results between patients with and without well-controlled HbA1c levels. MATERIALS AND METHODS All outpatients with type 2 diabetes using the CGM device (FreeStyle Libre Pro®) between 2017 and 2022 were investigated. Sural nerve conduction was evaluated by sensory nerve action potential (SNAP) amplitude and sensory conduction velocity (SCV) using DPNCheck™. Associations of CGM-derived GV metrics with SNAP amplitude and SCV were investigated. RESULTS In total, 304 outpatients with type 2 diabetes were included. In a linear regression model, most CGM-derived GV metrics except for the mean amplitude of glucose excursion and low blood glucose index were significantly associated with SCV, but not with SNAP amplitude. The significant associations of most CGM-derived GV metrics with SCV remained after adjustment for possible confounding factors, but not after adjustment for glycated hemoglobin (HbA1c). Most CGM-derived GV metrics were significantly associated with SCV after adjustment for HbA1c in patients with a HbA1c ≤ 6.9%, but not in those with a HbA1c ≥ 7.0%. CONCLUSIONS In outpatients with type 2 diabetes, multiple CGM-derived GV metrics were significantly associated with SCV obtained by DPNCheck™. GV may have independent impacts on peripheral nerve function, particularly in patients with well-controlled HbA1c levels.
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Affiliation(s)
- Machiko Morita
- Department of Diabetes and Metabolism, Koseiren Tsurumi Hospital, Oita, Japan
- Department of Endocrinology, Metabolism, Rheumatology and Nephrology, Faculty of Medicine, Oita University, Oita, Japan
| | - Kentaro Sada
- Department of Diabetes and Metabolism, Koseiren Tsurumi Hospital, Oita, Japan
- Department of Endocrinology, Metabolism, Rheumatology and Nephrology, Faculty of Medicine, Oita University, Oita, Japan
| | - Shuji Hidaka
- Department of Diabetes and Metabolism, Koseiren Tsurumi Hospital, Oita, Japan
| | - Miki Ogawa
- Department of Diabetes and Metabolism, Koseiren Tsurumi Hospital, Oita, Japan
- Department of Endocrinology, Metabolism, Rheumatology and Nephrology, Faculty of Medicine, Oita University, Oita, Japan
| | - Hirotaka Shibata
- Department of Endocrinology, Metabolism, Rheumatology and Nephrology, Faculty of Medicine, Oita University, Oita, Japan
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Liu D, Zhang Y, Wu Q, Han R, Cheng D, Wu L, Guo J, Yu X, Ge W, Ni J, Li Y, Ma T, Fang Q, Wang Y, Zhao Y, Zhao Y, Sun B, Li H, Jia W. Exercise-induced improvement of glycemic fluctuation and its relationship with fat and muscle distribution in type 2 diabetes. J Diabetes 2024; 16:e13549. [PMID: 38584275 PMCID: PMC10999499 DOI: 10.1111/1753-0407.13549] [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: 09/11/2023] [Revised: 01/01/2024] [Accepted: 02/13/2024] [Indexed: 04/09/2024] Open
Abstract
AIMS Management of blood glucose fluctuation is essential for diabetes. Exercise is a key therapeutic strategy for diabetes patients, although little is known about determinants of glycemic response to exercise training. We aimed to investigate the effect of combined aerobic and resistance exercise training on blood glucose fluctuation in type 2 diabetes patients and explore the predictors of exercise-induced glycemic response. MATERIALS AND METHODS Fifty sedentary diabetes patients were randomly assigned to control or exercise group. Participants in the control group maintained sedentary lifestyle for 2 weeks, and those in the exercise group specifically performed combined exercise training for 1 week. All participants received dietary guidance based on a recommended diet chart. Glycemic fluctuation was measured by flash continuous glucose monitoring. Baseline fat and muscle distribution were accurately quantified through magnetic resonance imaging (MRI). RESULTS Combined exercise training decreased SD of sensor glucose (SDSG, exercise-pre vs exercise-post, mean 1.35 vs 1.10 mmol/L, p = .006) and coefficient of variation (CV, mean 20.25 vs 17.20%, p = .027). No significant change was observed in the control group. Stepwise multiple linear regression showed that baseline MRI-quantified fat and muscle distribution, including visceral fat area (β = -0.761, p = .001) and mid-thigh muscle area (β = 0.450, p = .027), were significantly independent predictors of SDSG change in the exercise group, as well as CV change. CONCLUSIONS Combined exercise training improved blood glucose fluctuation in diabetes patients. Baseline fat and muscle distribution were significant factors that influence glycemic response to exercise, providing new insights into personalized exercise intervention for diabetes.
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Affiliation(s)
- Dan Liu
- Department of Endocrinology and MetabolismShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes MellitusShanghaiChina
| | - Ying Zhang
- Department of Endocrinology and MetabolismShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes MellitusShanghaiChina
| | - Qian Wu
- Department of Endocrinology and MetabolismShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes MellitusShanghaiChina
| | - Rui Han
- Department of Endocrinology and MetabolismShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes MellitusShanghaiChina
| | - Di Cheng
- Department of Endocrinology and MetabolismShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes MellitusShanghaiChina
| | - Liang Wu
- Department of Endocrinology and MetabolismShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes MellitusShanghaiChina
| | - Jingyi Guo
- Clinical Research CenterShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Xiangtian Yu
- Clinical Research CenterShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Wenli Ge
- Department of Endocrinology and MetabolismShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes MellitusShanghaiChina
| | - Jiacheng Ni
- Department of Endocrinology and MetabolismShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes MellitusShanghaiChina
| | - Yaohui Li
- School of Sports Science and Physical EducationNanjing Normal UniversityNanjingChina
| | - Tianshu Ma
- Department of KinesiologyNanjing Sport InstituteNanjingChina
| | - Qichen Fang
- Department of Endocrinology and MetabolismShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes MellitusShanghaiChina
| | - Yufei Wang
- Department of Endocrinology and MetabolismShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes MellitusShanghaiChina
| | - Yan Zhao
- Department of Sports and Health ScienceNanjing Sport InstituteNanjingChina
| | - Yanan Zhao
- School of Sports Science and Physical EducationNanjing Normal UniversityNanjingChina
| | - Biao Sun
- Department of KinesiologyNanjing Sport InstituteNanjingChina
| | - Huating Li
- Department of Endocrinology and MetabolismShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes MellitusShanghaiChina
| | - Weiping Jia
- Department of Endocrinology and MetabolismShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes MellitusShanghaiChina
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Yu J, Cho J, Lee S. The era of continuous glucose monitoring and its expanded role in type 2 diabetes. J Diabetes Investig 2023; 14:841-843. [PMID: 37145998 PMCID: PMC10286781 DOI: 10.1111/jdi.14028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 04/24/2023] [Accepted: 04/26/2023] [Indexed: 05/07/2023] Open
Affiliation(s)
- Jin Yu
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of MedicineThe Catholic University of KoreaSeoulKorea
| | - Jae‐Hyoung Cho
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of MedicineThe Catholic University of KoreaSeoulKorea
- Department of Medical Informatics, College of MedicineThe Catholic University of KoreaSeoulKorea
| | - Seung‐Hwan Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul St. Mary's Hospital, College of MedicineThe Catholic University of KoreaSeoulKorea
- Department of Medical Informatics, College of MedicineThe Catholic University of KoreaSeoulKorea
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Cuevas H, Stuifbergen AK, Hilsabeck RC, Sales A, Wood S, Kim J. The role of cognitive rehabilitation in people with type 2 diabetes: A study protocol for a randomized controlled trial. PLoS One 2023; 18:e0285553. [PMID: 37186584 PMCID: PMC10184896 DOI: 10.1371/journal.pone.0285553] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2023] [Accepted: 04/25/2023] [Indexed: 05/17/2023] Open
Abstract
Today, the prevalence of cognitive dysfunction and the prevalence of diabetes are increasing. Research shows that diabetes increases cognitive impairment risk, and cognitive impairment makes diabetes self-management more challenging. Diabetes self-management, essential to good glycemic control, requires patients to assimilate knowledge about their complex disease and to engage in activities such as glucose self-monitoring and the management of their medications. To test a comprehensive cognitive rehabilitation intervention-the Memory, Attention, and Problem-Solving Skills for Persons with Diabetes (MAPSS-DM) program. Our central hypothesis is that participants who take part in the MAPSS-DM intervention will have improved memory and executive function, increased use of compensatory cognitive skills, and improved self-management. We will also explore the role of glucose variability in those changes. This is a randomized controlled trial. Sixty-six participants with cognitive concerns and type 2 diabetes will be assigned to either the full MAPSS-DM intervention or an active control. Participants will use continuous glucose monitoring pre- and post-intervention to identify changes in glycemic variability. All participants will also be evaluated systematically via questionnaires and neuropsychological tests at three timepoints: baseline, immediately post-intervention, and 3 months post-intervention. This study will fill an important gap by addressing cognitive function in the management of diabetes. Diabetes is related to accelerated cognitive aging, cognitive deficits are related to poorer self-management, and improvements in cognitive performance as a result of cognitive rehabilitation can translate into improved performance in everyday life and, potentially, diabetes self-management. The results of the proposed study will therefore potentially inform strategies to support cognitive function and diabetes self-management, as well as offer new mechanistic insights into cognitive function through the use of continuous glucose monitoring. Trial registration: This study has been registered at ClinicalTrials.gov (NCT04831775).
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Affiliation(s)
- Heather Cuevas
- School of Nursing, The University of Texas at Austin, Austin, Texas, United States of America
| | - Alexa K. Stuifbergen
- School of Nursing, The University of Texas at Austin, Austin, Texas, United States of America
| | - Robin C. Hilsabeck
- Department of Neurology, Dell Medical School, Austin, Texas, United States of America
| | - Adam Sales
- Mathematical Sciences, Worcester Polytechnic Institute, Worcester, Massachusetts, United States of America
| | - Shenell Wood
- School of Nursing, The University of Texas at Austin, Austin, Texas, United States of America
| | - Jeeyeon Kim
- School of Nursing, The University of Texas at Austin, Austin, Texas, United States of America
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Shi R, Feng L, Liu YM, Xu WB, Luo BB, Tang LT, Bi QY, Cao HY. Glycemic dispersion: a new index for screening high glycemic variability. Diabetol Metab Syndr 2023; 15:95. [PMID: 37158980 PMCID: PMC10169464 DOI: 10.1186/s13098-023-01077-y] [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: 01/04/2023] [Accepted: 05/01/2023] [Indexed: 05/10/2023] Open
Abstract
OBJECTIVE For patients with diabetes, high-frequency and -amplitude glycemic variability may be more harmful than continuous hyperglycemia; however, there is still a lack of screening indicators that can quickly and easily assess the level of glycemic variability. The aim of this study was to investigate whether the glycemic dispersion index is effective for screening high glycemic variability. METHODS A total of 170 diabetes patients hospitalized in the Sixth Affiliated Hospital of Kunming Medical University were included in this study. After admission, the fasting plasma glucose, 2-hour postprandial plasma glucose, and glycosylated hemoglobin A1c were measured. The peripheral capillary blood glucose was measured seven times in 24 h, before and after each of three meals and before bedtime. The standard deviation of the seven peripheral blood glucose values was calculated, and a standard deviation of > 2.0 was used as the threshold of high glycemic variability. The glycemic dispersion index was calculated and its diagnostic efficacy for high glycemic variability was determined by the Mann-Whitney U test, receiver operating characteristic (ROC) curve and, Pearson correlation analysis. RESULTS The glycemic dispersion index of patients with high glycemic variability was significantly higher than that of those with low glycemic variability (p < 0.01). The best cutoff value of the glycemic dispersion index for screening high glycemic variability was 4.21. The area under the curve (AUC) was 0.901 (95% CI: 0.856-0.945) and had a sensitivity of 0.781 and specificity of 0.905. It was correlated with the standard deviation of blood glucose values (r = 0.813, p < 0.01). CONCLUSIONS The glycemic dispersion index had good sensitivity and specificity for screening high glycemic variability. It was significantly associated with the standard deviation of blood glucose concentration and is simple and easy to calculate. It was an effective screening indicator of high glycemic variability.
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Affiliation(s)
- Rui Shi
- Department of Medical Laboratory, Sixth Affiliated Hospital of Kunming Medical University, Yunnan, China
| | - Lei Feng
- Department of Medical Laboratory, Sixth Affiliated Hospital of Kunming Medical University, Yunnan, China.
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, People's Republic of China.
| | - Yan-Mei Liu
- Department of Medical Laboratory, Sixth Affiliated Hospital of Kunming Medical University, Yunnan, China
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, People's Republic of China
| | - Wen-Bo Xu
- Department of Medical Laboratory, Sixth Affiliated Hospital of Kunming Medical University, Yunnan, China
| | - Bei-Bei Luo
- Department of Medical Laboratory, Sixth Affiliated Hospital of Kunming Medical University, Yunnan, China
- Department of Laboratory Medicine, The Sixth Affiliated Hospital of Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, People's Republic of China
| | - Ling-Tong Tang
- Department of Medical Laboratory, Sixth Affiliated Hospital of Kunming Medical University, Yunnan, China
| | - Qian-Ye Bi
- Center Blood Station of Yuxi, Yuxi, China
| | - Hui-Ying Cao
- Department of Medical Laboratory, Sixth Affiliated Hospital of Kunming Medical University, Yunnan, China
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Sartore G, Ragazzi E, Caprino R, Lapolla A. Long-term HbA1c variability and macro-/micro-vascular complications in type 2 diabetes mellitus: a meta-analysis update. Acta Diabetol 2023; 60:721-738. [PMID: 36715767 PMCID: PMC10148792 DOI: 10.1007/s00592-023-02037-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 01/17/2023] [Indexed: 01/31/2023]
Abstract
AIMS The aim of the present study was to evaluate, by means of a meta-analysis approach, whether new available data, appeared on qualified literature, can support the effectiveness of an association of HbA1c variability with the risk of macro- and/or micro-vascular complications in type 2 diabetes mellitus (T2DM). METHODS The meta-analysis was conducted according to PRISMA Statement guidelines and considered published studies on T2DM, presenting HbA1c variability as standard deviation (SD) or its derived coefficient of variation (CV). Literature search was performed on PubMed in the time range 2015-July 2022, with no restrictions of language. RESULTS Twenty-three selected studies fulfilled the aims of the present investigation. Overall, the analysis of the risk as hazard ratios (HR) indicated a significant association between the HbA1c variability, expressed either as SD or CV, and the complications, except for neuropathy. Macro-vascular complications were all significantly associated with HbA1c variability, with HR 1.40 (95%CI 1.31-1.50, p < 0.0001) for stroke, 1.30 (95%CI 1.25-1.36, p < 0.0001) for transient ischaemic attack/coronary heart disease/myocardial infarction, and 1.32 (95%CI 1.13-1.56, p = 0.0007) for peripheral arterial disease. Micro-vascular complications yielded HR 1.29 (95%CI 1.22-1.36, p < 0.0001) for nephropathy, 1.03 (95%CI 0.99-1.08, p = 0.14) for neuropathy, and 1.15 (95%CI 1.08-1.24, p < 0.0001) for retinopathy. For all-cause mortality, HR was 1.33 (95%CI 1.27-1.39, p < 0.0001), and for cardiovascular mortality 1.25 (95%CI 1.17-1.34, p < 0.0001). CONCLUSIONS Our meta-analysis on HbA1c variability performed on the most recent published data since 2015 indicates positive association between HbA1c variability and macro-/micro-vascular complications, as well as mortality events, in T2DM, suggesting that this long-term glycaemic parameter merits further attention as a predictive, independent risk factor for T2DM population.
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Affiliation(s)
- Giovanni Sartore
- Department of Medicine - DIMED, University of Padua, Padua, Italy
| | - Eugenio Ragazzi
- Department of Pharmaceutical and Pharmacological Sciences - DSF, University of Padua, Padua, Italy.
| | - Rosaria Caprino
- Department of Medicine - DIMED, University of Padua, Padua, Italy
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Gouveri E, Papanas N. The Emerging Role of Continuous Glucose Monitoring in the Management of Diabetic Peripheral Neuropathy: A Narrative Review. Diabetes Ther 2022; 13:931-952. [PMID: 35394566 PMCID: PMC9076783 DOI: 10.1007/s13300-022-01257-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 03/17/2022] [Indexed: 12/14/2022] Open
Abstract
The aim of this narrative review is to present data on the role of continuous glucose monitoring (CGM) in the management of peripheral diabetic neuropathy (DPN) among individuals with type 1 and type 2 diabetes mellitus. Adequate glycaemic control is crucial to prevent the development or progression of DPN. CGM systems are valuable tools for improving glycaemic control and reducing glycaemic variability (GV). Chronic hyperglycaemia is known to be a risk factor for the development of diabetic microvascular complications, including DPN. In addition, there is now evidence that GV, evaluated by mean amplitude of glycaemic excursions, may be a novel factor in the pathogenesis of diabetic complications. Increased GV appears to be an independent risk factor for DPN and correlates with painful neuropathy. Similarly, time-in-range correlates positively with peripheral nerve function and negatively with sudomotor dysfunction. However, relevant studies are rather limited in scope, and the vast majority are cross-sectional and use different methodologies for the assessment of DPN. Therefore, the causal relationship between CGM-derived data and the development of DPN cannot be firmly established at the present time. It also remains to be elucidated whether CGM measures can be considered the new therapeutic targets for DPN management.
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Affiliation(s)
| | - Nikolaos Papanas
- Diabetes Centre, Second Department of Internal Medicine, Democritus University of Thrace, 68132, Alexandroupolis, Greece.
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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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