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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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Sebastian-Valles F, Arranz Martin JA, Martínez-Alfonso J, Jiménez-Díaz J, Hernando Alday I, Navas Moreno V, Armenta Joya T, Fandiño García MDM, Román Gómez GL, Garai Hierro J, Lander Lobariñas LE, Martinez de Icaya P, Sampedro-Nuñez MA, Martínez-Vizcaíno V, Marazuela M. Effect of Christmas Holidays on Type 1 Diabetes Mellitus in Users of Glucose Flash Systems. Endocr Pract 2024; 30:372-379. [PMID: 38307457 DOI: 10.1016/j.eprac.2024.01.011] [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: 11/09/2023] [Revised: 01/19/2024] [Accepted: 01/24/2024] [Indexed: 02/04/2024]
Abstract
OBJECTIVE Christmas holidays can impact weight and glycemic control in type 2 diabetes, but their effect on type 1 diabetes (T1D) remains understudied. This study assessed how Christmas holidays affect individuals with T1D who use flash continuous glucose monitoring systems. METHODS This retrospective study involved 812 adults diagnosed with T1D recruited from 3 hospitals. Clinical, anthropometric, and socioeconomic data were collected. Glucose metrics from 14 days before January 1st, and before December 1st and February 1st as control periods, were recorded. Analyses adjusted for multiple variables were conducted to assess the holiday season's impact on glycemic control. RESULTS The average time in range during the holidays (60.0 ± 17.2%) was lower compared to December (61.9 ± 17.2%, P < .001) and February (61.7 ± 17.7%, P < .001). Time above range (TAR > 180 mg/dL) was higher during Christmas (35.8 ± 18.2%) compared to December (34.1 ± 18.3%, P < .001) and February (34.2 ± 18.4%, P < .001). Differences were also observed in TAR >250 mg/dL, coefficient of variation, and average glucose (P < .05). No differences were found in time below range or other metrics. Linear regression models showed that the holidays reduced time in range by 1.9% (β = -1.92, P = .005) and increased TAR >180 mg/dL by 1.8% (β = 1.75, P = .016). CONCLUSION Christmas holidays are associated with a mild and reversible deterioration in glucose metrics among individuals with T1D using flash continuous glucose monitoring, irrespective of additional influencing factors. These discoveries can be useful to advise individuals with diabetes during the festive season and to recognize potential biases within studies conducted during this timeframe.
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Affiliation(s)
- Fernando Sebastian-Valles
- Department of Endocrinology and Nutrition, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria de La Princesa, Universidad Autónoma de Madrid, Madrid, Spain.
| | - Jose A Arranz Martin
- Department of Endocrinology and Nutrition, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria de La Princesa, Universidad Autónoma de Madrid, Madrid, Spain
| | - Julia Martínez-Alfonso
- Department of Family and Community Medicine, Hospital La Princesa/Centro de Salud Daroca, Madrid, Spain
| | - Jessica Jiménez-Díaz
- Department of Endocrinology and Nutrition, Hospital Universitario Severo Ochoa, Leganés, Madrid, Spain
| | - Iñigo Hernando Alday
- Department of Endocrinology and Nutrition, Hospital Universitario Basurto, Bilbao, Spain
| | - Victor Navas Moreno
- Department of Endocrinology and Nutrition, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria de La Princesa, Universidad Autónoma de Madrid, Madrid, Spain
| | - Teresa Armenta Joya
- Department of Endocrinology and Nutrition, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria de La Princesa, Universidad Autónoma de Madrid, Madrid, Spain
| | | | - Gisela L Román Gómez
- Department of Endocrinology and Nutrition, Hospital Universitario Severo Ochoa, Leganés, Madrid, Spain
| | - Jon Garai Hierro
- Department of Endocrinology and Nutrition, Hospital Universitario Basurto, Bilbao, Spain
| | - Luis E Lander Lobariñas
- Department of Endocrinology and Nutrition, Hospital Universitario Severo Ochoa, Leganés, Madrid, Spain
| | | | - Miguel A Sampedro-Nuñez
- Department of Endocrinology and Nutrition, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria de La Princesa, Universidad Autónoma de Madrid, Madrid, Spain
| | - Vicente Martínez-Vizcaíno
- Health and Social Care Research Center, Universidad de Castilla-La Mancha, Cuenca, Spain; Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Talca, Chile
| | - Mónica Marazuela
- Department of Endocrinology and Nutrition, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria de La Princesa, Universidad Autónoma de Madrid, Madrid, Spain
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Sebastian-Valles F, Martínez-Alfonso J, Arranz Martin JA, Jiménez-Díaz J, Hernando Alday I, Navas-Moreno V, Armenta Joya T, Fandiño García MDM, Román Gómez GL, Lander Lobariñas LE, Martinez de Icaya P, Sampedro-Nuñez MA, Martínez-Vizacaíno V, Marazuela M. Scans per day as predictors of optimal glycemic control in people with type 1 diabetes mellitus using flash glucose monitoring: what number of scans per day should raise a red flag? Acta Diabetol 2024; 61:343-350. [PMID: 37930420 PMCID: PMC10948530 DOI: 10.1007/s00592-023-02204-x] [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: 03/11/2023] [Accepted: 10/16/2023] [Indexed: 11/07/2023]
Abstract
AIMS This study aimed to determine the minimum frequency of flash glucose monitoring (FGM) scans necessary for optimal glycemic control in patients with type 1 diabetes (T1D). METHODS Data were collected from 692 patients (47.5% female, with a median age of 47.4 years) who used FGM systems daily and recorded their clinical variables and device data. RESULTS Logistic regression models showed that performing more than 12 scans per day was associated with improved T1D control (OR = 4.22, p < 0.001) and a reduction in HbA1c (7.6 vs 7.0%, 60-53 mmol/mol p < 0.001). However, those performing less than 6 scans showed no improvement in HbA1c (7.9 vs 7.8%, 63-61 mmol/mol p = 0.514). Thirteen daily scans were determined as the optimal cutoff point for predicting optimal glycemic control using a maximally selected rank algorithm. Significant reductions were observed in mean glucose (< 0.001), coefficient of variation (< 0.001), HbA1c (< 0.001), and an increase in TIR (< 0.001) in patients who performed more than 12 daily scans. CONCLUSIONS The results suggest that a higher frequency of daily scans by T1D patients using FGM systems leads to improved chronic glycemic control. The minimum recommended frequency for optimal control is 13 scans per day, and more than 6 daily scans are needed to improve HbA1c.
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Affiliation(s)
- Fernando Sebastian-Valles
- Department of Endocrinology and Nutrition, Hospital Universitario de La PrincesaInstituto de Investigación Sanitaria de La Princesa, Universidad Autónoma de Madrid, 28006, Madrid, Spain.
| | - Julia Martínez-Alfonso
- Department of Family and Community Medicine, Hospital La Princesa/Centro de Salud Daroca, 28006, Madrid, Spain
| | - Jose Alfonso Arranz Martin
- Department of Endocrinology and Nutrition, Hospital Universitario de La PrincesaInstituto de Investigación Sanitaria de La Princesa, Universidad Autónoma de Madrid, 28006, Madrid, Spain
| | - Jessica Jiménez-Díaz
- Department of Endocrinology and Nutrition, Hospital Universitario Severo Ochoa, 28194, Leganés, Madrid, Spain
| | - Iñigo Hernando Alday
- Department of Endocrinology and Nutrition, Hospital Universitario Basurto, 48013, Bilbao, Spain
| | - Victor Navas-Moreno
- Department of Endocrinology and Nutrition, Hospital Universitario de La PrincesaInstituto de Investigación Sanitaria de La Princesa, Universidad Autónoma de Madrid, 28006, Madrid, Spain
| | - Teresa Armenta Joya
- Department of Endocrinology and Nutrition, Hospital Universitario de La PrincesaInstituto de Investigación Sanitaria de La Princesa, Universidad Autónoma de Madrid, 28006, Madrid, Spain
| | | | - Gisela Liz Román Gómez
- Department of Endocrinology and Nutrition, Hospital Universitario Severo Ochoa, 28194, Leganés, Madrid, Spain
| | | | | | - Miguel Antonio Sampedro-Nuñez
- Department of Endocrinology and Nutrition, Hospital Universitario de La PrincesaInstituto de Investigación Sanitaria de La Princesa, Universidad Autónoma de Madrid, 28006, Madrid, Spain
| | - Vicente Martínez-Vizacaíno
- Health and Social Care Research Center, Universidad de Castilla-La Mancha, 16071, Cuenca, Spain
- Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Talca, Chile
| | - Mónica Marazuela
- Department of Endocrinology and Nutrition, Hospital Universitario de La PrincesaInstituto de Investigación Sanitaria de La Princesa, Universidad Autónoma de Madrid, 28006, Madrid, Spain
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Lima RAD, Fernandes DR, Garcia RAC, Carvalho LADR, Silveira RCDCP, Teixeira CRDS. Correlation between time on target and glycated hemoglobin in people with diabetes mellitus: systematic review. Rev Lat Am Enfermagem 2023; 31:e4088. [PMID: 38055596 PMCID: PMC10695292 DOI: 10.1590/1518-8345.6655.4088] [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: 01/06/2023] [Accepted: 09/19/2023] [Indexed: 12/08/2023] Open
Abstract
to analyze the correlation between time on target and glycated hemoglobin in people living with diabetes mellitus and carrying out continuous blood glucose monitoring or self-monitoring of capillary blood glucose. systematic review of etiology and risk based on JBI guidelines and reported according to Preferred Reporting Items for Systematic Reviews and Meta- Analyses, covering six databases and grey literature. The sample included 16 studies and methodological quality was assessed using JBI tools. Protocol registered in the Open Science Framework, available at https://doi.org/10.17605/OSF.IO/NKMZB. time on target (70-180 mg/dl) showed a negative correlation with glycated hemoglobin, while time above target (>180 mg/dl) showed a positive correlation. Correlation coefficients ranged between -0.310 and -0.869 for time on target, and between 0.66 and 0.934 for time above target. A study was carried out on a population that performed self-monitoring. there is a statistically significant correlation between time on target and time above target with glycated hemoglobin. The higher the proportion in the adequate glycemic range, the closer to or less than 7% the glycated hemoglobin will be. More studies are needed to evaluate this metric with data from self-monitoring of blood glucose.
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Affiliation(s)
- Rafael Aparecido Dias Lima
- Universidade de São Paulo, Escola de Enfermagem de Ribeirão Preto, Centro Colaborador de la OPS/OMS para el Desarrollo de la Investigación en Enfermería, Ribeirão Preto, SP, Brasil
| | - Daiane Rubinato Fernandes
- Universidade de São Paulo, Escola de Enfermagem de Ribeirão Preto, Centro Colaborador de la OPS/OMS para el Desarrollo de la Investigación en Enfermería, Ribeirão Preto, SP, Brasil
- Becaria de la Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Brasil
| | - Rute Aparecida Casas Garcia
- Universidade de São Paulo, Escola de Enfermagem de Ribeirão Preto, Centro Colaborador de la OPS/OMS para el Desarrollo de la Investigación en Enfermería, Ribeirão Preto, SP, Brasil
| | | | - Renata Cristina de Campos Pereira Silveira
- Universidade de São Paulo, Escola de Enfermagem de Ribeirão Preto, Centro Colaborador de la OPS/OMS para el Desarrollo de la Investigación en Enfermería, Ribeirão Preto, SP, Brasil
| | - Carla Regina de Souza Teixeira
- Universidade de São Paulo, Escola de Enfermagem de Ribeirão Preto, Centro Colaborador de la OPS/OMS para el Desarrollo de la Investigación en Enfermería, Ribeirão Preto, SP, Brasil
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Yogev D, Goldberg T, Arami A, Tejman-Yarden S, Winkler TE, Maoz BM. Current state of the art and future directions for implantable sensors in medical technology: Clinical needs and engineering challenges. APL Bioeng 2023; 7:031506. [PMID: 37781727 PMCID: PMC10539032 DOI: 10.1063/5.0152290] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Accepted: 08/28/2023] [Indexed: 10/03/2023] Open
Abstract
Implantable sensors have revolutionized the way we monitor biophysical and biochemical parameters by enabling real-time closed-loop intervention or therapy. These technologies align with the new era of healthcare known as healthcare 5.0, which encompasses smart disease control and detection, virtual care, intelligent health management, smart monitoring, and decision-making. This review explores the diverse biomedical applications of implantable temperature, mechanical, electrophysiological, optical, and electrochemical sensors. We delve into the engineering principles that serve as the foundation for their development. We also address the challenges faced by researchers and designers in bridging the gap between implantable sensor research and their clinical adoption by emphasizing the importance of careful consideration of clinical requirements and engineering challenges. We highlight the need for future research to explore issues such as long-term performance, biocompatibility, and power sources, as well as the potential for implantable sensors to transform healthcare across multiple disciplines. It is evident that implantable sensors have immense potential in the field of medical technology. However, the gap between research and clinical adoption remains wide, and there are still major obstacles to overcome before they can become a widely adopted part of medical practice.
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Affiliation(s)
| | | | | | | | | | - Ben M. Maoz
- Authors to whom correspondence should be addressed: and
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Bellido V, Aguilera E, Cardona-Hernandez R, Diaz-Soto G, González Pérez de Villar N, Picón-César MJ, Ampudia-Blasco FJ. Expert Recommendations for Using Time-in-Range and Other Continuous Glucose Monitoring Metrics to Achieve Patient-Centered Glycemic Control in People With Diabetes. J Diabetes Sci Technol 2023; 17:1326-1336. [PMID: 35470692 PMCID: PMC10563535 DOI: 10.1177/19322968221088601] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
New metrics for assessing glycemic control beyond HbA1c have recently emerged due to the increasing use of continuous glucose monitoring (CGM) in diabetes clinical practice. Among them, time in range (TIR) has appeared as a simple and intuitive metric that correlates inversely with HbA1c and has also been newly linked to the risk of long-term diabetes complications. The International Consensus on Time in Range established a series of target glucose ranges (TIR, time below range and time above range) and recommendations for time spent within these ranges for different diabetes populations. These parameters should be evaluated together with the ambulatory glucose profile (AGP). Using standardized visual reporting may help people with diabetes and healthcare professionals in the evaluation of glucose control in frequent clinical situations. The objective of the present review is to provide practical insights to quick interpretation of patient-centered metrics based on flash glucose monitoring data, as well as showing some visual examples of common clinical situations and giving practical recommendations for their management.
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Affiliation(s)
- Virginia Bellido
- Unidad de Gestión Clínica de Endocrinología y Nutrición, Hospital Universitario Virgen del Rocío, Sevilla, Spain
| | - Eva Aguilera
- Endocrinology and Nutrition Department, Health Sciences Research Institute and University, Hospital Germans Trias i Pujol, Badalona, Spain
| | | | - Gonzalo Diaz-Soto
- Endocrinology and Nutrition Department, Hospital Clínico Universitario de Valladolid, Valladolid, Spain
- Universidad de Valladolid, Valladolid, Spain
| | | | - María J. Picón-César
- Endocrinology and Nutrition Department, Hospital Universitario Virgen de la Victoria, Málaga, Spain
- Instituto de Investigación Biomédica de Málaga, Málaga, Spain
- Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
| | - Francisco Javier Ampudia-Blasco
- Endocrinology and Nutrition Department, Hospital Clínico Universitario de Valencia, Valencia, Spain
- INCLIVA Research Foundation, Valencia, Spain
- CIBERDEM, Madrid, Spain
- Universitat de Valencia, Valencia, Spain
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Jin X, Yang X, Xu Y, Liang J, Liu C, Guo Q, Wang W, Feng Z, Yuan Y, Zhou H, Zhang Z, Jiang W, Liang Y, Lu B, Shao J, Zhong Y, Gu P. Differential correlation between time in range and eGFR or albuminuria in type 2 diabetes. Diabetol Metab Syndr 2023; 15:92. [PMID: 37386515 DOI: 10.1186/s13098-023-01071-4] [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: 04/11/2023] [Accepted: 04/27/2023] [Indexed: 07/01/2023] Open
Abstract
INTRODUCTION As a CGM-derived indicator, 'time in range' (TIR) is emerging as a key indicator for accurate assessment of glycaemic control. However, there is few report focusing on the correlation of TIR with albumuria and renal fuction. The aim of this work was to investigate whether TIR, as well as nocturnal TIR and hypoglycaemic events is related to the presence and severity of albuminuria and decrease of eGFR in type 2 diabetes. RESEARCH DESIGN AND METHODS A total of 823 patients were enrolled in this study. All patients received continuous glucose monitoring, TIR indicating the percentage of time that blood glucose was in the range of 3.9-10.0 mmol/L. The Spearman analysis was applied to analyze the relationship between TIR (or nocturnal TIR) and ACR. Logistic regression was used to explore whether TIR (or nocturnal TIR) is an independent risk factor for albuminuria. RESULTS The prevalence of albuminuria decreased with increasing TIR quartiles. Binary logistic regression revealed that TIR as well as nocturnal TIR was obviously related to the presence of albuminuria. Multiple regression analysis found that only nocturnal TIR was obviously related to the severity of albuminuria. In our study, eGFR was significantly associated with the number of hypoglycemic events. CONCLUSIONS In T2DM patients, TIR and nocturnal TIR is associated with the presence of albuminuria independent of HbA1c and GV metrics. Nocturnal TIR shows better correlation than TIR. The role of TIR especially nocturnal TIR in the evaluation of diabetes kidney disease should be emphasized.
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Affiliation(s)
- Xuguang Jin
- Medical School, Affiliated Jinling Hospital, Department of Endocrinology, Nanjing University, 305 East Zhongshan Road, Nanjing, 210002, Jiangsu, China
| | - Xinyi Yang
- Medical School, Affiliated Jinling Hospital, Department of Endocrinology, Nanjing University, 305 East Zhongshan Road, Nanjing, 210002, Jiangsu, China
| | - Yixin Xu
- Medical School, Affiliated Jinling Hospital, Department of Endocrinology, Nanjing University, 305 East Zhongshan Road, Nanjing, 210002, Jiangsu, China
| | - Jingjing Liang
- Medical School, Affiliated Jinling Hospital, Department of Endocrinology, Nanjing University, 305 East Zhongshan Road, Nanjing, 210002, Jiangsu, China
| | - Chunyan Liu
- Medical School, Affiliated Jinling Hospital, Department of Endocrinology, Nanjing University, 305 East Zhongshan Road, Nanjing, 210002, Jiangsu, China
| | - Qingyu Guo
- Medical School, Affiliated Jinling Hospital, Department of Endocrinology, Nanjing University, 305 East Zhongshan Road, Nanjing, 210002, Jiangsu, China
| | - Wei Wang
- Medical School, Affiliated Jinling Hospital, Department of Endocrinology, Nanjing University, 305 East Zhongshan Road, Nanjing, 210002, Jiangsu, China
| | - Zhouqin Feng
- Medical School, Affiliated Jinling Hospital, Department of Endocrinology, Nanjing University, 305 East Zhongshan Road, Nanjing, 210002, Jiangsu, China
| | - Yanyu Yuan
- Department of Endocrinology, the affiliated Jinling Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Hui Zhou
- Department of Endocrinology, Jinling Hospital, First School of Clinical Medicine, Southern Medical University, Nanjing, China
| | - Zhen Zhang
- Department of Endocrinology, Jinling Hospital, First School of Clinical Medicine, Southern Medical University, Nanjing, China
| | - Wenwen Jiang
- Department of Endocrinology, the affiliated Jinling Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yue Liang
- Medical School, Affiliated Jinling Hospital, Department of Endocrinology, Nanjing University, 305 East Zhongshan Road, Nanjing, 210002, Jiangsu, China
| | - Bin Lu
- Medical School, Affiliated Jinling Hospital, Department of Endocrinology, Nanjing University, 305 East Zhongshan Road, Nanjing, 210002, Jiangsu, China
| | - Jiaqing Shao
- Medical School, Affiliated Jinling Hospital, Department of Endocrinology, Nanjing University, 305 East Zhongshan Road, Nanjing, 210002, Jiangsu, China.
| | - Yong Zhong
- Medical School, Affiliated Jinling Hospital, Department of Endocrinology, Nanjing University, 305 East Zhongshan Road, Nanjing, 210002, Jiangsu, China.
| | - Ping Gu
- Medical School, Affiliated Jinling Hospital, Department of Endocrinology, Nanjing University, 305 East Zhongshan Road, Nanjing, 210002, Jiangsu, China.
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Montt-Blanchard D, Sánchez R, Dubois-Camacho K, Leppe J, Onetto MT. Hypoglycemia and glycemic variability of people with type 1 diabetes with lower and higher physical activity loads in free-living conditions using continuous subcutaneous insulin infusion with predictive low-glucose suspend system. BMJ Open Diabetes Res Care 2023; 11:11/2/e003082. [PMID: 36944432 DOI: 10.1136/bmjdrc-2022-003082] [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: 08/08/2022] [Accepted: 02/23/2023] [Indexed: 03/23/2023] Open
Abstract
INTRODUCTION Maintaining glycemic control during and after physical activity (PA) is a major challenge in type 1 diabetes (T1D). This study compared the glycemic variability and exercise-related diabetic management strategies of adults with T1D achieving higher and lower PA loads in nighttime-daytime and active- sedentary behavior hours in free-living conditions. RESEARCH DESIGN AND METHODS Active adults (n=28) with T1D (ages: 35±10 years; diabetes duration: 21±11 years; body mass index: 24.8±3.4 kg/m2; glycated hemoglobin A1c: 6.9±0.6%) on continuous subcutaneous insulin delivery system with predictive low glucose suspend system and glucose monitoring, performed different types, duration and intensity of PA under free-living conditions, tracked by accelerometer over 14 days. Participants were equally divided into lower load (LL) and higher load (HL) by median of daily counts per minute (61122). Glycemic variability was studied monitoring predefined time in glycemic ranges (time in range (TIR), time above range (TAR) and time below range (TBR)), coefficient of variation (CV) and mean amplitude of glycemic excursions (MAGE). Parameters were studied in defined hours timeframes (nighttime-daytime and active-sedentary behavior). Self-reported diabetes management strategies were analysed during and post-PA. RESULTS Higher glycemic variability (CV) was observed in sedentary hours compared with active hours in the LL group (p≤0.05). HL group showed an increment in glycemic variability (MAGE) during nighttime versus daytime (p≤0.05). There were no differences in TIR and TAR across all timeframes between HL and LL groups. The HL group had significantly more TBR during night hours than the LL group (p≤0.05). Both groups showed TBR above recommended values. All participants used fewer post-PA management strategies than during PA (p≤0.05). CONCLUSION Active people with T1D are able to maintain glycemic variability, TIR and TAR within recommended values regardless of PA loads. However, the high prevalence of TBR and the less use of post-PA management strategies highlights the potential need to increase awareness on actions to avoid glycemic excursions and hypoglycemia after exercise completion.
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Affiliation(s)
| | - Raimundo Sánchez
- Faculty of Engineering and Sciences, Universidad Adolfo Ibáñez, Penalolen, Chile
| | - Karen Dubois-Camacho
- Faculty of Medicine, Institute of Biomedical Sciences, Universidad de Chile, Santiago de Chile, Chile
| | - Jaime Leppe
- Faculty of Medicine, Clínica Alemana, Universidad del Desarrollo, Santiago, Chile
| | - María Teresa Onetto
- Faculty of Medicine, Pontifical Catholic University of Chile, Santiago, Chile
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9
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Eissa MR, Benaissa M, Good T, Hui Z, Gianfrancesco C, Ferguson C, Elliott J. Analysis of real-world capillary blood glucose data to help reduce HbA 1c and hypoglycaemia in type 1 diabetes: Evidence in favour of using the percentage of readings in target and coefficient of variation. Diabet Med 2023; 40:e14972. [PMID: 36209371 PMCID: PMC10091810 DOI: 10.1111/dme.14972] [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: 01/25/2022] [Accepted: 10/28/2022] [Indexed: 01/17/2023]
Abstract
AIMS To examine real-world capillary blood glucose (CBG) data according to HbA1c to define proportions of CBG readings at different HbA1c levels, and evaluate patterns in CBG measurements to suggest areas to focus on with regard to self-management. METHODS A retrospective analysis stratified 682 adults with type 1 diabetes split into quartiles based on their HbA1c . The proportions of results in different CBG ranges and associations with HbA1c were evaluated. Patterns in readings following episodes of hyperglycaemia and hypoglycaemia were examined, using glucose to next glucose reading table (G2G). RESULTS CBG readings in the target range (3.9-10 mmol/L) increase by ~10% across each CBG quartile (31% in the highest versus 63% in the lowest quartile, p < 0.05). The novel G2G table helps the treatment-based interpretation of data. Hypoglycaemia is often preceded by hyperglycaemia, and vice-versa, and is twice as likely in the highest HbA1c quartile. Re-testing within 30 min of hypoglycaemia is associated with less hypoglycaemia, 1.6% versus 7.2%, p < 0.001, and also reduces subsequent hyperglycaemia and further hypoglycaemia in the proceeding 24 h. The coefficient of variation, but not standard deviation, is highly associated with hypoglycaemia, r = 0.71, and a CV ≤ 36% equates to 3.3% of CBG readings in the hypoglycaemic range. CONCLUSIONS HbA1c <58 mmol/mol (7.5%) is achievable even when only ~60% of CBG readings are between 3.9-10 mmol/L. Examining readings subsequent to out-of-range readings suggests useful behaviours which people with type 1 diabetes could be supported to adhere to, both in a clinic and structured education programmes, thereby decreasing the risk of hypoglycaemia whilst also reducing hyperglycaemia and improving HbA1c .
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Affiliation(s)
- Mohammad R Eissa
- Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield, UK
| | - Mohammed Benaissa
- Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield, UK
| | - Tim Good
- Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield, UK
| | - Zheng Hui
- Department of Electronic and Electrical Engineering, University of Sheffield, Sheffield, UK
| | - Carla Gianfrancesco
- Department of Diabetes and Endocrinology, Sheffield Teaching Hospitals NHS FT, Sheffield, UK
| | - Carolin Ferguson
- Department of Diabetes and Endocrinology, Sheffield Teaching Hospitals NHS FT, Sheffield, UK
| | - Jackie Elliott
- Department of Diabetes and Endocrinology, Sheffield Teaching Hospitals NHS FT, Sheffield, UK
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK
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10
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Shah VN, Akturk HK, Vigers T, Pyle L, Oliver N, Klonoff DC. Relationship Between Daytime Versus Nighttime Continuous Glucose Monitoring Metrics with A1C in Adults with Type 1 Diabetes. Diabetes Technol Ther 2023; 25:62-68. [PMID: 36306519 DOI: 10.1089/dia.2022.0365] [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: 01/06/2023]
Abstract
Objective: To evaluate influence of daytime versus nighttime continuous glucose monitoring (CGM)-based metrics on A1C in adults with type 1 diabetes (T1D). Research Design and Methods: CGM data from 407 adults with T1D (age 39 ± 15 years, diabetes duration 20 ± 12 years, A1C 7.3% ± 1.4% and 53% female) from two studies were included in this analysis. The association between daytime (6 AM-10.59 PM) and nighttime (11 PM-5.59 AM) CGM variables such as mean glucose, time in range (TIR; 70-180 mg/dL), time in tight target range (TTIR; 70-140 mg/dL), and time above range (TAR >180 mg/dL) was examined within five A1C categories (<7%, 7%-7.9%, 8%-8.9%, 9%-9.9%, and ≥10%). Results: Although mean glucose was increasing with higher A1C, there was no statistical difference in mean glucose between daytime versus nighttime within five A1C groups (143.2 ± 22.7 vs. 143.6 ± 25.0 for A1C <7%, 171.4 ± 17.3 vs. 175.3 ± 28.8 for A1C 7.0%-7.9%, 193.4 ± 19.4 vs. 195.3 ± 29.5 for A1C 8.0%-8.9%, 214.9 ± 28.8 vs. 219.7 ± 36.1 for A1C 9.0%-9.9% and 244.0 ± 39.0 vs. 239.9 ± 50.9 for A1C ≥10%, P > 0.05). Similarly, there was no difference between various CGM metrics by daytime versus nighttime within five A1C groups. Differences between five A1C groups' daytime versus nighttime mean glucose, TIR, TTIR, and TAR were also not statistically significant (all P > 0.05) Conclusion: Daytime versus nighttime glycemic control has similar influence on A1C in adults with T1D.
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Affiliation(s)
- Viral N Shah
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Halis K Akturk
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Tim Vigers
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Laura Pyle
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Nick Oliver
- Imperial College London, London, United Kingdom
| | - David C Klonoff
- Diabetes Research Institute, Mills-Peninsula Medical Center, San Mateo, California, USA
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11
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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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12
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Choudhary P, Kolassa R, Keuthage W, Kroeger J, Thivolet C, Evans M, Ré R, de Portu S, Vorrink L, Shin J, Habteab A, Castañeda J, da Silva J, Cohen O. Advanced hybrid closed loop therapy versus conventional treatment in adults with type 1 diabetes (ADAPT): a randomised controlled study. Lancet Diabetes Endocrinol 2022; 10:720-731. [PMID: 36058207 DOI: 10.1016/s2213-8587(22)00212-1] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 06/29/2022] [Accepted: 07/07/2022] [Indexed: 12/23/2022]
Abstract
BACKGROUND Adults with type 1 diabetes who are treated with multiple daily injections of insulin plus intermittently scanned continuous glucose monitoring (isCGM) can have suboptimal glucose control. We aimed to assess the efficacy of an advanced hybrid closed loop (AHCL) system compared with such therapy in this population. METHODS The Advanced Hybrid Closed Loop Study in Adult Population with Type 1 Diabetes (ADAPT) trial is a prospective, multicentre, open-label, randomised controlled trial that involved 14 centres in three European countries (France, Germany, and the UK). We enrolled patients who were at least 18 years of age, had a type 1 diabetes duration of at least 2 years, HbA1c of at least 8% (64 mmol/mol), and were using multiple daily injections of insulin plus isCGM (cohort A) or real time continuous glucose monitoring (cohort B) for at least 3 months. Here, only results for cohort A are reported. Participants were randomly allocated 1:1 to AHCL therapy or continuation of multiple daily injections of insulin plus continuous glucose monitoring for 6 months with an investigator-blinded block randomisation procedure. Participants and treating clinicians could not be masked to the arm assignment. The primary endpoint was the between-group difference in mean HbA1c change from baseline to 6 months in the intention-to-treat population using AHCL therapy and those using multiple daily injections of insulin plus isCGM. The primary endpoint was analysed using a repeated measures random-effects model with the study arm and period as factors. Safety endpoints included the number of device deficiencies, severe hypoglycaemic events, diabetic ketoacidosis, and serious adverse events. This study is registered with ClinicalTrials.gov, NCT04235504. FINDINGS Between July 13, 2020, and March 12, 2021, 105 people were screened and 82 randomly assigned to treatment (41 in each arm). At 6 months, mean HbA1c had decreased by 1·54% (SD 0·73), from 9·00% to 7·32% in the AHCL group and 0·20% (0·80) in the multiple daily injections of insulin plus isCGM from 9·07% to 8·91% (model-based difference -1·42%, 95% CI -1·74 to -1·10; p<0·0001). No diabetic ketoacidosis, severe hypoglycaemia, or serious adverse events related to study devices occurred in either group; two severe hypoglycaemic events occurred in the run-in phase. 15 device-related non-serious adverse events occurred in the AHCL group, compared with three in the multiple daily injections of insulin plus isCGM group. Two serious adverse events occurred (one in each group), these were breast cancer (in one patient in the AHCL group) and intravitreous haemorrhage (in one patient in the multiple daily injections of insulin plus isCGM group). INTERPRETATION In people with type 1 diabetes using multiple daily injections of insulin plus isCGM and with HbA1c of at least 8%, the use of AHCL confers benefits in terms of glycaemic control beyond those that can be achieved with multiple daily injections of insulin plus isCGM. These data support wider access to AHCL in people with type 1 diabetes not at target glucose levels. FUNDING Medtronic International Trading Sàrl.
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Affiliation(s)
- Pratik Choudhary
- Kings College Hospital NHS Foundation Trust, London, UK; Leicester Diabetes Centre, University of Leicester, Leicester, UK
| | - Ralf Kolassa
- Diabetologische Schwerpunktpraxis, Bergheim, Germany
| | - Winfried Keuthage
- Schwerpunktpraxis für Diabetes und Ernährungsmedizin, Münster, Germany
| | - Jens Kroeger
- Zentrum für Diabetologie Bergedorf, Hamburg, Germany
| | | | - Mark Evans
- Wellcome Trust-MRC Institute of Metabolic Science and Department of Medicine, University of Cambridge, Cambridge, UK
| | - Roseline Ré
- Medtronic International Trading Sàrl, Tolochenaz, Switzerland
| | - Simona de Portu
- Medtronic International Trading Sàrl, Tolochenaz, Switzerland
| | - Linda Vorrink
- Medtronic International Trading Sàrl, Tolochenaz, Switzerland
| | - John Shin
- Medtronic, Northridge, California, USA
| | - Aklilu Habteab
- Medtronic Bakken Research Center, Maastricht, Netherlands
| | | | - Julien da Silva
- Medtronic International Trading Sàrl, Tolochenaz, Switzerland
| | - Ohad Cohen
- Medtronic International Trading Sàrl, Tolochenaz, Switzerland.
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13
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Kapsar P, Chao C, Walker T. Nontraditional Uses of Continuous Glucose Monitoring. J Nurse Pract 2022. [DOI: 10.1016/j.nurpra.2022.06.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
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14
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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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15
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Abstract
PURPOSE OF REVIEW In this review, we examine the expanding role of continuous glucose monitoring in glycaemic management in primary care. RECENT FINDINGS Improving technology and decreasing cost have increased the uptake of use of continuous glucose monitoring (CGM) for glycaemic management in primary care, wherein most diabetes is managed. Optimized use of this technology, however, will require a convergence of several factors. Availability of devices for people with diabetes, availability of data at the time of clinical interactions, and expertise in interpretation of CGM and ambulatory glucose profile (AGP) data, as well as optimization of therapies, will be required. Significant progress has been made in all three areas in recent years, yet creating systems of support for widespread use of CGM in primary care remains an area of active investigation. SUMMARY There has been significant uptake in the use of CGM in the management of diabetes in primary care. Optimized use, however, requires both access to CGM data and the expertise to use the data. Although promising strategies have emerged, the task of generalizing these strategies to the broad population of primary care in America is ongoing. CGM technology holds significant potential for improving glycaemic management in primary care, yet important work remains to leverage the full potential of this promising technology.
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Affiliation(s)
- Thomas W Martens
- International Diabetes Center, HealthPartners Institute and Park Nicollet Department of Internal Medicine, Minneapolis, Minnesota, USA
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