Glucose Variability: A Review of Clinical Applications and Research Developments

Multiscale Entropy Analysis of Complex Physiologic Time Series

Costa, M., Goldberger, A. L., & Peng, C.-K. (2002) · Physical Review Letters · doi:10.1103/physrevlett.89.068102 · Cited by 3,207

International consensus on use of continuous glucose monitoring

Danne, T., Nimri, R., Battelino, T., Bergenstal, R. M., Close, K. L., DeVries, J. H., Garg, S., Heinemann, L., Hirsch, I., Amiel, S. A., et al. (2017) · Diabetes Care · doi:10.2337/dc17-1600 · Cited by 2,069

Glucose variability is associated with intensive care unit mortality*

Hermanides, J., Vriesendorp, T. M., Bosman, R. J., Zandstra, D. F., Hoekstra, J. B. L., & DeVries, J. H. (2010) · Critical Care Medicine · doi:10.1097/ccm.0b013e3181cc4be9 · Cited by 446

Glucose Variability; Does It Matter?

Siegelaar, S. E., Holleman, F., Hoekstra, J. B. L., & DeVries, J. H. (2010) · Endocrine Reviews · doi:10.1210/er.2009-0021 · Cited by 409

Toward Defining the Threshold Between Low and High Glucose Variability in Diabetes

Monnier, L., Colette, C., Wojtusciszyn, A., Dejager, S., Renard, E., Molinari, N., & Owens, D. R. (2017) · Diabetes Care · doi:10.2337/dc16-1769 · Cited by 390

Interpretation of Continuous Glucose Monitoring Data: Glycemic Variability and Quality of Glycemic Control

Rodbard, D. (2009) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2008.0132 · Cited by 324

Recommendations for standardizing glucose reporting and analysis to optimize clinical decision making in diabetes: the Ambulatory Glucose Profile (AGP)

Bergenstal, R. M., Ahmann, A. J., Bailey, T., Beck, R. W., Bissen, J., Buckingham, B., Deeb, L., Dolin, R. H., Garg, S. K., Goland, R., et al. (2013) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2013.0051 · Cited by 307

Glucose Variability: Timing, Risk Analysis, and Relationship to Hypoglycemia in Diabetes

Kovatchev, B. P., & Cobelli, C. (2016) · Diabetes Care · doi:10.2337/dc15-2035 · Cited by 276

Symmetrization of the Blood Glucose Measurement Scale and Its Applications

Kovatchev, B. P., Cox, D. J., Gonder-Frederick, L. A., & Clarke, W. L. (1997) · Diabetes Care · doi:10.2337/diacare.20.11.1655 · Cited by 258

Statistical Tools to Analyze Continuous Glucose Monitor Data

Clarke, W. L., & Kovatchev, B. P. (2009) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2008.0138 · Cited by 248

Clinical Targets for Continuous Glucose Monitoring Data Interpretation: Recommendations From the International Consensus on Time in Range

Battelino, T., Danne, T., Bergenstal, R. M., Amiel, S. A., Beck, R., Biester, T., Bosi, E., Buckingham, B. A., Cefalu, W. T., Close, K. L., et al. (2019) · Diabetes Care · doi:10.2337/dci19-0028 · Cited by 4,237

Glucose‐Sensitive Hydrogel Optical Fibers Functionalized with Phenylboronic Acid

Yetisen, A. K., Jiang, N., Fallahi, A., Montelongo, Y., Ruiz‐Esparza, G. U., Tamayol, A., Zhang, Y. S., Mahmood, I., Yang, S., Kim, K. S., et al. (2017) · Advanced Materials · doi:10.1002/adma.201606380 · Cited by 311

Review of methods for detecting glycemic disorders

Bergman, M., Abdul‐Ghani, M. A., DeFronzo, R. A., Manco, M., Sesti, G., Fiorentino, T. V., Ceriello, A., Rhee, M. K., Phillips, L. S., Chung, S. T., et al. (2020) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2020.108233 · Cited by 210

Real-time intradermal continuous glucose monitoring using a minimally invasive microneedle-based system

Ribet, F., Stemme, G., & Roxhed, N. (2018) · Biomedical Microdevices · doi:10.1007/s10544-018-0349-6 · Cited by 184

Glucose Variability: How Does It Work?

Klimontov, V. V., Saik, O., & Korbut, A. I. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22157783 · Cited by 133

Artificial Intelligence and Machine Learning for Improving Glycemic Control in Diabetes: Best Practices, Pitfalls, and Opportunities

Jacobs, P. G., Herrero, P., Facchinetti, A., Vehi, J., Kovatchev, B., Breton, M. D., Cinar, A., Nikita, K. S., Doyle, F. J., Bondia, J., et al. (2024) · IEEE Reviews in Biomedical Engineering · doi:10.1109/rbme.2023.3331297 · Cited by 113

Utilizing the Ambulatory Glucose Profile to Standardize and Implement Continuous Glucose Monitoring in Clinical Practice

Johnson, M. L., Martens, T. W., Criego, A. B., Carlson, A. L., Simonson, G. D., & Bergenstal, R. M. (2019) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2019.0034 · Cited by 106

Ever-Increasing Insulin-Requiring Patients Globally

Garg, S. K., Rewers, A. H., & Aktürk, H. K. (2018) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2018.0101 · Cited by 104

Engineering digital biomarkers of interstitial glucose from noninvasive smartwatches

Bent, B., Cho, P. J., Henriquez, M., Wittmann, A., Thacker, C., Feinglos, M. N., Crowley, M. J., & Dunn, J. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00465-w · Cited by 101

A Consensus Statement for Continuous Glucose Monitoring Metrics for Inpatient Clinical Trials

Spanakis, E. K., Cook, C. B., Kulasa, K. M., Aloi, J., Bally, L., Davis, G. M., Dungan, K. M., Galindo, R. J., Mendez, C. E., Pasquel, F. J., et al. (2023) · Journal of Diabetes Science and Technology · doi:10.1177/19322968231191104 · Cited by 82

Glucose time in range, time above range, and time below range depend on mean or median glucose or HbA1c, glucose coefficient of variation, and shape of the glucose distribution

Rodbard, D. (2020) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2019.0440 · Cited by 75

Explainable Machine Learning for Real-Time Hypoglycemia and Hyperglycemia Prediction and Personalized Control Recommendations

Duckworth, C., Guy, M., Kumaran, A., O’Kane, A. A., Ayobi, A., Chapman, A. P., Marshall, P., & Boniface, M. (2022) · Journal of Diabetes Science and Technology · doi:10.1177/19322968221103561 · Cited by 76

Respective Contributions of Glycemic Variability and Mean Daily Glucose as Predictors of Hypoglycemia in Type 1 Diabetes: Are They Equivalent?

Monnier, L., Wojtusciszyn, A., Molinari, N., Colette, C., Renard, É., & Owens, D. R. (2020) · Diabetes Care · doi:10.2337/dc19-1549 · Cited by 62

Glucose variability and diabetes complications: Risk factor or biomarker? Can we disentangle the “Gordian Knot”?

Monnier, L., Colette, C., & Owens, D. R. (2021) · Diabetes & Metabolism · doi:10.1016/j.diabet.2021.101225 · Cited by 61

Retrospective study of glycemic variability, BMI, and blood pressure in diabetes patients in the Digital Twin Precision Treatment Program

Shamanna, P., Dharmalingam, M., Sahay, R. K., Mohammed, J., Mohamed, M., Poon, T., Kleinman, N. L., & Thajudeen, M. (2021) · Scientific Reports · doi:10.1038/s41598-021-94339-6 · Cited by 59

Greater daily glucose variability and lower time in range assessed with continuous glucose monitoring are associated with greater aortic stiffness: The Maastricht Study

Foreman, Y. D., van Doorn, W. P. T. M., Schaper, N. C., van Greevenbroek, M. M. J., Kallen, C., Henry, R. M. A., Koster, A., Eussen, S. J. P. M., Wesselius, A., Reesink, K. D., et al. (2021) · Diabetologia · doi:10.1007/s00125-021-05474-8 · Cited by 51

A Review of Research Progress on Glycemic Variability and Gestational Diabetes

Yu, W., Wu, N., Li, L., OuYang, H., Qian, M., & Shen, H. (2020) · Diabetes, Metabolic Syndrome and Obesity: Targets and Therapy · doi:10.2147/dmso.s261486 · Cited by 44

Point-of-care diagnostics to improve maternal and neonatal health in low-resource settings

Majors, C. E., Smith, C. A., Natoli, M. E., Kundrod, K. A., & Richards-Kortum, R. R. (2017) · Lab on a Chip · doi:10.1039/c7lc00374a · Cited by 52

Ageing well with diabetes: the role of technology

Maltese, G., McAuley, S. A., Trawley, S. L., & Sinclair, A. J. (2024) · Diabetologia · doi:10.1007/s00125-024-06240-2 · Cited by 56

Glycemic variability: Measurement, target, impact on complications of diabetes and does it really matter?

Mo, Y., Lu, J., & Zhou, J. (2023) · Journal of Diabetes Investigation · doi:10.1111/jdi.14112 · Cited by 53

Sleep quality and glycaemic variability in a real-life setting in adults with type 1 diabetes

Brandt, R., Park, M., Wroblewski, K., Quinn, L. T., Tasali, E., & Çınar, A. (2021) · Diabetologia · doi:10.1007/s00125-021-05500-9 · Cited by 46

A retrospective in‐depth analysis of continuous glucose monitoring datasets for patients with hepatic glycogen storage disease: Recommended outcome parameters for glucose management

Peeks, F., Hoogeveen, I. J., Feldbrugge, R. L., Burghard, R., de Boer, F., Fokkert‐Wilts, M. J., van der Klauw, M. M., Oosterveer, M. H., & Derks, T. G. J. (2021) · Journal of Inherited Metabolic Disease · doi:10.1002/jimd.12383 · Cited by 42

Glycemic variability: Importance, relationship with physical activity, and the influence of exercise

Sparks, J. R., Kishman, E. E., Sarzynski, M. A., Davis, J. M., Grandjean, P. W., Durstine, J. L., & Wang, X. (2021) · Sports Medicine and Health Science · doi:10.1016/j.smhs.2021.09.004 · Cited by 48

Defining High Glycemic Variability in Type 1 Diabetes: Comparison of Multiple Indexes to Identify Patients at Risk of Hypoglycemia

Gómez, A. M., Henao, D. C., Madero, A. I., Taboada, L. B., Cruz, V., Gómez, M. A. R., Rondón, M., Múñoz, Ó., Maira, G., & Vargas, F. M. L. (2019) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2019.0075 · Cited by 41

Key indices of glycaemic variability for application in diabetes clinical practice

Monnier, L., Bonnet, F., Colette, C., Renard, É., & Owens, D. R. (2023) · Diabetes & Metabolism · doi:10.1016/j.diabet.2023.101488 · Cited by 35

Glycemic Variability As a Prognostic Factor for Mortality in Patients With Critical Illness: A Systematic Review and Meta-Analysis

Hryciw, B. N., Ghossein, J., Rochwerg, B. N., Meggison, H., Fernando, S. M., Kyeremanteng, K., Tran, A., & SEELY, A. J. E. (2024) · Critical Care Explorations · doi:10.1097/cce.0000000000001025 · Cited by 30

Enhancing the Long‐Term Stability of a Polymer Dot Glucose Transducer by Using an Enzymatic Cascade Reaction System

Sun, K., Ding, Z., Zhang, J., Chen, H., Qin, Y., Xu, S., Wu, C., Yu, J., & Chiu, D. T. (2020) · Advanced Healthcare Materials · doi:10.1002/adhm.202001019 · Cited by 31

Impact of anxiety, depression and disease-related distress on long-term glycaemic variability among subjects with Type 1 diabetes mellitus

Déniz-García, A., Díaz-Artiles, A., Saavedra, P., Alvarado-Martel, D., Wägner, A. M., & Boronat, M. (2022) · BMC Endocrine Disorders · doi:10.1186/s12902-022-01013-7 · Cited by 30

Machine Learning Models for Nocturnal Hypoglycemia Prediction in Hospitalized Patients with Type 1 Diabetes

Berikov, V., Андреевна, К. О., Semenova, J. F., & Klimontov, V. V. (2022) · Journal of Personalized Medicine · doi:10.3390/jpm12081262 · Cited by 30

Orexin neurons track temporal features of blood glucose in behaving mice

Viskaitis, P., Tesmer, A. L., Liu, Z., Karnani, M., Arnold, M., Donegan, D., Bracey, E. F., Grujic, N., Patriarchi, T., Peleg‐Raibstein, D., et al. (2024) · Nature Neuroscience · doi:10.1038/s41593-024-01648-w · Cited by 30

Effect of cinnamon spice on continuously monitored glycemic response in adults with prediabetes: a 4-week randomized controlled crossover trial

Zelicha, H., Yang, J., Henning, S. M., Huang, J., Lee, R., Thames, G., Livingston, E. H., Heber, D., & Li, Z. (2024) · American Journal of Clinical Nutrition · doi:10.1016/j.ajcnut.2024.01.008 · Cited by 36

Glycemic variability assessed by continuous glucose monitoring in hospitalized patients with community-acquired pneumonia

Olsen, M. T., Dungu, A. M., Klarskov, C. K., Jensen, A. K., Lindegaard, B., & Kristensen, P. L. (2022) · BMC Pulmonary Medicine · doi:10.1186/s12890-022-01874-7 · Cited by 27

Glycaemic variation is a predictor of all-cause mortality in the Veteran Affairs Diabetes Trial

Zhou, J. J., Koška, J., Bahn, G., & Reaven, P. D. (2019) · Diabetes and Vascular Disease Research · doi:10.1177/1479164119827598 · Cited by 27

Is the Consensual Threshold for Defining High Glucose Variability Implementable in Clinical Practice?

Julla, J., Jacquemier, P., Fagherazzi, G., Vidal-Trécan, T., Juddoo, V., Jaziri, A., Mersel, H., Venteclef, N., Roussel, R., Massin, P., et al. (2021) · Diabetes Care · doi:10.2337/dc20-1847 · Cited by 26

Glucose variability in subjects with normal glucose tolerance: Relations with body composition, insulin secretion and sensitivity

Klimontov, V. V., & Semenova, J. F. (2022) · Diabetes & Metabolic Syndrome Clinical Research & Reviews · doi:10.1016/j.dsx.2022.102387 · Cited by 26

Glucose Variability and Risk of Hepatocellular Carcinoma in Patients with Diabetes: A Nationwide Population-Based Study

Yoo, J., Cho, E. J., Han, K., Heo, S. S., Kim, B., Shin, D. W., & Yu, S. J. (2021) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-20-1654 · Cited by 25

Association of specialized enteral nutrition with glycemic control and clinical outcomes in critically ill patients: A meta-analysis of randomized controlled trials

Eckert, I. D. C., Kumbier, M. C. C., Silva, F. M., Franzosi, O. S., & de Almeida, J. C. (2021) · Clinical Nutrition · doi:10.1016/j.clnu.2021.04.030 · Cited by 25

Critical Reappraisal of the Time-in-Range: Alternative or Useful Addition to Glycated Hemoglobin?

Heinemann, L., Freckmann, G., Müller‐Wieland, D., & Kellerer, M. (2019) · Journal of Diabetes Science and Technology · doi:10.1177/1932296819883885 · Cited by 25

Comparison of the effects of gemigliptin and dapagliflozin on glycaemic variability in type 2 diabetes: A randomized, open‐label, active‐controlled, 12‐week study (STABLE II study)

Kwak, S. H., Hwang, Y., Won, J. C., Bae, J. C., Kim, H. J., Suh, S., Lee, E. Y., Lee, S., Kim, S., & Kim, J. H. (2019) · Diabetes Obesity and Metabolism · doi:10.1111/dom.13882 · Cited by 24

Association of glycemic variability assessed by continuous glucose monitoring with subclinical diabetic polyneuropathy in type 2 diabetes patients

Pan, J., Yan, X., Li, F., Zhang, Y., Jiang, L., & Wang, C. (2021) · Journal of Diabetes Investigation · doi:10.1111/jdi.13652 · Cited by 22

Current landscape and comprehensive management of glycemic variability in diabetic retinopathy

Chen, B., Shen, C., & Sun, B. (2024) · Journal of Translational Medicine · doi:10.1186/s12967-024-05516-w · Cited by 21

Quality of Glycemic Control: Assessment Using Relationships Between Metrics for Safety and Efficacy

Rodbard, D. (2021) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2021.0115 · Cited by 21

Large-Scale Data Analysis for Glucose Variability Outcomes with Open-Source Automated Insulin Delivery Systems

Shahid, A., & Lewis, D. (2022) · Nutrients · doi:10.3390/nu14091906 · Cited by 21

Long‐term glycemic control and glucose variability assessed with continuous glucose monitoring in a pediatric population with type 1 diabetes: Determination of optimal sampling duration

Piona, C. A., Marigliano, M., Mozzillo, E., Franzese, A., Zanfardino, A., Iafusco, D., Maltoni, G., Zucchini, S., Delvecchio, M., & Maffeis, C. (2020) · Pediatric Diabetes · doi:10.1111/pedi.13115 · Cited by 21

How to Measure Glycemic Variability? A Literature Review

Lazăr, S., Ioniță, I., Reurean‐Pintilei, D., & Timar, B. (2023) · Medicina · doi:10.3390/medicina60010061 · Cited by 22

Decreasing complexity of glucose time series derived from continuous glucose monitoring is correlated with deteriorating glucose regulation

Li, C., Ma, X., Lu, J., Tao, R., Yu, X., Mo, Y., Lu, W., Bao, Y., Zhou, J., & Jia, W. (2022) · Frontiers of Medicine · doi:10.1007/s11684-022-0955-9 · Cited by 19

The Ambulatory Glucose Profile: Opportunities for Enhancement

Rodbard, D. (2020) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2020.0524 · Cited by 20

Impact of acute glycemic variability on short-term outcomes in patients with ST-segment elevation myocardial infarction: a multicenter population-based study

Wang, J., Wang, L., Yang, Y., Tan, H., & Zhu, J. (2024) · Cardiovascular Diabetology · doi:10.1186/s12933-024-02250-x · Cited by 19

Low‐carbohydrate, high‐fat enteral formulas for managing glycemic control in patients who are critically ill: A review of the evidence

Burslem, R., Radler, D. R., Parker, A., & Zelig, R. S. (2021) · Nutrition in Clinical Practice · doi:10.1002/ncp.10652 · Cited by 18

The significance of coefficient of variation as a measure of hypoglycaemia risk and glycaemic control in real world users of the automated insulin delivery MiniMed 780G system

Castañeda, J., Arrieta, A., van den Heuvel, T. R. A., & Cohen, O. (2023) · Diabetes Obesity and Metabolism · doi:10.1111/dom.15139 · Cited by 18

Kernel machine learning methods to handle missing responses with complex predictors. Application in modelling five-year glucose changes using distributional representations

Matabuena, M., Félix, P., Meijide-Garcia, C., & Gudé, F. (2022) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2022.106905 · Cited by 17

Cardiovascular autonomic neuropathy is associated with increased glycemic variability driven by hyperglycemia rather than hypoglycemia in patients with diabetes

Gad, H., Elgassim, E., Mohammed, I., Alhaddad, A. Y., Aly, H., Cabibihan, J., Al-Ali, A. K., Sadasivuni, K. K., Petropoulos, I. N., Ponirakis, G., et al. (2023) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2023.110670 · Cited by 16

Admission Hyperglycemia Predicts Long-Term Mortality in Critically Ill Patients With Subarachnoid Hemorrhage: A Retrospective Analysis of the MIMIC-III Database

Liu, D., Tang, Y., & Zhang, Q. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.678998 · Cited by 17

Continuous glucose monitoring of steroid-induced hyperglycemia in patients with dermatologic diseases

Kleinhans, M., Albrecht, L. J., Benson, S., Fuhrer, D., Dissemond, J., & Tan, S. (2024) · Journal of Diabetes Science and Technology · doi:10.1177/19322968221147937 · Cited by 19

Glycaemic variabilities: Key questions in pursuit of clarity

Monnier, L., Owens, D. R., Colette, C., & Bonnet, F. (2021) · Diabetes & Metabolism · doi:10.1016/j.diabet.2021.101283 · Cited by 16

Continuous Glucose Monitoring in Patients Following Simultaneous Pancreas–Kidney Transplantation: Time in Range and Glucose Variability

Дмитриев, И. В., Severina, A. S., Журавель, Н. С., Yevloyeva, M. I., Salimkhanov, R. K., Павловна, Щ. С., Bezunov, E. A., Шамхалова, М. Ш., Semenova, J. F., Klimontov, V. V., et al. (2023) · Diagnostics · doi:10.3390/diagnostics13091606 · Cited by 15

The Role of Glucagon in Glycemic Variability in Type 1 Diabetes: A Narrative Review

Guo, K., Tian, Q., Yang, L., & Zhou, Z. (2021) · Diabetes Metabolic Syndrome and Obesity · doi:10.2147/dmso.s343514 · Cited by 19

Association Between the Variability of Glycated Hemoglobin and Retinopathy in Patients with Type 2 Diabetes Mellitus: A Meta-Analysis

Zhai, L., Lü, J., Cao, X., Zhang, J., Yin, Y., & Hu, T. (2022) · Hormone and Metabolic Research · doi:10.1055/a-1931-4400 · Cited by 14

Glycemic Variability and Prognosis of Patients with Intracerebral Hemorrhage: A Meta-Analysis

Xu, J., Wang, H., Li, M., & Lu, Y. (2023) · Hormone and Metabolic Research · doi:10.1055/a-2010-2345 · Cited by 14

Role of Composite Glycemic Indices: A Comparison of the Comprehensive Glucose Pentagon Across Diabetes Types and HbA1c Levels

CHANDRAN, S. R., Vigersky, R. A., Thomas, A., Lim, L., Ratnasingam, J., Tan, A. T. B., & Gardner, D. S.-L. (2019) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2019.0277 · Cited by 14

Making sense of glucose sensors in end-stage kidney disease: A review

Williams, M. E., Steenkamp, D., & Wolpert, H. A. (2022) · Frontiers in Clinical Diabetes and Healthcare · doi:10.3389/fcdhc.2022.1025328 · Cited by 13

Statistical Packages and Algorithms for the Analysis of Continuous Glucose Monitoring Data: A Systematic Review

Olsen, M. T., Klarskov, C. K., Dungu, A. M., Hansen, K. B., Pedersen‐Bjergaard, U., & Kristensen, P. L. (2024) · Journal of Diabetes Science and Technology · doi:10.1177/19322968231221803 · Cited by 14

Standardizing Reporting of Glucose and Insulin Data for Patients on Multiple Daily Injections Using Connected Insulin Pens and Continuous Glucose Monitoring

Rodbard, D., & Garg, S. K. (2021) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2021.0030 · Cited by 13

Association of Body Fat Percentage with Time in Range Generated by Continuous Glucose Monitoring during Continuous Subcutaneous Insulin Infusion Therapy in Type 2 Diabetes

Ruan, Y., Zhong, J., Chen, R., Zhang, Z., Liu, D., Sun, J. M., & Chen, H. (2021) · Journal of Diabetes Research · doi:10.1155/2021/5551216 · Cited by 16

Glycaemia dynamics in gestational diabetes mellitus

Valero, P., Salas, R., Pardo, F., Cornejo, M., Fuentes, G., Vega, S., Grismaldo, A., Hillebrands, J., van der Beek, E. M., van Goor, H., et al. (2022) · Biochimica et Biophysica Acta (BBA) - General Subjects · doi:10.1016/j.bbagen.2022.130134 · Cited by 12

Application of medium-term metrics for assessing glucose homoeostasis: Usefulness, strengths and weaknesses

Monnier, L., Colette, C., & Owens, D. R. (2020) · Diabetes & Metabolism · doi:10.1016/j.diabet.2020.06.004 · Cited by 12

Glucose Variability and Time in Range in Type 2 Diabetes Treated with U-500R by Pump or Injection: CGM Findings from the VIVID Study

Blevins, T., Lane, W. S., Rodbard, D., Sindelar, D. K., Fan, L., Ellinor, K., Ilag, L. L., Ly, T. T., & Johnson, J. L. (2020) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2020.0030 · Cited by 12

Compensatory thalamocortical functional hyperconnectivity in type 2 Diabetes Mellitus

Wang, J., Zhou, S., Deng, D., Chen, M., Cai, H., Zhang, C., Liu, F., Luo, W., Zhu, J., & Yu, Y. (2022) · Brain Imaging and Behavior · doi:10.1007/s11682-022-00710-0 · Cited by 11

Association of Blood Glucose Variability with Sepsis-Related Disseminated Intravascular Coagulation Morbidity and Mortality

Liu, D., Fan, Y., Zhuang, Y., Hu, P. C., Gao, C., & Chen, Y. (2022) · Journal of Inflammation Research · doi:10.2147/jir.s383053 · Cited by 14

Glycemic Variability and Its Association with Traditional Glycemic Control Biomarkers in Patients with Type 1 Diabetes: A Cross-Sectional, Multicenter Study

Lazăr, S., Reurean‐Pintilei, D., Ioniță, I., Avram, V. F., Herascu, A., & Timar, B. (2025) · Journal of Clinical Medicine · doi:10.3390/jcm14072434 · Cited by 13

Glucose variability: A physiological correlate of eating disorder behaviors among individuals with binge-spectrum eating disorders

Presseller, E., Patarinski, A. G. G., Zhang, F., Page, K., Srivastava, P., Manasse, S., & Juarascio, A. (2022) · International Journal of Eating Disorders · doi:10.1002/eat.23838 · Cited by 13

Association between Intensity Levels of Physical Activity and Glucose Variability among Children and Adolescents with Type 1 Diabetes

Jaggers, J. R., King, K. M., McKay, T. E., Dyess, R. J., Thrasher, B. J., & Wintergerst, K. A. (2023) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20021623 · Cited by 10

Applications of Variability Analysis Techniques for Continuous Glucose Monitoring Derived Time Series in Diabetic Patients

Kohnert, K., Heinke, P., Vogt, L., Augstein, P., & Salzsieder, E. (2018) · Frontiers in Physiology · doi:10.3389/fphys.2018.01257 · Cited by 10

The Association Between Glycemic Variability and Myocardial Infarction: A Review and Meta-Analysis of Prospective Studies and Randomized Trials

Alatawi, Z., & Mirghani, H. O. (2020) · Cureus · doi:10.7759/cureus.11556 · Cited by 10

Proposed Practical Guidelines to Improve Glycaemic Management by Reducing Glycaemic Variability in People with Type 1 Diabetes Mellitus

de Torres-Sánchez, A., Ampudia‐Blasco, F. J., Murillo, S., Bellido, V., Amor, A. J., & Mezquita‐Raya, P. (2025) · Diabetes Therapy · doi:10.1007/s13300-025-01703-0 · Cited by 9

Glycemic Variability Assessment in Newly Treated Exocrine Pancreatic Insufficiency With Type 1 Diabetes

Lewis, D. M., & Shahid, A. (2022) · Journal of Diabetes Science and Technology · doi:10.1177/19322968221108414 · Cited by 9

Association of Long-Term HbA1c Variability with Anxiety and Depression in Patients with Type 2 Diabetes: A Cross-Sectional Retrospective Study

Shi, Q., Ding, J., Su, H., Du, Y., Pan, T., & Zhong, X. (2023) · Psychology Research and Behavior Management · doi:10.2147/prbm.s441058 · Cited by 10

Patient understanding of discharge instructions for home diabetes self-management and risk for hospital readmission and emergency department visits

Pinkhasova, D., Swami, J. B., Patel, N., Karslioglu-French, E., Hlasnik, D. S., Delisi, K. J., Donihi, A. C., Rubin, D. J., Siminerio, L. S., Wang, L., et al. (2021) · Endocrine Practice · doi:10.1016/j.eprac.2021.03.013 · Cited by 9

Influence of dipeptidyl peptidase-4 inhibitors on glycemic variability in patients with type 2 diabetes: A meta-analysis of randomized controlled trials

Chai, S., Zhang, R., Zhang, Y., Carr, R. D., Zheng, Y., Rajpathak, S. N., & Yu, M. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.935039 · Cited by 9

Glycemic Variability in Type 1 Diabetes Mellitus Pregnancies—Novel Parameters in Predicting Large-for-Gestational-Age Neonates: A Prospective Cohort Study

Lekšić, G., Baretić, M., Gudelj, L., Radić, M., Miličić, I., Ivanišević, M., & Jurišić‐Eržen, D. (2022) · Biomedicines · doi:10.3390/biomedicines10092175 · Cited by 9

The relationship between hypoglycaemia and glucose variability in type 1 diabetes

Perlman, J. E., Gooley, T. A., Meyers, J., & Hirsch, I. B. (2021) · Diabetes Obesity and Metabolism · doi:10.1111/dom.14617 · Cited by 8

Comparison of efficacy and safety of insulin degludec/liraglutide and insulin glargine U‐100/lixisenatide in individuals with type 2 diabetes mellitus using professional continuous glucose monitoring

Kawaguchi, Y., Hajika, Y., Rinka, M., Masumoto, K., Sawa, J., Hamazaki, K., & Kumeda, Y. (2024) · Journal of Diabetes Investigation · doi:10.1111/jdi.14151 · Cited by 12

Patient-Tailored Decision Support System Improves Short- and Long-Term Glycemic Control in Type 2 Diabetes

Augstein, P., Heinke, P., Vogt, L., Kohnert, K., & Salzsieder, E. (2021) · Journal of Diabetes Science and Technology · doi:10.1177/19322968211008871 · Cited by 8

Comparisons of efficacy and safety in insulin glargine and lixisenatide plus glulisine combination therapy with multiple daily injection therapy in Japanese patients with type 2 diabetes

Kawaguchi, Y., Miyamoto, S., Hajika, Y., Ashida, N., Masumoto, K., Sawa, J., Hamazaki, K., & Kumeda, Y. (2021) · Journal of Diabetes Investigation · doi:10.1111/jdi.13677 · Cited by 8

The state of variability: A vision for descriptors of glycaemia

Zhou, T., Knopp, J. L., & Chase, J. G. (2019) · Annual Reviews in Control · doi:10.1016/j.arcontrol.2019.06.004 · Cited by 8

Resistance to data loss from the Freestyle Libre: impact on glucose variability indices and recommendations for data analysis

Kingsnorth, A. P., Whelan, M., Orme, M. W., Routen, A. C., Sherar, L. B., & Esliger, D. (2020) · Applied Physiology, Nutrition, and Metabolism · doi:10.1139/apnm-2020-0386 · Cited by 8

Improved detection of decreased glucose handling capacities via continuous glucose monitoring-derived indices

Sugimoto, H., Hironaka, K., Nakamura, T., Yamada, T., Miura, H., Otowa‐Suematsu, N., Fujii, M., Hirota, Y., Sakaguchi, K., Ogawa, W., et al. (2025) · Communications Medicine · doi:10.1038/s43856-025-00819-5 · Cited by 10

Carbohydrate-Energy Replacement Following High-Intensity Interval Exercise Blunts Next-Day Glycemic Control in Untrained Women

Estafanos, S., Friesen, B., Govette, A., & Gillen, J. B. (2022) · Frontiers in Nutrition · doi:10.3389/fnut.2022.868511 · Cited by 8

Preferences for Risks and Benefits of Islet Cell Transplantation for Persons With Type 1 Diabetes With History of Episodes of Severe Hypoglycemia: A Discrete-Choice Experiment to Inform Regulatory Decisions

Wilson, L., Kwok, T., Ma, Y., Wong, J. C., Ho, M., Ionova, Y., MCGRATH, M. T., Mueller, M. M., Gitelman, S. E., & Irony, T. (2022) · Transplantation · doi:10.1097/tp.0000000000004189 · Cited by 7

Establishment of blood glucose control model in diabetic mice

Rao, C.-H., Gao, J., Du, Z.-H., & Gao, C. (2022) · International Journal of Ophthalmology · doi:10.18240/ijo.2022.12.03 · Cited by 7

Association between time in range 70-180 mg/dl in early stage and severity with in patients acute pancreatitis

Meng, C., Zhang, J., Wang, Y., Ye, X., & Zhuang, S. (2023) · BMC Endocrine Disorders · doi:10.1186/s12902-023-01414-2 · Cited by 7

Do Metrics of Temporal Glycemic Variability Reveal Abnormal Glucose Rates of Change in Type 1 Diabetes?

Richardson, R. (2024) · Journal of Diabetes Science and Technology · doi:10.1177/19322968241298248 · Cited by 7

Use of ambulatory glucose monitoring and analysis of ambulatory glucose profile in clinical practice for diabetes management; a position statement of the Arab Society of Paediatric Endocrinology and diabetes

Deeb, A., Muammar, T., Alsaffar, H., Sedaghat, S., Hassani, N. A., Odeh, R., Alkhayyat, H., Sinani, A. A., Attia, N. A., Adhami, S., et al. (2021) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2021.108671 · Cited by 7

Optimizing postprandial glucose prediction through integration of diet and exercise: Leveraging transfer learning with imbalanced patient data

Hotta, S., Kytö, M., Koivusalo, S. B., Heinonen, S. T., & Marttinen, P. (2024) · PLoS ONE · doi:10.1371/journal.pone.0298506 · Cited by 7

Prognostic effects of glycaemic variability on diastolic heart failure and type 2 diabetes mellitus: insights and 1-year mortality machine learning prediction model

Yang, Z., Li, Y., Liu, Y., Zhong, Z., Ditchfield, C., Guo, T., Yang, M., & Chen, Y. (2024) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-024-01534-2 · Cited by 6

Rational Design and Efficacy of Glucose‐Responsive Insulin Therapeutics and Insulin Delivery Systems by Computation Using Connected Human and Rodent Models

Yang, S., Yang, J., Gong, X., Weiss, M. A., & Strano, M. S. (2023) · Advanced Healthcare Materials · doi:10.1002/adhm.202300587 · Cited by 6

Performance and patients’ satisfaction with the A7+TouchCare insulin patch pump system: A randomized controlled non-inferiority study

Amadou, C., Melki, V., Allain, J., Clavel, S., Gouet, D., Chaillous, L., Catargi, B., Schaeplynck-Belicard, P., Petit, C., Thivolet, C. H., et al. (2023) · PLoS ONE · doi:10.1371/journal.pone.0289684 · Cited by 5

Are postprandial glucose responses sufficiently person-specific to use in personalized dietary advice? Design of the RepEAT study: a fully controlled dietary intervention to determine the variation in glucose responses

Daanje, M., Siebelink, E., Vrieling, F., van den Belt, M., van der Haar, S., Gerdessen, J. C., Kersten, S., Esser, D., & Afman, L. A. (2023) · Frontiers in Nutrition · doi:10.3389/fnut.2023.1281978 · Cited by 5

Continuous Glucose Monitoring in Hospitalized Patients With Type 2 Diabetes: A Step Forward in Inpatient Glycemic Control

Montenegro, A. M. R., Áñez, R., Pastor, A. G.-S., & Albarrán, O. G. (2025) · Endocrine Practice · doi:10.1016/j.eprac.2025.02.007 · Cited by 6

Long-Term Effects and Potential Impact of Early Nutrition with Breast Milk or Infant Formula on Glucose Homeostasis Control in Healthy Children at 6 Years Old: A Follow-Up from the COGNIS Study

Diéguez, E., Nieto-Ruíz, A., Sepúlveda-Valbuena, N., Herrmann, F., Agil, A., De-Castellar, R., Jiménez, J., Azaryah, H., García-Santos, J. A., García-Bermúdez, M., et al. (2023) · Nutrients · doi:10.3390/nu15040852 · Cited by 7

Gradient variability coefficient: a novel method for assessing glycemic variability and risk of hypoglycemia

Li, J., Lu, J., Igbe, T., Liu, Y., Kandwal, A., Wang, L., Ma, X., Lu, W., Bao, Y., Zhou, J., et al. (2022) · Endocrine · doi:10.1007/s12020-021-02950-4 · Cited by 6

Glycemic Variability Percentage: A Novel Method for Assessing Glycemic Variability from Continuous Glucose Monitor Data

Peyser, T. A., Balo, A. K., Buckingham, B. A., Hirsch, I. B., & Garcia, A. (2017) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2017.0187 · Cited by 90

Relationship of Glucose Variability With Glycated Hemoglobin and Daily Mean Glucose: A Post Hoc Analysis of Data From 5 Phase 3 Studies

Luo, J., Qu, Y., Zhang, Q., Chang, A. M., & Jacober, S. J. (2017) · Journal of Diabetes Science and Technology · doi:10.1177/1932296817736315 · Cited by 6

Temporal Analysis of Glycaemic Variability Metrics

Munawar, F., Donovan, J., Kiely, E., & Mulrennan, K. (2025) · International Journal of Integrated Care · doi:10.5334/ijic.icic24451

Impact of glucose variability on the assessment of the glycemia risk index (GRI) and classic glycemic metrics

Pérez-López, P., Fernández-Velasco, P., Bahillo-Curieses, P., de Luis, D. A., & Díaz-Soto, G. (2023) · Endocrine · doi:10.1007/s12020-023-03511-7 · Cited by 24