The DOI matches its Crossref record; 66 of the 67 references it cites were found in a registry or an index.
Glycemic Variability: How to Measure and Its Clinical Implication for Type 2 Diabetes
Open accessAbstract
(A1C) levels have traditionally been the gold standard for assessing glycemic control and treatment efficacy in patients with type 2 diabetes. However, A1C does not take into account fluctuations in blood glucose levels known as glycemic variability (GV). In recent years, GV has become increasingly clinically relevant, because of a better understanding of the need to reach target A1C while avoiding hypoglycemia. GV relates to both hyperglycemia and hypoglycemia, and has been associated with poorer quality of life. Diabetes treatments targeting multiple pathophysiological mechanisms are most beneficial in controlling A1C and reducing GV. In clinical trials, a number of metrics are used to measure GV, many of which are not well understood in the clinical practice. Until a gold standard metric for GV is established, the variety of measurements available may confound the choice of an optimal treatment for an individual patient.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Recent clinical data indicate that GV is associated with increased risk of hypoglycemia, microvascular and macrovascular complications, and mortality in patients with diabetes, independently of glycated hemoglobin level.”
From Glycemic variability and cardiovascular disease in patients with type 2 diabetes (2021) · cites this paper as [13]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
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
Self-citationMonnier, L., Lapinski, H., & Colette, C. (2003) · Diabetes Care · doi:10.2337/diacare.26.3.881 · Cited by 1,461
Continuous Glucose Monitoring: A Review of Successes, Challenges, and Opportunities
Rodbard, D. (2016) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2015.0417 · Cited by 768
Rosenstock, J., Davies, M., Home, P. D., Larsen, J., Koenen, C., & Schernthaner, G. (2008) · Diabetologia · doi:10.1007/s00125-007-0911-x · Cited by 447
Glycemic Variability: How Do We Measure It and Why Is It Important?
Suh, S., & Kim, J. H. (2015) · Diabetes & Metabolism Journal · doi:10.4093/dmj.2015.39.4.273 · Cited by 439
Folli, F. B., Corradi, D., Fanti, P., Davalli, A. M., Paez, A. M., Giaccari, A., Perego, C., & Muscogiuri, G. (2011) · Current Diabetes Reviews · doi:10.2174/157339911797415585 · Cited by 376
Hirakawa, Y., Arima, H., Zoungas, S., Ninomiya, T., Cooper, M., Hamet, P., Mancia, G., Poulter, N., Harrap, S., Woodward, M., et al. (2014) · Diabetes Care · doi:10.2337/dc14-0199 · Cited by 363
Evaluation of a New Measure of Blood Glucose Variability in Diabetes
Kovatchev, B. P., Otto, E., Cox, D. J., Gonder-Frederick, L. A., & Clarke, W. L. (2006) · Diabetes Care · doi:10.2337/dc06-1085 · Cited by 344
Kovatchev, B. P., Cox, D. J., Gonder-Frederick, L. A., Young-Hyman, D. L., Schlundt, D. G., & Clarke, W. L. (1998) · Diabetes Care · doi:10.2337/diacare.21.11.1870 · Cited by 309
Review of head‐to‐head comparisons of glucagon‐like peptide‐1 receptor agonists
Madsbad, S. (2016) · Diabetes, Obesity and Metabolism · doi:10.1111/dom.12596 · Cited by 305
Flagged first, then by citations
1 of the 67 references couldn’t be matched to a known paper.
Research works printed but not linked: 15
- de Ranitz-Greven, 2015, Is higher glycemic variability in type 2 diabetes patients associated with reduced quality of life?, Endocr Rev, 36, 2015
- Inzucchi, 2012, Association of measures of glycemic variability with glycemic control and hypoglycemic events, Diabetes, 61, A291
- Jangam, 2016, Reduction in glycemic variability is correlated with reductions in both hypoglycemia and hyperglycemia risk in type 1 and type 2 subjects, Diabetes Technol Ther, 18, A42
- Bailey, 2017, Within-day variability based on 9-point profiles correlates with risk of overall and nocturnal hypoglycemia in adults with type 1 (T1D) and type 2 diabetes (T2D), Diabetes, 66, A107
- McMahon, 2016, Glycometrics in 70,167 patients with type 2 diabetes derived from retrospective continuous glucose monitoring (CGM), Diabetes Technol Ther, 18, A28
- Noyes, 2016, Characteristics of patients with low and high HbA(1c) variability in type 2 diabetes, Diabetologia, 59, S61
- Beliaeva, 2013, The impact of glycemic variability on local contractility of the left ventricular in acute period of myocardial infarction, Cardiology (Switzerland), 126, 93
- Lowe, 2012, Glucose variability as a predictor of poor clinical outcomes among hospital in patients with diabetes mellitus, J Diabetes Sci Technol, 6, A16
- Pozzilli, 2016, CSII and other technologies for preventing beta cell failure in type 2 diabetes, Diabetes Technol Ther, 18, A1
- Kovatchev, 2017, The association between iglarlixi and patient satisfaction with their treatment's ability to control type 2 diabetes (T2D) is mediated by reduced glycemic variability (GV), Diabetes, 66, A624
- Yusoff, 2017, Glycaemic variability with dapagliflozin compared to saxagliptin in type 2 diabetic patients during Ramadan fasting, Endocr Rev, 38
- Vilsboll, 2015, Assessment of glycaemic control by continuous glucose monitoring in patients with type 2 diabetes treated with IDegLira, Diabetologia, 58, S401
- Bajaj, 2014, Least glucose variability is observed with the combination of a GLP-1 receptor agonist and basal insulin among four commonly used insulin regimens in type 2 diabetes, Can J Diabetes, 38, S41
- Sainsbury, 2016, Sulphonylurea use is positively and metformin inversely associated with an increased rate of hypoglycaemia, glucose variability and 5 year mortality amongst inpatients with Type 2 diabetes in a retrospective matched cohort study, Diabet Med, 33, 193
- Caffrey M. Abbott's Freestyle Libre CGM Gains Medicare Coverage. American Journal of Managed Care Website. https://www.ajmc.com/newsroom/abbotts-freestyle-libre-cgm-gains-medicare-coverage. Published January 5, 2018. Accessed July 11, 2018.
Cited by
Sorted by citations
Items 101–149 of 149
Evaluation of renal and inflammatory markers in elderly diabetic patients in Port Harcourt
Ibama, O., & Uwikor, F. K. (2025) · Academia Medicine · doi:10.20935/acadmed7708 · Cited by 2
Factors associated with high glucose variability in patients with type 1 diabetes
Klimontov, V. V., Semenova, J. F., & Korbut, A. I. (2022) · Diabetes Mellitus · doi:10.14341/dm12888 · Cited by 2
Enhancement of Ambulatory Glucose Profile for Decision Assistance and Treatment Adjustments
Satuluri, V. K. R. R., & Ponnusamy, V. (2024) · Diagnostics · doi:10.3390/diagnostics14040436 · Cited by 2
Newer Outpatient Diabetes Therapies and Technologies
Kamal, N., Lee, K., & Aleppo, G. (2024) · Medical Clinics of North America · doi:10.1016/j.mcna.2024.03.002 · Cited by 2
Al-Asadi, J. N., & Al-Naama, L. M. (2022) · Qatar medical journal · doi:10.5339/qmj.2022.32 · Cited by 2
Simonson, D. C., Testa, M. A., Ekholm, E., Su, M., Vilsbøll, T., Jabbour, S. A., & Lind, M. (2024) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgae105 · Cited by 2
Glycemic variability and diabetic cardiac autonomic neuropathy
Serhiyenko, A. A., Tsaryk, T. V., Pavlovskiy, Y., & Serhiyenko, V. A. (2024) · INTERNATIONAL JOURNAL OF ENDOCRINOLOGY (Ukraine) · doi:10.22141/2224-0721.20.4.2024.1398 · Cited by 1
Pretorius, L., Pol, K., Perenboom, C. W. M., Appleton, K. M., James, J., & Mars, M. (2025) · Journal of Nutrition · doi:10.1016/j.tjnut.2025.06.028 · Cited by 1
Tian, J., Zhao, C., Li, Y., & Han, Y. (2025) · Journal of Diabetes and its Complications · doi:10.1016/j.jdiacomp.2025.109151 · Cited by 1
Exploring Stakeholder Perceptions and Experience of Biosimilar Insulin Switching: A Scoping Review
Hindley, B., Wright, S., Ooi, C., Costa, R. D., & Cope, L. C. (2025) · Endocrinology Diabetes & Metabolism · doi:10.1002/edm2.70142 · Cited by 1
Lee, C., & Lee, S. (2026) · Exercise Science · doi:10.15857/ksep.2025.00542 · Cited by 1
Reid, E., Barrow, M., & Cutler, B. (2026) · Journal of the American Nutrition Association · doi:10.1080/27697061.2026.2632580 · Cited by 1
Kloura, C., Jensen, M. M., Ekblond, T. S., Pedersen, H., Raben, A., Clemmensen, K. K. B., Færch, K., Blond, M. B., & Quist, J. S. (2026) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2026.113276 · Cited by 1
Flabouris, K., Pearson, O. R., Morey, K., Edwards, S., Jesudason, D. R., & Marathe, C. S. (2026) · Diabetic Medicine · doi:10.1111/dme.70400 · Cited by 1
Understanding Glycemic Variability
Purandare, V. B., Bale, C., Kakrani, A. L., & Unnikrishnan, A. (2021) · Journal of Diabetology · doi:10.4103/jod.jod_3_21 · Cited by 1
Taguchi, T., Suzuki, A., & Takano, K. (2021) · Endocrine Journal · doi:10.1507/endocrj.ej21-0439 · Cited by 1
Glucose Variability Measures in Critical Care
Sadan, O., & Hall, C. L. (2022) · Biomarkers in disease · doi:10.1007/978-3-030-87302-8_24-1 · Cited by 1
Shomali, M. E., Kelly, C., Kumbara, A., Iyer, A., Park, J., & Aleppo, G. (2024) · Diabetes Spectrum · doi:10.2337/ds24-0032 · Cited by 1
Nariswari, R. P., Prabowo, G. I., Novida, H., & Hasanatuludhhiyah, N. (2021) · Journal Of The Indonesian Medical Association · doi:10.47830/jinma-vol.71.1-2021-281 · Cited by 1
Cindro, P. V., Krnić, M., Modun, D., Vuković, J., Kurir, T. T., Kardum, G., Rušić, D., Perišin, A. Š., & Bukić, J. (2022) · JMIR Formative Research · doi:10.2196/35655 · Cited by 1
Capturing glucose variability in patients with diabetes
Laight, D. W. (2020) · Prescriber · doi:10.1002/psb.1864
Biryukova, E. V., Шинкин, М. В., & Mikheeva, O. (2021) · Meditsinskiy sovet = Medical Council · doi:10.21518/2079-701x-2021-12-246-255
Quah, P. L., Tan, K. H., Razali, N. S., & Razali, N. S. (2021) · doi:10.22541/au.163843479.99686909/v1
Kerekovska, V., Boyadzhieva, M., Zlatarova, Z. I., & Hristozov, K. (2022) · Scripta Scientifica Medica · doi:10.14748/ssm.v0i0.8120
Dorcely, B., Sifonte, E., Popp, C. J., Divakaran, A., Katz, K., Musleh, S., Jagannathan, R., Curran, M., Sevick, M. A., Alemán, J. O., et al. (2022) · Research Square · doi:10.21203/rs.3.rs-1547570/v1
Real-Time Continuous Glucose Monitoring for People Living With Type 2 Diabetes
Subramonian, A., & Grobelna, A. (2022) · Canadian Journal of Health Technologies · doi:10.51731/cjht.2022.455
Glucose Variability Measures in Critical Care
Sadan, O., & Hall, C. L. (2023) · Biomarkers in disease · doi:10.1007/978-3-031-07395-3_24
Miki, K., & Saito, T. (2023) · Nihon Toseki Igakkai Zasshi · doi:10.4009/jsdt.56.109
Evaluating Time in Range as an Outcome Measure for Vildagliptin 100 mg SR OD
Bhograj, A., Sahay, R. K., Sawn, P., Warrier, S. B., Prasad, A., & Birla, A. (2022) · International Journal of Diabetes and Technology · doi:10.4103/ijdt.ijdt_14_23
Fang, M., McCoy, R. G., O’Connor, P. J., & Selvin, E. (2023) · American Public Health Association eBooks · doi:10.2105/9780875533377ch12
Efficacy and Safety of Dpp-4 Inhibitor Use in the Hospital SettingPreprint
Dass, B. (2024) · doi:10.28971/532024db66
Ahmed, Y. H., ElBadawi, H., Sultan, I. E., Mohammed, R. A., Aljedaani, H., Abozeid, H. E., & Badawy, M. I. (2024) · Cureus · doi:10.7759/cureus.60979
cgmquantify: Analyzing Glucose and Glucose Variability
Henriquez, M., & Bent, B. (2021) · doi:10.32614/cran.package.cgmquantify
Apriliany, F., Cholisah, E., Zainal, Z. A., & Umboro, R. O. (2024) · JURNAL MANAJEMEN DAN PELAYANAN FARMASI (Journal of Management and Pharmacy Practice) · doi:10.22146/jmpf.83586
de Pádua, C. S., Resende, R., do Prado, P. R., Penha‐Silva, N., & Bortolini, M. J. S. (2024) · Revista de Medicina · doi:10.11606/issn.1679-9836.v103i3e-205312
Glycation and Glucose Variability in Subjects with Type 1 Diabetes
Klimontov, V. V., Мухтаровна, Б. Д., & Semenova, J. F. (2024) · Biochemistry (Moscow) Supplement Series B Biomedical Chemistry · doi:10.1134/s1990750824600080
ANALYSIS OF FACTORS AFFECTING THE QUALITY OF LIFE OF PROLANIS PATIENT WITH TYPE 2 DIABETES MELLITUS
Handayani, D., Salsabila, J. N., Versita, R., & Pranata, M. (2024) · Medical Sains Jurnal Ilmiah Kefarmasian · doi:10.37874/ms.v9i3.1277
Evidence of use of microalgae on glycemic control and glucose metabolism
Pereira, L. (2025) · Elsevier eBooks · doi:10.1016/b978-0-443-22080-7.00035-1
Li, X., Zhang, D., Chen, Y., Ye, W., Wu, S., Lou, L., & Zhu, Y. (2022) · Figshare · doi:10.6084/m9.figshare.19643445
Bezerra, M. F., Neves, C., Neves, J. S., & Carvalho, D. (2023) · Figshare · doi:10.6084/m9.figshare.24636469
Lee, A. K. C., Tabora, J., Cheng, C. B. T., & Sy, R. A. (2022) · Philippine Journal of Internal Medicine · doi:10.65564/pjim.689866e1a8
Maillot, M. U., Amadio, A., Bonini, C., Dávila, L. R., Legnani, W. E., & Otero, D. (2025) · Biomedical Engineering Advances · doi:10.1016/j.bea.2025.100205
Glatzer, T., Peak, A., Leppäaho, E., Lustenberger, P., Herrero, P., Andorrà, M., & van Maren, E. (2026) · Journal of Diabetes Science and Technology · doi:10.1177/19322968261438523
Hu, S., Miao, Z., Dong, Y., Lai, Y., Zhang, K., Xiao, C., Chen, J., Gou, W., Fu, Y., Wang, T., et al. (2026) · EBioMedicine · doi:10.1016/j.ebiom.2026.106303
Phase-specific intraoperative glycemic control in simultaneous pancreas-kidney transplantation
Kashiv, P., Balwani, M. R., Tolani, P. R., Pasari, A. S., Saxena, K., & Kute, V. B. (2026) · World Journal of Transplantation · doi:10.5500/wjt.v16.i2.119146
Balaji, R. S., Vinith, V., Kannan, R., Ramadurai, M., & Murugan, P. (2026) · Obesity Medicine · doi:10.1016/j.obmed.2026.100724
Idrees, T., Nalabolu, S., Oladejo, O., Elshimy, G., Orobio, C., & Umpierrez, G. E. (2026) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2026-006533
Metadata
- Authors
- Umpierrez, G. E., & P. Kovatchev, B.
- Affiliations
- Emory University (US)
- Corresponding author
- Umpierrez, Guillermo E.
- Venue
- The American Journal of the Medical Sciences
- Publisher
- Elsevier BV
- Published
- 2018-12
- Volume
- 356
- Issue
- 6
- Pages
- 518-527
- ISSN
- 0002-9629 (ISSN-L)
- PMC
- PMC6709582
- OpenAlex
- W2895746197
- Cited by
- 148
- References
- 67
- Citations by year
- 2026: 10 · 2025: 12 · 2024: 23 · 2023: 25 · 2022: 31 · 2021: 27 · 2020: 13 · 2019: 7
- FWCI
- 1.88
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- The American Journal of the Medical Sciences (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health
- University of Virginia
- National Institute of Diabetes and Digestive and Kidney Diseases
- Merck
- National Center for Research Resources
- Sanofi
- Boehringer Ingelheim
- Novo Nordisk
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
- Keywords
- glycemic variability, type 2 diabetes, HbA1c, glycemic control, hypoglycemia, hyperglycemia, quality of life
- MeSH terms
- Blood Glucose, Diabetes Mellitus, Type 2, Glycated Hemoglobin, Humans, Hyperglycemia, Hypoglycemia, Treatment Outcome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
