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
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
Glycemic variability and cardiovascular disease in patients with type 2 diabetes
Martinez, M., Santamarina, J., Pavesi, A., Musso, C., & Umpierrez, G. E. (2021) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2020-002032 · Cited by 155
Self-citationGlucose 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
Interpreting blood GLUcose data with R package iglu
Broll, S., Urbanek, J. K., Buchanan, D., Chun, E., Muschelli, J., Punjabi, N. M., & Gaynanova, I. (2021) · PLoS ONE · doi:10.1371/journal.pone.0248560 · Cited by 123
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
Glycemic Variability and CNS Inflammation: Reviewing the Connection
Watt, C., RANGEL, E. S., & Hwang, J. J. (2020) · Nutrients · doi:10.3390/nu12123906 · Cited by 89
Advances in electrochemical sensors for real-time glucose monitoring
Harun-Or-Rashid, M., Aktar, M. N., Preda, V. A., & Nasiri, N. (2024) · Sensors & Diagnostics · doi:10.1039/d4sd00086b · Cited by 81
Diabetes mellitus and perioperative outcomes: a scoping review of the literature
Drayton, D. J., Birch, R. J., D'souza-Ferrer, C., Ayres, M., Howell, S. J., & Ajjan, R. (2022) · British Journal of Anaesthesia · doi:10.1016/j.bja.2022.02.013 · Cited by 74
Perspectives of glycemic variability in diabetic neuropathy: a comprehensive review
Zhang, X., Yang, X. Q., Sun, B., & Zhu, C. (2021) · Communications Biology · doi:10.1038/s42003-021-02896-3 · Cited by 54
Insulin Therapy: Future Perspectives
Cernea, S., & Raz, I. (2019) · American Journal of Therapeutics · doi:10.1097/mjt.0000000000001076 · Cited by 50
Pu, Z., Lai, L., Yang, X.-S., Wang, Y., Dong, P., Wang, D., Xie, Y., & Han, Z. (2019) · Endocrine · doi:10.1007/s12020-019-02150-1 · Cited by 41
Acute glycemic variability and risk of mortality in patients with sepsis: a meta-analysis
Li, X., Zhang, D., Chen, Y., Ye, W., Wu, S., Lou, L., & Zhu, Y. (2022) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-022-00819-8 · Cited by 40
Non-invasive wearables for remote monitoring of HbA1c and glucose variability: proof of concept
Bent, B., Cho, P. J., Wittmann, A., Thacker, C., Muppidi, S., Snyder, M. P., Crowley, M. J., Feinglos, M. N., & Dunn, J. (2021) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2020-002027 · Cited by 43
Immune Response to SARS-CoV-2 Infection in Obesity and T2D: Literature Review
Pérez, J., Ramírez, C. A. P., Cañadas, C., Aguirre, D., Pibaque, R., Bedón-Galarza, R., Sempértegui, F., Drexhage, H. A., & Baldeón, L. (2021) · Vaccines · doi:10.3390/vaccines9020102 · Cited by 34
Valenzano, M., Cibrario Bertolotti, I., Valenzano, A., & Grassi, G. (2021) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2019-001045 · Cited by 34
Leohr, J. K., Dellva, M. A., Carter, K., LaBell, E. S., & Linnebjerg, H. (2021) · Clinical Pharmacokinetics · doi:10.1007/s40262-021-01030-0 · Cited by 34
Use of continuous glucose monitoring in obesity research: A scoping review
Hegedus, E., Salvy, S., Wee, C. P., Naguib, M. N., Raymond, J. K., Fox, D. S., & Vidmar, A. P. (2021) · Obesity Research & Clinical Practice · doi:10.1016/j.orcp.2021.08.006 · Cited by 36
Kalra, S., Shaikh, S. S., Priya, G., Baruah, M., Verma, A., Das, A. K., Shah, M., Das, S., Khandelwal, D., Sanyal, D., et al. (2020) · Diabetes Therapy · doi:10.1007/s13300-020-00973-0 · Cited by 32
Karakasis, P., Patoulias, D., Kassimis, G., Koufakis, T., Klisic, A. N., Doumas, M. N., Fragakis, N., & Rizzo, M. (2024) · Current Pharmaceutical Design · doi:10.2174/0113816128304097240529053538 · Cited by 33
Leohr, J. K., Dellva, M. A., Coutant, D. E., LaBell, E. S., Heise, T., Andersen, G., Zijlstra, E., Hermanski, L., Nosek, L., & Linnebjerg, H. (2020) · Clinical Pharmacokinetics · doi:10.1007/s40262-020-00901-2 · Cited by 32
Huang, Y., Yue, L., Qiu, J., Gao, M., Liu, S., & Wang, J. (2022) · Hormone and Metabolic Research · doi:10.1055/a-1880-0978 · Cited by 31
Protein glycation in diabetes mellitus
Shin, A., Connolly, S. M., & Kabytaev, K. (2023) · Advances in clinical chemistry · doi:10.1016/bs.acc.2022.11.003 · Cited by 34
Lee, S., Min, K. W., Lee, B., Jeong, I., Yoo, S.-J., Kwon, H., Choi, Y., & Yoon, K. (2020) · Diabetes & Metabolism Journal · doi:10.4093/dmj.2019.0203 · Cited by 28
Bent, B., Henriquez, M., & Dunn, J. (2021) · IEEE Open Journal of Engineering in Medicine and Biology · doi:10.1109/ojemb.2021.3105816 · Cited by 28
Psoma, O., Makris, M., Tselepis, A. D., & Tsimihodimos, V. (2022) · Journal of Diabetes Science and Technology · doi:10.1177/19322968221146808 · Cited by 32
Chowdhury, M. H., Chowdhury, M. E. H., & Alqahtani, A. (2024) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2024.105975 · Cited by 27
Wafa, I. A., Pratama, N. R., Sofia, N. F., Anastasia, E. S., Konstantin, T., Wijaya, M. A., Wiyono, M. R., Djuari, L., & Novida, H. (2022) · Diabetes & Metabolism Journal · doi:10.4093/dmj.2021.0125 · Cited by 24
Brown, S. A., Basu, A., & Kovatchev, B. P. (2019) · Diabetic Medicine · doi:10.1111/dme.13944 · Cited by 27
Time-in-range and frequency of continuous glucose monitoring: Recommendations for South Asia
Kesavadev, J., Misra, A., Saboo, B., Agarwal, S., Sosale, A., Joshi, S., Hussain, A., Somasundaram, N. P., Basit, A., Choudhary, P., et al. (2021) · Diabetes & Metabolic Syndrome Clinical Research & Reviews · doi:10.1016/j.dsx.2021.102345 · Cited by 24
Acute glycemic variability and mortality of patients with acute stroke: a meta-analysis
Lin, J., Cai, C., Xie, Y., & Li, Y. (2022) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-022-00826-9 · Cited by 23
Krämer, A. L., Riederer, A., Fracassi, F., Boretti, F. S., Sieber‐Ruckstuhl, N. S., Lutz, T. A., Contiero, B., Zini, E., & Reusch, C. E. (2020) · Journal of Veterinary Internal Medicine · doi:10.1111/jvim.15915 · Cited by 23
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
Kim, S. H., Kim, J. Y., Kim, E. S., Park, I. R., Ha, E. Y., Chung, S. M., Moon, J. S., Yoon, J. S., Won, K. C., & Lee, H. W. (2022) · Annals of Medicine · doi:10.1080/07853890.2022.2128399 · Cited by 20
Continuous Glucose Monitoring in Dogs and Cats
Baldo, F. D., & Fracassi, F. (2023) · Veterinary Clinics of North America Small Animal Practice · doi:10.1016/j.cvsm.2023.01.008 · Cited by 20
Arnoriaga‐Rodríguez, M., Leal, Y., Mayneris‐Perxachs, J., Pérez‐Brocal, V., Moyá, A., Ricart, W., Fernández-Balsells, M., & Fernández‐Real, J. M. (2023) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgad258 · Cited by 19
Bezerra, M. F., Neves, C., Neves, J. S., & Carvalho, D. M. (2023) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-023-01219-2 · Cited by 21
Dyakov, I. N., & Zyryanov, S. K. (2021) · Kachestvennaya Klinicheskaya Praktika = Good Clinical Practice · doi:10.37489/2588-0519-2021-2-4-15 · Cited by 18
Mazzotta, F. A., Paoli, L. L., Rizzi, A., Tartaglione, L., Leo, M. L., Popolla, V., Barberio, A., Viti, L., Leo, M. A. S. D., Pontecorvi, A., et al. (2024) · Nutrition and Diabetes · doi:10.1038/s41387-024-00319-w · Cited by 24
Burslem, R., Radler, D. R., Parker, A., & Zelig, R. S. (2021) · Nutrition in Clinical Practice · doi:10.1002/ncp.10652 · Cited by 18
Oganesova, Z., Pembérton, J. H., & Brown, A. C. (2024) · Diabetic Medicine · doi:10.1111/dme.15369 · Cited by 22
Glucose variability predicts 6-month mortality in patients hospitalized with acute heart failure
Cunha, F. M., Cidade-Rodrigues, C., Elias, C., Oliveira, D., Bettencourt, P., & Lourenço, P. (2021) · Internal and Emergency Medicine · doi:10.1007/s11739-021-02719-7 · Cited by 18
HbA1c variability associated with dementia risk in people with type 2 diabetes
Moran, C., Whitmer, R. A., Dove, Z., LACY, M. E., Soh, Y., Tsai, A., Quesenberry, C. P., Karter, A. J., Adams, A. S., & Gilsanz, P. (2024) · Alzheimer s & Dementia · doi:10.1002/alz.14066 · Cited by 18
Glycemic Variability in Early Pregnancy May Predict a Subsequent Diagnosis of Gestational Diabetes
Quah, P. L., Tan, L. K., Lek, N., Thain, S. P. T., & Tan, K. H. (2022) · Diabetes Metabolic Syndrome and Obesity · doi:10.2147/dmso.s379616 · Cited by 16
Harbuwono, D. S., Kurniawan, F., Sudarsono, N. C., & Tahapary, D. L. (2020) · PLoS ONE · doi:10.1371/journal.pone.0234443 · Cited by 15
Emerging technologies for the management of type 2 diabetes mellitus
Shah, N. A., & Levy, C. J. (2021) · Journal of Diabetes · doi:10.1111/1753-0407.13188 · Cited by 17
Mphwanthe, G., Weatherspoon, D. D., Kalimbira, A. A., & Weatherspoon, L. (2020) · Social Work in Public Health · doi:10.1080/19371918.2020.1785367 · Cited by 14
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
Lacruz-Pleguezuelos, B., Bazán, G. X., Romero-Tapiador, S., Freixer, G., Tolosana, R., Daza, R., Fernández-Díaz, C. M., Molina, S., Crespo, M. C., Laguna, T., et al. (2025) · Clinical Nutrition · doi:10.1016/j.clnu.2025.03.003 · Cited by 13
GLP 1 receptor agonists, glycemic variability, oxidative stress and acute coronary syndrome
Olmo-García, M. I. D., & Merino-Torres, J. F. (2019) · Medical Hypotheses · doi:10.1016/j.mehy.2019.109504 · Cited by 15
Koracevic, G. P., Mićić, S., Stojanović, M., Tomasevic, M. V., Kostić, T. L., Koraćević, M., & Janković, I. (2020) · Primary care diabetes · doi:10.1016/j.pcd.2020.09.004 · Cited by 14
Chan, N. B., Li, W., Aung, T., Bazuaye, E., & Montero, R. (2023) · JMIR AI · doi:10.2196/45450 · Cited by 13
Schaich, C. L., Bancks, M. P., Hayden, K. M., Ding, J., Rapp, S. R., Bertoni, A. G., Heckbert, S. R., Hughes, T. M., & Mongraw‐Chaffin, M. (2023) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgad444 · Cited by 12
Zhong, H., Zhang, K., Lin, L., Yan, Y., Shen, L., Chen, H., Liang, X., Chen, J., Miao, Z., Zheng, J., et al. (2024) · Cardiovascular Diabetology · doi:10.1186/s12933-024-02409-6 · Cited by 15
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) · Endocrine · doi:10.1007/s12020-022-03109-5 · Cited by 11
Wu, W., Chai, Q., & Zhang, Z. (2021) · Molecular and Cellular Biology · doi:10.1128/mcb.00282-21 · Cited by 10
Dimova, R. B., Chakarova, N. Y., Prato, S. D., & Tankova, T. I. (2023) · Journal of Nutrition · doi:10.1016/j.tjnut.2023.03.007 · Cited by 9
Olveira, G., Abuín, J., López, R., Herránz, S., García‐Almeida, J. M., García-Malpartida, K., Ferrer, M., Cáncer, E., Pérez, L. M. L., Álvarez, J., et al. (2020) · Endocrine Practice · doi:10.4158/ep-2019-0482 · Cited by 9
Shao, D., Wang, S., Sun, J., Wang, H., & Sun, Q. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.847348 · Cited by 8
Salam, M., Bailey, R. J., Calhoun, P. M., McGill, J. B., Bergenstal, R. M., Price, D. A., & Beck, R. W. (2022) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2022.0387 · Cited by 9
Cuevas, H. E., Stuifbergen, A. M., Hilsabeck, R. C., Sales, A., Wood, S., & Kim, J. (2023) · PLoS ONE · doi:10.1371/journal.pone.0285553 · Cited by 8
Lu, J., Ou, H., Wu, C., Yang, C.-Y., Jiang, J., Lu, C., Jiang, Y., Chang, T., Chang, Y., Hsieh, M.-L., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-29791-7 · Cited by 7
Mornagui, B., Rezg, R., Neffati, F., Najjar, M. F., & Rejeb, A. (2023) · Toxicology and Industrial Health · doi:10.1177/07482337231166490 · Cited by 9
Sheng, T., Offringa, R., Kerr, D. E., Clements, M. A., Fischer, J., Parks, L. J., & Greenfield, M. (2019) · Journal of Diabetes Science and Technology · doi:10.1177/1932296819873641 · Cited by 7
Ratnasari, P. M. D., Andayani, T. M., & Endarti, D. (2020) · Jurnal Sains Farmasi & Klinis · doi:10.25077/jsfk.7.1.15-22.2020 · Cited by 7
Meng, Q.-Z., Wang, Y., Li, B., Xi, Z., Wang, M., Xiu, J.-Q., & Yang, X.-P. (2023) · World Journal of Clinical Cases · doi:10.12998/wjcc.v11.i5.1019 · Cited by 8
Individualized diabetes care: Lessons from the real-world experience
Khor, X. Y., Pappachan, J. M., & Jeeyavudeen, M. S. (2023) · World Journal of Clinical Cases · doi:10.12998/wjcc.v11.i13.2890 · Cited by 12
Olmo-García, M. I. D., Hervás, D., Caudet-Esteban, J., Martín-Portugués, A. B., Rubio, A. C., Vives, M. Á. A., Catalá-Gregori, A. I., Martínez, M. P., & Merino-Torres, J. F. (2020) · Journal of International Medical Research · doi:10.1177/0300060520926063 · Cited by 7
Risk for Imbalanced Blood Glucose Pattern: Construct Analysis and Nursing Diagnosis Proposal
Lopes, R. O. P., Santos, J. D. C., de Oliveira, H. C., Campos, J. F., Primo, C. Ç., Lopes, C. T., & Brandão, M. A. G. (2022) · Clinical Nursing Research · doi:10.1177/10547738211073395 · Cited by 7
Fathi, A. E., Ganji, M., Boiroux, D., Bengtsson, H. L., & Breton, M. D. (2023) · IEEE Conference on Control Technology and Applications (CCTA) · doi:10.1109/ccta54093.2023.10253127 · Cited by 6
Ehrhardt, N. M., Aroda, V. R., Galindo, R. J., Peters, A. L., & Shubrook, J. H. (2023) · Clinical Diabetes · doi:10.2337/cd23-0047 · Cited by 6
Dhatariya, K., Humberstone, A., Hasnat, A., Wright, R. M., Lujan, M., & Nunney, I. (2021) · Diabetes Therapy · doi:10.1007/s13300-021-01146-3 · Cited by 7
Litchfield, I. J., Barrett, T. G., Hamilton-Shield, J. P., Moore, T. H., Narendran, P., Redwood, S., Searle, A., Uday, S., Wheeler, J., & Greenfield, S. (2022) · Diabetic Medicine · doi:10.1111/dme.15035 · Cited by 8
Patients’ Perspective on Barriers to Utilization of a Diabetic Retinopathy Screening Service
Owusu-Afriyie, B., Gende, T., Tapilas, M., Zimbare, N., & Kewande, J. (2023) · Diabetology · doi:10.3390/diabetology4030033 · Cited by 8
Irace, C., Acmet, E., Cutruzzolà, A., Parise, M., Ponzani, P., Scarpitta, A. M., & Candido, R. (2023) · Endocrine · doi:10.1007/s12020-023-03605-2 · Cited by 6
Impacto de la actividad física en la variabilidad glucémica en personas con diabetes mellitus tipo 2
Astrid von Oetinger, G., Gittermann, L. M. T., & Soto, N. (2021) · Rehabilitación · doi:10.1016/j.rh.2020.11.004 · Cited by 7
Lin, J., Cai, C., & Xie, Y. (2022) · Hormone and Metabolic Research · doi:10.1055/a-1837-0141 · Cited by 5
León, D. G., Gittermann, L. M. T., Isla, N. S., Boratovic, S. R. V., & Astrid von Oetinger, G. (2022) · Endocrinología Diabetes y Nutrición (English ed ) · doi:10.1016/j.endien.2022.11.027 · Cited by 5
Cañas, J. M. H., Pontificia Universidad Javeriana, B., Gómez-Gutiérrez, M., Pontificia Universidad Javeriana, B., Ossa, A. B., & Pontificia Universidad Javeriana, B. (2023) · touchREVIEWS in Endocrinology · doi:10.17925/ee.2023.19.2.4 · Cited by 5
Schwartz, S. S., & Herman, M. E. (2024) · Frontiers in Endocrinology · doi:10.3389/fendo.2024.1394805 · Cited by 6
Cindro, P. V., Krnić, M., Modun, D., Smajić, B., & Vuković, J. (2021) · BMC Endocrine Disorders · doi:10.1186/s12902-021-00746-1 · Cited by 5
Ciechanowska, A., Góra, I. M., Sabalińska, S., Foltyński, P., & Ładyżyński, P. (2021) · Journal of Applied Biomedicine · doi:10.1016/j.bbe.2021.04.010 · Cited by 5
Glucose variability is a marker for COVID-19 severity and mortality
Abuhasira, R., & Grossman, A. (2022) · Archives of Endocrinology and Metabolism · doi:10.20945/2359-3997000000527 · Cited by 5
Construction of a QCM Biosensor for free Hemoglobin Assay
Pohanka, M. (2019) · International Journal of Electrochemical Science · doi:10.20964/2019.06.48 · Cited by 5
Zhang, S., Zhang, C., Chen, J., Deng, F., Wu, Z., Zhu, D., Chen, F., Duan, Y., Zhao, Y., & Hou, K. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2023.1171399 · Cited by 4
Screening for Impaired Glucose Homeostasis: A Novel Metric of Glycemic Control
Kaufman, J. M., VEEN, L. V., & Fossat, Y. (2023) · Mayo Clinic Proceedings Digital Health · doi:10.1016/j.mcpdig.2023.02.008 · Cited by 4
Araya, M. R., & Padilla, S. G. (2020) · Endocrinología Diabetes y Nutrición (English ed ) · doi:10.1016/j.endien.2020.04.007 · Cited by 4
The Implication of Time-in-Range for the Management of Diabetes in India: A Narrative Review
Tripathi, S., Jindal, S., Chawla, M. S., Gupta, A., Jha, S. K., Phadke, U., & Lathia, T. B. (2022) · Clinical Diabetology · doi:10.5603/dk.a2022.0018 · Cited by 4
Risco de glicemia instável em pessoas idosas com diabetes mellitus tipo 2
Stival, M. M., de Lima, L. R., da Costa, M. V. G., Volpe, C. R. G., Funghetto, S. S., & Pinho, D. L. M. (2022) · Revista de Enfermagem da UFSM · doi:10.5902/2179769271452 · Cited by 4
iglu: Interpreting Glucose Data from Continuous Glucose Monitors
Chun, E., Broll, S., Buchanan, D., Muschelli, J., Fernandes, N. J., & Gaynanova, I. (2020) · doi:10.32614/cran.package.iglu · Cited by 4
Davidsen, L., Jensen, M. H., Kronborg, T., Hangaard, S., Vestergaard, P., Drewes, A. M., Knop, F. K., Cichosz, S. L., & Olesen, S. S. (2025) · Journal of Diabetes Science and Technology · doi:10.1177/19322968251356239 · Cited by 6
Xu, Y., Chen, D., Yang, H., Zhang, Y., Huang, C., Zhong, Y., Li, H., Zhu, L., Li, C., Yan, R., et al. (2025) · Food Science & Nutrition · doi:10.1002/fsn3.71242 · Cited by 3
Lee, M., & Nam, S. (2026) · Journal of Diabetes Science and Technology · doi:10.1177/19322968251412449 · Cited by 3
Type 2 diabetes risk prediction using glycemic control Metrics: A machine learning approach
Qasrawi, R., Thwib, S., Issa, G., Ghoush, R. A., & Amro, M. (2025) · Human Nutrition & Metabolism · doi:10.1016/j.hnm.2025.200341 · Cited by 4
Araya, M. R., & Padilla, S. G. (2019) · Endocrinología Diabetes y Nutrición · doi:10.1016/j.endinu.2019.07.007 · Cited by 3
Loganadan, N. K., Huri, H. Z., Vethakkan, S. R., & Hussein, Z. B. (2021) · Pharmacogenomics · doi:10.2217/pgs-2021-0059 · Cited by 4
León, D. G., Gittermann, L. M. T., Isla, N. S., Boratovic, S. R. V., & Astrid von Oetinger, G. (2022) · Endocrinología Diabetes y Nutrición · doi:10.1016/j.endinu.2021.10.009 · Cited by 3
Ahmed, B. H., Voss, J. G., Schiltz, N. K., Naif, A. A., Ruksakulpiwat, S., & Griggs, S. A. (2024) · Clinical Nursing Research · doi:10.1177/10547738231223577 · Cited by 4
Farndon, D., Bennett, P. C., Nunney, I., & Dhatariya, K. (2024) · Annals of Vascular Surgery · doi:10.1016/j.avsg.2024.02.004 · Cited by 2
Glycemic Variability and the Risk of Diabetic Peripheral Neuropathy: A Meta-Analysis
Song, Y., Zhang, H., Sun, J., Long, Y., Zhang, K., Yin, Q., & Duan, X. (2023) · Hormone and Metabolic Research · doi:10.1055/a-2165-3579 · Cited by 2
Incretin therapy in feline diabetes mellitus – A review of the current state of research
Haller, N., & Lutz, T. A. (2024) · Domestic Animal Endocrinology · doi:10.1016/j.domaniend.2024.106869 · Cited by 3
Seufert, J., Wiesner, T., Pegelow, K., Kenzler, J., & Pfohl, M. (2025) · Diabetes Obesity and Metabolism · doi:10.1111/dom.16161 · Cited by 3
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