International consensus on use of continuous glucose monitoring
Open accessAbstract
Measurement of glycated hemoglobin (HbA1c) has been the traditional method for assessing glycemic control. However, it does not reflect intra- and interday glycemic excursions that may lead to acute events (such as hypoglycemia) or postprandial hyperglycemia, which have been linked to both microvascular and macrovascular complications. Continuous glucose monitoring (CGM), either from real-time use (rtCGM) or intermittently viewed (iCGM), addresses many of the limitations inherent in HbA1c testing and self-monitoring of blood glucose. Although both provide the means to move beyond the HbA1c measurement as the sole marker of glycemic control, standardized metrics for analyzing CGM data are lacking. Moreover, clear criteria for matching people with diabetes to the most appropriate glucose monitoring methodologies, as well as standardized advice about how best to use the new information they provide, have yet to be established. In February 2017, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address these issues. This article summarizes the ATTD consensus recommendations and represents the current understanding of how CGM results can affect outcomes.
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In many countries, the benefits and utility of CGM are now recognized by national and international medical organizations for individuals with insulin-requiring diabetes and/or those at risk for hypoglycemia.
“In many countries, the benefits and utility of CGM are now recognized by national and international medical organizations for individuals with insulin-requiring diabetes and/or those at risk for hypoglycemia (16-21).”
From Clinical Targets for Continuous Glucose Monitoring Data Interpretation: Recommendations From the International Consensus on Time in Range (2019) · cites this paper as [18]
The International Consensus recommendations say CGM should be considered for people with type 1 diabetes and for people with type 2 diabetes on intensive insulin therapy who are not meeting glucose targets, especially those with problematic hypoglycemia. This supports recognition of CGM’s utility by an international expert panel. The passages do not establish that national medical organizations in many countries recognize its benefits. (LLM, conf=0.82)
Experimental — accuracy not yet measuredCorrelations of fructosamine with HbA1c and mean blood glucose were examined in 4 observational studies.
“Correlations of fructosamine with HbA1c and mean blood glucose were examined in 4 observational studies.”
From KDIGO 2022 Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease (2022) · cites this paper as [198]
The “Limitations of HbA1c” section discusses the relationship between mean glucose and fructosamine. It does not say that four observational studies examined correlations of fructosamine with both HbA1c and mean blood glucose. (LLM, conf=0.72)
Experimental — accuracy not yet measuredThe list of core CGM metrics has now been streamlined for use in clinical practice based on the expert opinion of this International Consensus Group.
“The list of core CGM metrics has now been streamlined for use in clinical practice based on the expert opinion of this International Consensus Group (18).”
From Clinical Targets for Continuous Glucose Monitoring Data Interpretation: Recommendations From the International Consensus on Time in Range (2019) · cites this paper as [18]
The AGP recommendation was endorsed at the international consensus conference on CGM metrics and referenced in ADA 2019 Standards of Care and AACE consensus.
“This recommendation was later endorsed at the aforementioned international consensus conference on CGM metrics (18) and is referenced as an example in the American Diabetes Association (ADA) 2019 Standards of Care (16) and in an update to the American Association of Clinical Endocrinologists (AACE) consensus on use of CGM (69).”
From Clinical Targets for Continuous Glucose Monitoring Data Interpretation: Recommendations From the International Consensus on Time in Range (2019) · cites this paper as [18]
CGM helps characterize the timing, amplitude, and frequency of excursions, and provides quantitative metrics such as TIR, time in hypoglycemia (TBR) and hyperglycemia (TAR), and indices of glycemic variability, which are increasingly used as clinically meaningful targets in diabetes management.
“CGM helps characterize the timing, amplitude, and frequency of excursions [133–139], and provides quantitative metrics such as TIR, time in hypoglycemia (TBR) and hyperglycemia (TAR), and indices of glycemic variability, which are increasingly used as clinically meaningful targets in diabetes management [140–144].”
From Diabetic gastroparesis: pathophysiology and impact on insulin timing choices (2026) · cites this paper as [133]
CGM plays a central role by enabling visualization of glycemic trends and revealing patterns that are missed with capillary glucose testing.
“In this context, CGM plays a central role by enabling visualization of glycemic trends and revealing patterns that are missed with capillary glucose testing [132, 133].”
From Diabetic gastroparesis: pathophysiology and impact on insulin timing choices (2026) · cites this paper as [133]
The findings support the recent consensus conference recommendation that sensor glucose values <54 mg/dL represent a more meaningful cut-off than 70 mg/dL to define clinically important hypoglycemia.
“Our findings support the recent consensus conference recommendation (12, 13) that sensor glucose values ,54 mg/dL represent a more meaningful cut-off than 70 mg/dL to define clinically important hypoglycemia because CGM glucose levels below 54 mg/dL were uncommon, whereas most participants had some glucose levels of 55 to 69 mg/dL.”
From Continuous Glucose Monitoring Profiles in Healthy Nondiabetic Participants: A Multicenter Prospective Study (2019) · cites this paper as [12]
Current consensus conferences have somewhat arbitrarily set time in ranges for CGM sensor glucose levels for patients with T1D, with time in target identified as being between 70 to 180 mg/dL.
“The current consensus conferences have somewhat arbitrarily set time in ranges for CGM sensor glucose levels for patients with T1D, with time in target identified as being between 70 to 180 mg/dL (12,13).”
From Continuous Glucose Monitoring Profiles in Healthy Nondiabetic Participants: A Multicenter Prospective Study (2019) · cites this paper as [12]
Core glucose metrics determined by continuous glucose monitoring, including time in range and glucose management indicator, provide more precise real-time and retrospective information about glycemic control.
“Core glucose metrics determined by CGM, including TIR and GMI, provide more precise real-time and retrospective information about glycemic control.34”
From Glucose time in range and peripheral neuropathy in type 2 diabetes mellitus and chronic kidney disease (2020) · cites this paper as [34]
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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 4,032 · see citing works
Self-citationKDIGO 2020 Clinical practice guideline for diabetes management in chronic kidney disease
de Boer, I. H., Caramori, M. L., Chan, J. C. N., Heerspink, H. J. L., Hurst, C., Khunti, K., Liew, A., Michos, E. D., Navaneethan, S. D., Olowu, W. A., et al. (2020) · Kidney International · doi:10.1016/j.kint.2020.06.019 · Cited by 1,399 · see citing works
KDIGO 2022 Clinical Practice Guideline for Diabetes Management in Chronic Kidney Disease
Rossing, P., Caramori, M. L., Chan, J. C. N., Heerspink, H. J. L., Hurst, C., Khunti, K., Liew, A., Michos, E. D., Navaneethan, S. D., Olowu, W. A., et al. (2022) · Kidney International · doi:10.1016/j.kint.2022.06.008 · Cited by 1,373 · see citing works
Electrochemical glucose sensors in diabetes management: an updated review (2010–2020)
Teymourian, H., Barfidokht, A., & Wang, J. (2020) · Chemical Society Reviews · doi:10.1039/d0cs00304b · Cited by 890 · see citing works
Continuous glucose monitoring and metrics for clinical trials: an international consensus statement
Battelino, T., Alexander, C. M., Amiel, S. A., Arreaza-Rubin, G., Beck, R. W., Bergenstal, R. M., Buckingham, B. A., Carroll, J., Ceriello, A., Chow, E., et al. (2023) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(22)00319-9 · Cited by 831 · see citing works
Self-citationValidation of Time in Range as an Outcome Measure for Diabetes Clinical Trials
Beck, R. W., Bergenstal, R. M., Riddlesworth, T. D., Kollman, C., Li, Z., Brown, A. S., & Close, K. L. (2019) · Diabetes Care · doi:10.2337/dc18-1444 · Cited by 793 · see citing works
Self-citationGonzales, W. V., Mobashsher, A. T., & Abbosh, A. M. (2019) · Sensors · doi:10.3390/s19040800 · Cited by 788 · see citing works
Glucose management indicator (GMI): a new term for estimating A1C from continuous glucose monitoring
Bergenstal, R. M., Beck, R. W., Close, K. L., Grunberger, G., Sacks, D. B., Kowalski, A., Brown, A. S., Heinemann, L., Aleppo, G., Ryan, D. B., et al. (2018) · Diabetes Care · doi:10.2337/dc18-1581 · Cited by 684 · see citing works
“An international consensus group recently included the eA1C in its list of core CGMmetrics recommended for inclusion in all standard CGM reports (2).”
BackgroundSelf-citationDiMeglio, L. A., Acerini, C. L., Codner, E., Craig, M. E., Hofer, S. E., Pillay, K., & Maahs, D. M. (2018) · Pediatric Diabetes · doi:10.1111/pedi.12737 · Cited by 604 · see citing works
Self-citationGlycaemic variability in diabetes: clinical and therapeutic implications
Ceriello, A., Monnier, L., & Owens, D. (2019) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(18)30136-0 · Cited by 588 · see citing works
Martens, T., Beck, R. W., Bailey, R., Ruedy, K. J., Calhoun, P., Peters, A. L., Pop-Busui, R., Philis-Tsimikas, A., Bao, S., Umpierrez, G., et al. (2021) · JAMA · doi:10.1001/jama.2021.7444 · Cited by 543 · see citing works
Self-citationLu, J., Ma, X., Zhou, J., Zhang, L., Mo, Y., Ying, L., Lu, W., Zhu, W., Bao, Y., Vigersky, R. A., et al. (2018) · Diabetes Care · doi:10.2337/dc18-1131 · Cited by 517 · see citing works
Self-citationHeinemann, L., Freckmann, G., Ehrmann, D., Faber-Heinemann, G., Guerra, S., Waldenmaier, D., & Hermanns, N. (2018) · The Lancet · doi:10.1016/s0140-6736(18)30297-6 · Cited by 522 · see citing works
Self-citation6. Glycemic Goals and Hypoglycemia: Standards of Care in Diabetes—2024
ElSayed, N. A., Aleppo, G., Bannuru, R. R., Bruemmer, D., Collins, B. S., Ekhlaspour, L., Hilliard, M. E., Johnson, E. L., Khunti, K., Lingvay, I., et al. (2023) · Diabetes Care · doi:10.2337/dc24-s006 · Cited by 541 · see citing works
Papachristoforou, E., Lambadiari, V., Maratou, E., & Makrilakis, K. (2020) · Journal of Diabetes Research · doi:10.1155/2020/7489795 · Cited by 497 · see citing works
The relationships between time in range, hyperglycemia metrics, and HbA1c
Beck, R. W., Bergenstal, R. M., Cheng, P., Kollman, C., Carlson, A. L., Johnson, M. L., & Rodbard, D. (2019) · Journal of Diabetes Science and Technology · doi:10.1177/1932296818822496 · Cited by 479 · see citing works
Self-citationCappon, G., Vettoretti, M., Sparacino, G., & Facchinetti, A. (2019) · Diabetes & Metabolism Journal · doi:10.4093/dmj.2019.0121 · Cited by 477 · see citing works
The relationship of hemoglobin A1C to time-in-range in patients with diabetes
Vigersky, R. A., & McMahon, C. (2019) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2018.0310 · Cited by 464 · see citing works
Consensus report: definition and interpretation of remission in type 2 diabetes
Riddle, M. C., Cefalu, W. T., Evans, P. H., Gerstein, H. C., Nauck, M. A., Oh, W. K., Rothberg, A. E., le Roux, C. W., Rubino, F., Schauer, P., et al. (2021) · Diabetes Care · doi:10.2337/dci21-0034 · Cited by 464 · see citing works
Phillip, M., Nimri, R., Bergenstal, R. M., Barnard-Kelly, K., Danne, T., Hovorka, R., Kovatchev, B. P., Messer, L. H., Parkin, C. G., Ambler-Osborn, L., et al. (2023) · Endocrine Reviews · doi:10.1210/endrev/bnac022 · Cited by 443 · see citing works
Self-citationBekiari, E., Kitsios, K., Thabit, H., Tauschmann, M., Athanasiadou, E., Karagiannis, T., Haidich, A.-B., Hovorka, R., & Tsapas, A. (2018) · BMJ · doi:10.1136/bmj.k1310 · Cited by 437 · see citing works
Self-citationAgiostratidou, G., Anhalt, H., Ball, D., Blonde, L., Gourgari, E., Harriman, K. N., Kowalski, A. J., Madden, P., McAuliffe-Fogarty, A. H., McElwee-Malloy, M., et al. (2017) · Diabetes Care · doi:10.2337/dc17-1624 · Cited by 397 · see citing works
Self-citationMaiorino, M. I., Signoriello, S., Maio, A., Chiodini, P., Bellastella, G., Scappaticcio, L., Longo, M., Giugliano, D., & Esposito, K. (2020) · Diabetes Care · doi:10.2337/dc19-1459 · Cited by 364 · see citing works
Ramzy, A., Thompson, D. M., Ward-Hartstonge, K. A., Ivison, S., Cook, L., Garcia, R. V., Loyal, J., Kim, P. T. W., Warnock, G. L., Levings, M. K., et al. (2021) · Cell Stem Cell · doi:10.1016/j.stem.2021.10.003 · Cited by 342 · see citing works
7. Diabetes Technology: Standards of Care in Diabetes—2025
American Diabetes Association Professional Practice Committee, ElSayed, N. A., McCoy, R. G., Aleppo, G., Balapattabi, K., Beverly, E. A., Briggs Early, K., Bruemmer, D., Echouffo-Tcheugui, J. B., Ekhlaspour, L., et al. (2025) · Diabetes Care · doi:10.2337/dc25-s007 · Cited by 348 · see citing works
Sacks, D. B., Arnold, M., Bakris, G. L., Bruns, D. E., Horvath, A. R., Lernmark, Å., Metzger, B. E., Nathan, D. M., & Kirkman, M. S. (2023) · Diabetes Care · doi:10.2337/dci23-0036 · Cited by 351 · see citing works
Shah, V. N., DuBose, S. N., Li, Z., Beck, R. W., Peters, A. L., Weinstock, R. S., Kruger, D., Tansey, M., Sparling, D., Woerner, S., et al. (2019) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2018-02763 · Cited by 315 · see citing works
Self-citation7. Diabetes Technology: <i>Standards of Care in Diabetes</i> — <i>2023</i>
ElSayed, N. A., Aleppo, G., Aroda, V. R., Bannuru, R. R., Brown, F. M., Bruemmer, D., Collins, B. S., Hilliard, M. E., Isaacs, D., Johnson, E. L., et al. (2023) · Diabetes Care · doi:10.2337/dc23-s007 · Cited by 301 · see citing works
Wearable Devices in Cardiovascular Medicine
Hughes, A. N., Shandhi, M. M. H., Master, H., Dunn, J., & Brittain, E. L. (2023) · Circulation Research · doi:10.1161/circresaha.122.322389 · Cited by 323 · see citing works
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Self-citationGrunberger, G., Sherr, J., Allende, M., Blevins, T., Bode, B., Handelsman, Y., Hellman, R., Lajara, R., Roberts, V. L., Rodbard, D., et al. (2021) · Endocrine Practice · doi:10.1016/j.eprac.2021.04.008 · Cited by 288 · see citing works
de Boer, I. H., Caramori, M. L., Chan, J. C. N., Heerspink, H. J. L., Hurst, C., Khunti, K., Liew, A., Michos, E. D., Navaneethan, S. D., Olowu, W. A., et al. (2020) · Kidney International · doi:10.1016/j.kint.2020.06.024 · Cited by 278 · see citing works
7. Diabetes Technology: <i>Standards of Care in Diabetes—2024</i>
American Diabetes Association Professional Practice Committee, ElSayed, N. A., Aleppo, G., Bannuru, R. R., Bruemmer, D., Collins, B. S., Ekhlaspour, L., Hilliard, M. E., Johnson, E. L., Khunti, K., et al. (2024) · Diabetes Care · doi:10.2337/dc24-s007 · Cited by 281 · see citing works
Charleer, S., De Block, C., Van Huffel, L., Broos, B., Fieuws, S., Nobels, F., Mathieu, C., & Gillard, P. (2020) · Diabetes Care · doi:10.2337/dc19-1610 · Cited by 261 · see citing works
Dedov, I. I., Shestakova, M. V., Mayorov, A. Y., Vikulova, O. K., Galstyan, G. R., Кураева, Т. Л., Peterkova, V. A., Smirnova, O. M., Starostina, E. G., Surkova, E. V., et al. (2019) · Diabetes Mellitus · doi:10.14341/dm221s1 · Cited by 260 · see citing works
Glycemic variability: adverse clinical outcomes and how to improve it?
Zhou, Z. G., Sun, B., Huang, S., Zhu, C., & Bian, M. (2020) · Cardiovascular Diabetology · doi:10.1186/s12933-020-01085-6 · Cited by 257 · see citing works
7. Diabetes Technology: <i>Standards of Medical Care in Diabetes—2022</i>
American Diabetes Association Professional Practice Committee (2022) · Diabetes Care · doi:10.2337/dc22-s007 · Cited by 358 · see citing works
An Effective Model of Diabetes Care and Education: The ADCES7 Self-Care Behaviors™
Kolb, L. E. (2021) · The Science of Diabetes Self-Management and Care · doi:10.1177/0145721720978154 · Cited by 266 · see citing works
One Year Real-World Use of the Control-IQ Advanced Hybrid Closed-Loop Technology
Breton, M. D., & Kovatchev, B. P. (2021) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2021.0097 · Cited by 250 · see citing works
Self-citation7. Diabetes Technology: Standards of Medical Care in Diabetes—2020
American Diabetes Association (2019) · Diabetes Care · doi:10.2337/dc20-s007 · Cited by 254 · see citing works
Forlenza, G. P., Li, Z., Buckingham, B. A., Pinsker, J. E., Cengiz, E., Wadwa, R. P., Ekhlaspour, L., Church, M. M., Weinzimer, S. A., Jost, E., et al. (2018) · Diabetes Care · doi:10.2337/dc18-0771 · Cited by 246 · see citing works
Self-citationAdvances in technology for management of type 1 diabetes
Beck, R. W., Bergenstal, R. M., Laffel, L. M., & Pickup, J. C. (2019) · The Lancet · doi:10.1016/s0140-6736(19)31142-0 · Cited by 242 · see citing works
Self-citationŠoupal, J., Petruželková, L., Grunberger, G., Hásková, A., Flekač, M., Matoulek, M., Mikeš, O., Pelcl, T., Škrha, J., Horová, E., et al. (2020) · Diabetes Care · doi:10.2337/dc19-0888 · Cited by 242 · see citing works
Self-citationA View Beyond HbA1c: Role of Continuous Glucose Monitoring
Chehrehgosha, H., Khamseh, M. E., Malek, M., Hosseinpanah, F., & Ismail‐Beigi, F. (2019) · Diabetes Therapy · doi:10.1007/s13300-019-0619-1 · Cited by 240 · see citing works
Microneedle biomedical devices
Zheng, M., Sheng, T., Yu, J., Gu, Z., & Xu, C. (2023) · Nature Reviews Bioengineering · doi:10.1038/s44222-023-00141-6 · Cited by 239 · see citing works
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Self-citationTime in Range Is Associated with Carotid Intima-Media Thickness in Type 2 Diabetes
Lu, J., Ma, X., Shen, Y., Wu, Q. E., Wang, R., Zhang, L., Mo, Y., Lu, W., Zhu, W., Bao, Y., et al. (2019) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2019.0251 · Cited by 227 · see citing works
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Glycemic Monitoring and Management in Advanced Chronic Kidney Disease
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Self-citationPullano, S. A., Greco, M., Bianco, M. G., Foti, D., Brunetti, A., & Fiorillo, A. S. (2022) · Theranostics · doi:10.7150/thno.64035 · Cited by 210 · see citing works
7. Diabetes Technology: <i>Standards of Medical Care in Diabetes—2021</i>
American Diabetes Association (2021) · Diabetes Care · doi:10.2337/dc21-s007 · Cited by 202 · see citing works
Clinical Implications of Real-time and Intermittently Scanned Continuous Glucose Monitoring
Edelman, S. V., Argento, N. B., Pettus, J., & Hirsch, I. B. (2018) · Diabetes Care · doi:10.2337/dc18-1150 · Cited by 203 · see citing works
Self-citationWadwa, R. P., Laffel, L. M., Shah, V. N., & Garg, S. K. (2018) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2018.0150 · Cited by 197 · see citing works
Self-citationReview 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 202 · see citing works
ISPAD Clinical Practice Consensus Guidelines 2018: diabetes technologies
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Self-citationCharleer, S., Mathieu, C., Nobels, F., De Block, C., Radermecker, R. P., Hermans, M. P., Taes, Y., Vercammen, C., T'Sjoen, G., Crenier, L., et al. (2018) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2017-02498 · Cited by 196 · see citing works
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Galindo, R. J., Migdal, A. L., Davis, G. M., Urrutia, M. A., Albury, B., Zambrano, C., Vellanki, P., Pasquel, F. J., Fayfman, M., Peng, L., et al. (2020) · Diabetes Care · doi:10.2337/dc19-2073 · Cited by 181 · see citing works
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Open-source automated insulin delivery in type 1 diabetes
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7. Diabetes Technology: <i>Standards of Medical Care in Diabetes—2019</i>
American Diabetes Association (2019) · Diabetes Care · doi:10.2337/dc19-s007 · Cited by 179 · see citing works
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Positioning time in range in diabetes management
Advani, A. (2020) · Diabetologia · doi:10.1007/s00125-019-05027-0 · Cited by 170 · see citing works
Heinemann, L., Schoemaker, M., Schmelzeisen-Redecker, G., Hinzmann, R., Kassab, A., Freckmann, G., Reiterer, F., & Del Re, L. (2020) · Journal of Diabetes Science and Technology · doi:10.1177/1932296819855670 · Cited by 170 · see citing works
Self-citationSun, B., Luo, Z., & Zhou, J. (2021) · Cardiovascular Diabetology · doi:10.1186/s12933-020-01200-7 · Cited by 168 · see citing works
Flash forward: a review of flash glucose monitoring
Leelarathna, L., & Wilmot, E. G. (2018) · Diabetic Medicine · doi:10.1111/dme.13584 · Cited by 169 · see citing works
RSSDI-ESI clinical practice recommendations for the management of type 2 diabetes mellitus 2020
Madhu, S., Chawla, R., Makkar, B. M., Ghosh, S. K., Saboo, B., & Kalra, S. (2020) · Indian Journal of Endocrinology and Metabolism · doi:10.4103/ijem.ijem_225_20 · Cited by 175 · see citing works
Self-citationVisser, M. M., Charleer, S., Fieuws, S., De Block, C., Hilbrands, R., Van Huffel, L., Maes, T., Vanhaverbeke, G., Dirinck, E., Myngheer, N., et al. (2021) · The Lancet · doi:10.1016/s0140-6736(21)00789-3 · Cited by 165 · see citing works
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Self-citationTechnology in the management of type 1 diabetes mellitus — current status and future prospects
Tauschmann, M., & Hovorka, R. (2018) · Nature Reviews Endocrinology · doi:10.1038/s41574-018-0044-y · Cited by 161 · see citing works
Self-citationDeng, Y., Lu, L., Aponte, L., Angelidi, A. M., Novak, V., Karniadakis, G. E., & Mantzoros, C. S. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00480-x · Cited by 152 · see citing works
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 · see citing works
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Glucose Variability: A Review of Clinical Applications and Research Developments
Rodbard, D. (2018) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2018.0092 · Cited by 154 · see citing works
Sacks, D. B., Arnold, M. A., Bakris, G. L., Bruns, D. E., Horvath, A. R., Lernmark, Å., Metzger, B. E., Nathan, D. M., & Kirkman, M. S. (2023) · Clinical Chemistry · doi:10.1093/clinchem/hvad080 · Cited by 157 · see citing works
Glycemic variability: how to measure and its clinical implication for type 2 diabetes
Umpierrez, G. E., & P. Kovatchev, B. (2018) · The American Journal of the Medical Sciences · doi:10.1016/j.amjms.2018.09.010 · Cited by 148 · see citing works
Self-citationIoMT-Enabled Real-Time Blood Glucose Prediction With Deep Learning and Edge Computing
Zhu, T., Kuang, L., Daniels, J., Herrero, P., Li, K., & Georgiou, P. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3143375 · Cited by 154 · see citing works
Hásková, A., Radovnická, L., Petruželková, L., Parkin, C. G., Grunberger, G., Horová, E., Navrátilová, V., Kádě, O., Matoulek, M., Prázný, M., et al. (2020) · Diabetes Care · doi:10.2337/dc20-0112 · Cited by 146 · see citing works
Self-citationManagement of hypoglycemia in older adults with type 2 diabetes
Freeman, J. S. (2019) · Postgraduate Medicine · doi:10.1080/00325481.2019.1578590 · Cited by 144 · see citing works
Glycaemic management in diabetes: old and new approaches
Ceriello, A., Prattichizzo, F., Phillip, M., Hirsch, I. B., Mathieu, C., & Battelino, T. (2021) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(21)00245-x · Cited by 146 · see citing works
Self-citationAdolfsson, P., Hartvig, N. V., Kaas, A., Møller, J. B., & Hellman, J. (2020) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2019.0411 · Cited by 139 · see citing works
Checkpoint Inhibitor–Associated Autoimmune Diabetes Is Distinct From Type 1 Diabetes
Tsang, V., McGrath, R. T., Clifton-Bligh, R. J., Scolyer, R. A., Jakrot, V., Guminski, A. D., Long, G. V., & Menzies, A. M. (2019) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2019-00423 · Cited by 140 · see citing works
Gerbaud, E., Darier, R., Montaudon, M., Beauvieux, M.-C., Coffin-Boutreux, C., Coste, P., Douard, H., Ouattara, A., & Catargi, B. (2019) · Diabetes Care · doi:10.2337/dc18-2047 · Cited by 138 · see citing works
Berget, C., Messer, L. H., Vigers, T., Frohnert, B. I., Pyle, L. L., Wadwa, R. P., Driscoll, K. A., & Forlenza, G. P. (2019) · Pediatric Diabetes · doi:10.1111/pedi.12962 · Cited by 138 · see citing works
Continuous glucose monitoring: The achievement of 100 years of innovation in diabetes technology
Galindo, R. J., & Aleppo, G. (2020) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2020.108502 · Cited by 138 · see citing works
Sherr, J. L., Heinemann, L., Fleming, G. A., Bergenstal, R. M., Bruttomesso, D., Hanaire, H., Holl, R. W., Petrie, J. R., Peters, A. L., & Evans, M. (2022) · Diabetes Care · doi:10.2337/dci22-0018 · Cited by 136 · see citing works
Self-citationYogev, D., Goldberg, T., Arami, A., Tejman‐Yarden, S., Winkler, T. E., & Maoz, B. M. (2023) · APL Bioengineering · doi:10.1063/5.0152290 · Cited by 143 · see citing works
Wang, P., & Kricka, L. J. (2018) · Clinical Chemistry · doi:10.1373/clinchem.2018.287052 · Cited by 131 · see citing works
Law, G. R., Alnaji, A., Alrefaai, L., Endersby, D., Cartland, S. J., Gilbey, S. G., Jennings, P. E., Murphy, H. R., & SCOTT, E. M. (2019) · Diabetes Care · doi:10.2337/dc18-2212 · Cited by 131 · see citing works
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 131 · see citing works
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Self-citationTime in range: a new parameter to evaluate blood glucose control in patients with diabetes
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Improving pregnancy outcomes in women with diabetes mellitus: modern management
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Self-citationContinuous Glucose Monitoring: A Brief Review for Primary Care Practitioners
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Consensus report: definition and interpretation of remission in type 2 diabetes
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- Authors
- Danne, T., Nimri, R., Battelino, T., Bergenstal, R. M., Close, K. L., DeVries, J. H., Garg, S., Heinemann, L., Hirsch, I., Amiel, S. A., Beck, R., Bosi, E., Buckingham, B., Cobelli, C., Dassau, E., Doyle, F. J., Heller, S., Hovorka, R., Jia, W., Jones, T., Kordonouri, O., Kovatchev, B., Kowalski, A., Laffel, L., Maahs, D., Murphy, H. R., Nørgaard, K., Parkin, C. G., Renard, E., Saboo, B., Scharf, M., Tamborlane, W. V., Weinzimer, S. A., & Phillip, M.
- Affiliations
- Kinderkrankenhaus auf der Bult (DE)
- Schneider Children's Medical Center (IL)
- University of Ljubljana (SI)
- Park Nicollet Health Services (US)
- Close Concerns (United States) (US)
- Amsterdam UMC Location University of Amsterdam (NL)
- University of Colorado Denver (US)
- Science & Co, Düsseldorf, Germany
- University of Washington (US)
- King's College London (GB)
- Jaeb Center for Health Research (US)
- Vita-Salute San Raffaele University (IT)
- Stanford Medicine (US)
- University of Padua (IT)
- Harvard University (US)
- University of Sheffield (GB)
- University of Cambridge (GB)
- Shanghai Jiao Tong University (CN)
- Telethon Kids Institute and School of Paediatrics and Child Health, The University of Western Australia, and Department of Endocrinology and Diabetes, Princess Margaret Hospital for Children, Perth, Australia
- University of Virginia (US)
- Breakthrough T1D (US)
- Joslin Diabetes Center (US)
- University of East Anglia (GB)
- Hvidovre Hospital (DK)
- CGParkin Communications, Boulder City, NV
- Department of Endocrinology, Diabetes, and Nutrition, Montpellier University Hospital, and Institute of Functional Genomics, University of Montpellier, and INSERM Clinical Investigation Centre, Montpellier, France
- DiaCare, Ahmedabad, Gujarat, India
- Hospital Nossa Senhora das Graças (BR)
- Yale University (US)
- Corresponding author
- Danne, Thomas
- ORCID
- Danne, Thomas
- Nimri, Revital
- Battelino, Tadej
- Bergenstal, Richard M.
- Close, Kelly L.
- DeVries, J. Hans
- Garg, Satish
- Heinemann, Lutz
- Hirsch, Irl
- Amiel, Stephanie A.
- Beck, Roy
- Bosi, Emanuele
- Buckingham, Bruce
- Cobelli, Claudio
- Dassau, Eyal
- Doyle, Francis J.
- Heller, Simon
- Hovorka, Roman
- Jia, Weiping
- Jones, Tim
- Kordonouri, Olga
- Kovatchev, Boris
- Kowalski, Aaron
- Laffel, Lori
- Maahs, David
- Murphy, Helen R.
- Nørgaard, Kirsten
- Parkin, Christopher G.
- Saboo, Banshi
- Tamborlane, William V.
- Weinzimer, Stuart A.
- Phillip, Moshe
- Venue
- Diabetes Care
- Publisher
- American Diabetes Association
- Published
- 2017-11-10
- Volume
- 40
- Issue
- 12
- Pages
- 1631-1640
- ISSN
- 0149-5992 (ISSN-L)
- 1935-5548
- PMC
- PMC6467165
- OpenAlex
- W2770616601
- Cited by
- 2,069
- References
- 82
- Citations by year
- 2026: 175 · 2025: 227 · 2024: 241 · 2023: 247 · 2022: 281 · 2021: 298 · 2020: 271 · 2019: 210 · 2018: 110 · 2017: 2 · 2016: 1 · 2014: 1
- FWCI
- 128.71
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Diabetes Care (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion, other-oa)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion, other-oa)
- UWA Profiles and Research Repository (UWA) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- HAL (submittedVersion)
- Archivio Istituzionale della Ricerca - Università Vita-Salute San Raffaele (submittedVersion)
- Apollo (University of Cambridge) (submittedVersion)
- Apollo
- Funders
- American Diabetes Association
- Abbott Laboratories
- Bristol-Myers Squibb
- Eli Lilly and Company
- AstraZeneca
- Sanofi
- Leona M. and Harry B. Helmsley Charitable Trust
- Bigfoot Biomedical
- Insulet Corporation
- Dexcom
- Jaeb Center for Health Research
- National Institute for Health and Care Research (NF-SI-0515-10079, CDF-2013-06-035)
- Bayer HealthCare
- Novo Nordisk
- Roche Diabetes Care
- Abbott Diabetes Care
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK116074)
- 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
- continuous glucose monitoring, glycemic control, HbA1c, HbA1c limitations, hypoglycemia, postprandial hyperglycemia, diabetes management, real-time CGM, diabetes complications, expert consensus recommendations
- MeSH terms
- Blood Glucose, Clinical Trials as Topic, Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2, Glycated Hemoglobin, Humans, Hyperglycemia, Hypoglycemia, Hypoglycemic Agents, Insulin, International Agencies, Physicians, Reference Standards, Research Personnel, Blood Glucose Self-Monitoring, Consensus
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 ›
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