Cited by 131Diabetes Management and ResearchDiabetes Management and EducationDiabetes Treatment and Management

The DOI matches its Crossref record; 11 of the 12 references it cites were found in a registry or an index.

Optimal Sampling Intervals to Assess Long-Term Glycemic Control Using Continuous Glucose Monitoring

Open access

Xing, Dongyuan, Kollman, Craig, Beck, Roy W., Tamborlane, William V., Laffel, Lori, Buckingham, Bruce A., Wilson, Darrell M., Weinzimer, Stuart, Fiallo-Scharer, Rosanna, Ruedy for the Juvenile Diabetes Research Foundation Continuo, Katrina J.·2011·Diabetes Technology & Therapeutics

DOI 10.1089/dia.2010.0156PMC PMC6468940

Open this paper in CoChat — free account

Abstract

AIMS AND HYPOTHESIS: The optimal duration and frequency of short-term continuous glucose monitoring (CGM) to reflect long-term glycemia have not been determined. The Juvenile Diabetes Research Foundation CGM randomized trials provided a large dataset of longitudinal CGM data for this type of analysis. METHODS: The analysis included 185 subjects who had 334 3-month intervals of CGM data meeting specific criteria. For various glucose indices, correlations (r²) were computed for the entire 3-month interval versus selected sampling periods ranging from 3 to 15 days. Other computed agreement measures included median relative absolute difference, values within ± 10% and ± 20% of full value, and median absolute difference. RESULTS: As would be expected, the more days of glucose data that were sampled, the higher the correlation with the full 3 months of data. For 3 days of sampling, the r² value ranged from 0.32 to 0.47, evaluating mean glucose, percentage of values 71-180 mg/dL, percentage of values > 180 mg/dL, percentage of values ≤ 70 mg/dL, and coefficient of variation; in contrast, for 15 days of sampling, the r² values ranged from 0.66 to 0.75. The results were similar when the analysis intervals were stratified by age group (8-14, 15-24, and ≥ 25 years), by baseline hemoglobin A1c level (< 7.0% and ≥ 7.0%), and by CGM device type. CONCLUSIONS AND INTERPRETATION: Our data suggest that a 12-15-day period of monitoring every 3 months may be needed to optimally assess overall glucose control. Shorter periods of sampling can be useful, but the correlation with 3-month measures of glycemic control is lower.

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

Crossref · 10.1089/dia.2010.0156

Cites

11 of 11 references verified0 citation errors · 0 not checkable

Statistics

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?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Translating the A1C assay into estimated average glucose values
Nathan, D. M., Kuenen, J., Borg, R., Zheng, H., Schoenfeld, D., Heine, R. J., & for the A1c-Derived Average Glucose (ADAG) Study Group (2008) · Diabetes Care · doi:10.2337/dc08-0545 · Cited by 1,812
Continuous glucose monitoring and intensive treatment of type 1 diabetes
(2008) · New England Journal of Medicine · doi:10.1056/nejmoa0805017 · Cited by 1,559
The effect of continuous glucose monitoring in well-controlled type 1 diabetes
Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group (2009) · Diabetes Care · doi:10.2337/dc09-0108 · Cited by 399
Effectiveness of Continuous Glucose Monitoring in a Clinical Care Environment
Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group (2010) · Diabetes Care · doi:10.2337/dc09-1502 · Cited by 313
Alarms Based on Real-Time Sensor Glucose Values Alert Patients to Hypo- and Hyperglycemia: The Guardian Continuous Monitoring System
Bode, B. W., Gross, K. M., Rikalo, N., Schwartz, S. L., Wahl, T. O., Page, C. W., Gross, T. M., & Mastrototaro, J. J. (2004) · Diabetes Technology & Therapeutics · doi:10.1089/152091504773731285 · Cited by 190
Continuous Glucose Monitoring in Youth with Type 1 Diabetes: 12-Month Follow-Up of the Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Randomized Trial
Chase, H. P., Beck, R. W., Xing, D., Tamborlane, W. V., Coffey, J., Fox, L. A., Ives, B., Keady, J., Kollman, C., Laffel, L. M., et al. (2010) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2010.0021 · Cited by 142
The Accuracy of the FreeStyle Navigator Continuous Glucose Monitoring System in Children With Type 1 Diabetes
Wilson, D. M., Beck, R. W., Tamborlane, W. V., Dontchev, M., Kollman, C., Chase, P., Fox, L. A., Ruedy, K. J., Tsalikian, E., WEINZIMER, S. A., et al. (2006) · Diabetes Care · doi:10.2337/dc06-1407 · Cited by 134
Sustained Benefit of Continuous Glucose Monitoring on A1C, Glucose Profiles, and Hypoglycemia in Adults With Type 1 Diabetes
The Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group (2009) · Diabetes Care · doi:10.2337/dc09-0846 · Cited by 121
JDRF Randomized Clinical Trial to Assess the Efficacy of Real-Time Continuous Glucose Monitoring in the Management of Type 1 Diabetes: Research Design and Methods
JDRF CGM Study Group (2008) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2007.0302 · Cited by 115
Eight-Point Glucose Testing Versus the Continuous Glucose Monitoring System in Evaluation of Glycemic Control in Type 1 Diabetes
The Diabetes Research in Children Network (DirecNet) Study Group (2005) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2004-2510 · Cited by 88

Flagged first, then by citations

Show all 12 references

1 of the 12 references couldn’t be matched to a known paper.

Research works printed but not linked: 3

Bugler J. An estimation of the amount of data required to measure glycemic variability. Presented at the Advanced Technologies and Treatment for Diabetes Conference, Prague, Czech Republic, 2008.
DexCom Inc. DexCom™ STS™ Continuous Glucose Monitoring System User's Guide. San Diego, CA: DexCom Inc., 2006; 86–102.
Magee L. R2 measures based on Wald and Likelihood Ratio Joint Significance tests. Am Stat, 1990; 44:250–253.

Sorted by citations

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
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
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
Validation 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
The fallacy of average: how using HbA1c alone to assess glycemic control can be misleading
Beck, R. W., Connor, C. G., Mullen, D. M., Wesley, D. M., & Bergenstal, R. M. (2017) · Diabetes Care · doi:10.2337/dc17-0636 · Cited by 477
Self-citation
Continuous glucose monitoring: a review of recent studies demonstrating improved glycemic outcomes
Rodbard, D. (2017) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2017.0035 · Cited by 458
Racial Differences in the Relationship of Glucose Concentrations and Hemoglobin A1c Levels
Bergenstal, R. M., Gal, R. L., Connor, C. G., Gubitosi-Klug, R., Kruger, D., Olson, B. A., Willi, S. M., Aleppo, G., Weinstock, R. S., Wood, J., et al. (2017) · Annals of Internal Medicine · doi:10.7326/m16-2596 · Cited by 306
American Association of Clinical Endocrinology clinical practice guideline: the use of advanced technology in the management of persons with diabetes mellitus
Grunberger, 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
Time in Range in Relation to All-Cause and Cardiovascular Mortality in Patients With Type 2 Diabetes: A Prospective Cohort Study
Lu, J., Wang, C., Shen, Y., Chen, L., Zhang, L., Cai, J., Lu, W., Zhu, W., Hu, G., Xia, T., et al. (2021) · Diabetes Care · doi:10.2337/dc20-1862 · Cited by 282
Optimal Sampling Duration for Continuous Glucose Monitoring to Determine Long-Term Glycemic Control
Riddlesworth, T. D., Beck, R. W., Gal, R. L., Connor, C. G., Bergenstal, R. M., Lee, S., & Willi, S. M. (2018) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2017.0455 · Cited by 266
Time 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 230
Clinical Use of Continuous Glucose Monitoring in Adults with Type 2 Diabetes
Carlson, A. L., Mullen, D. M., & Bergenstal, R. M. (2017) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2017.0024 · Cited by 181
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
Prevention of Hypoglycemia by Using Low Glucose Suspend Function in Sensor-Augmented Pump Therapy
Danne, T., Kordonouri, O., Holder, M., Haberland, H., Golembowski, S., Remus, K., Bläsig, S., Wadien, T., Zierow, S., Hartmann, R., et al. (2011) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2011.0084 · Cited by 150
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 144
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
Association Between Continuous Glucose Monitoring-Derived Time in Range, Other Core Metrics, and Albuminuria in Type 2 Diabetes
Yoo, J. H., Choi, M. S., Ahn, J., Park, S. W., Kim, Y., Hur, K. Y., Jin, S., Kim, G., & Kim, J. H. (2020) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2019.0499 · Cited by 102
Time in Range from Continuous Glucose Monitoring: A Novel Metric for Glycemic Control
Yoo, J. H., & Kim, J. H. (2020) · Diabetes & Metabolism Journal · doi:10.4093/dmj.2020.0257 · Cited by 98
Improved Accuracy of Continuous Glucose Monitoring Systems in Pediatric Patients with Diabetes Mellitus: Results from Two Studies
Laffel, L. M. (2016) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2015.0380 · Cited by 86
Improved time in range over 1 year is associated with reduced albuminuria in individuals with sensor-augmented insulin pump-treated type 1 diabetes
Ranjan, A. G., Rosenlund, S. V., Hansen, T. W., Rossing, P., Andersen, S., & Nørgaard, K. (2020) · Diabetes Care · doi:10.2337/dc20-0909 · Cited by 72
Associations between HbA1c and continuous glucose monitoring‐derived glycaemic variables
Hirsch, I. B., Welsh, J. B., Calhoun, P. M., Puhr, S., Walker, T. C., & Price, D. A. (2019) · Diabetic Medicine · doi:10.1111/dme.14065 · Cited by 63
International Society for Pediatric and Adolescent Diabetes Clinical Practice Consensus Guidelines 2024 Diabetes Technologies: Glucose Monitoring
Tauschmann, M., Cardona‐Hernandez, R., DeSalvo, D. J., Hood, K. K., Лаптев, Д. Н., Olinder, A. L., Wheeler, B. J., & Smart, C. E. (2025) · Hormone Research in Paediatrics · doi:10.1159/000543156 · Cited by 69
Considerations to address missing data when deriving clinical trial endpoints from digital health technologies
Di, J., Demanuele, C., Kettermann, A. E., Karahanoğlu, F. I., Cappelleri, J. C., Potter, A., Bury, D. P., Cedarbaum, J. M., & Byrom, B. (2021) · Contemporary Clinical Trials · doi:10.1016/j.cct.2021.106661 · Cited by 57
Glycemic variability modifies the relationship between time in range and hemoglobin A1c estimated from continuous glucose monitoring: a preliminary study
Lu, J., Ma, X., Zhang, L., Mo, Y., Lu, W., Zhu, W., Bao, Y., Jia, W., & Zhou, J. (2020) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2020.108032 · Cited by 49
Time-in-range for monitoring glucose control: Is it time for a change?
Bellido, V., Pinés-Corrales, P. J., Villar‐Taibo, R., & Ampudia‐Blasco, F. J. (2021) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2021.108917 · Cited by 49
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
Robust Determination of the Optimal Continuous Glucose Monitoring Length of Intervention to Evaluate Long-Term Glycemic Control
Herrero, P., Alalitei, A., Reddy, M., Georgiou, P., & Oliver, N. S. (2020) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2020.0387 · Cited by 44
Essential Continuous Glucose Monitoring Metrics: The Principal Dimensions of Glycemic Control in Diabetes
Montaser, E., Fabris, C., & Kovatchev, B. P. (2022) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2022.0104 · Cited by 44
Glucose Variability Assessed with Continuous Glucose Monitoring: Reliability, Reference Values, and Correlations with Established Glycemic Indices—The Maastricht Study
Foreman, Y. D., Brouwers, M. C. G. J., Kallen, C., Pagen, D. M. E., van Greevenbroek, M. M. J., Henry, R. M. A., Koster, A., Wesselius, A., Schaper, N. C., & Stehouwer, C. D. A. (2019) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2019.0385 · Cited by 42
Assessment of glycemia in chronic kidney disease
Hassanein, M., & Shafi, T. (2022) · BMC Medicine · doi:10.1186/s12916-022-02316-1 · Cited by 44
A Comparison of Two Hybrid Closed-Loop Systems in Italian Children and Adults With Type 1 Diabetes
Bassi, M., Teliti, M., Lezzi, M., Iosca, A., Strati, M. F., Carmisciano, L., d’Annunzio, G., Minuto, N., & Maggi, D. C. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2021.802419 · Cited by 35
Continuous glucose monitoring in adults with type 1 diabetes with 35 years duration from the DCCT/EDIC study
Gubitosi-Klug, R. A., Braffett, B. H., Bebu, I., Johnson, M. L., Farrell, K., Kenny, D., Trapani, V. R., Meadema-Mayer, L., Soliman, E. Z., Pop-Busui, R., et al. (2022) · Diabetes Care · doi:10.2337/dc21-0629 · Cited by 31
Multilevel clustering approach driven by continuous glucose monitoring data for further classification of type 2 diabetes
Tao, R., Yu, X., Lu, J., Shen, Y., Lu, W., Zhu, W., Bao, Y., Li, H., & Zhou, J. (2021) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2020-001869 · Cited by 31
Reduction of hypoglycaemia, lifestyle modifications and psychological distress during lockdown following SARS‐CoV‐2 outbreak in type 1 diabetes
Caruso, I., Molfetta, S. D., Guarini, F., Giordano, F., Cignarelli, A., Natalicchio, A., Perrini, S., Leonardini, A., Giorgino, F., & Laviola, L. (2020) · Diabetes/Metabolism Research and Reviews · doi:10.1002/dmrr.3404 · Cited by 27
Effect of Short-Term iPRO Continuous Glucose Monitoring on Hemoglobin A1c Levels in Clinical Practice
Pepper, G. M., Steinsapir, J., & Reynolds, K. (2012) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2012.0030 · Cited by 26
Reproducibility of continuous glucose monitoring results under real-life conditions in an adult population: a functional data analysis
Matabuena, M., Pazos-Couselo, M., Alonso‐Sampedro, M., Fernández‐Merino, C., González‐Quintela, A., & Gudé, F. (2023) · Scientific Reports · doi:10.1038/s41598-023-40949-1 · Cited by 28
Benefits of Short-Term Professional Continuous Glucose Monitoring in Clinical Practice
Leinung, M. C., Nardacci, E., Patel, N., Bettadahalli, S., Paika, K., & Thompson, S. (2013) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2013.0027 · Cited by 26
Correlation Among Hypoglycemia, Glycemic Variability, and C-Peptide Preservation After Alefacept Therapy in Patients with Type 1 Diabetes Mellitus: Analysis of Data from the Immune Tolerance Network T1DAL Trial
Pinckney, A., Rigby, M. R., Keyes-Elstein, L., Soppe, C. L., Nepom, G. T., & Ehlers, M. R. (2016) · Clinical Therapeutics · doi:10.1016/j.clinthera.2016.04.032 · Cited by 26
Impact of Different Types of Data Loss on Optimal Continuous Glucose Monitoring Sampling Duration
Aktürk, H. K., Herrero, P., Oliver, N. S., Wise, H., Eikermann, E., Snell‐Bergeon, J. K., & Shah, V. N. (2022) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2022.0093 · Cited by 25
Low-Dose Empagliflozin as Adjunct to Hybrid Closed-Loop Insulin Therapy in Adults With Suboptimally Controlled Type 1 Diabetes: A Randomized Crossover Controlled Trial
Pasqua, M., Jafar, A., Kobayati, A., Tsoukas, M. A., & Haidar, A. (2022) · Diabetes Care · doi:10.2337/dc22-0490 · Cited by 25
Strategies for clinical trials in type 1 diabetes
Ehlers, M. R. (2016) · Journal of Autoimmunity · doi:10.1016/j.jaut.2016.03.008 · Cited by 25
Comparison of glucose time in range and area under curve in range in relation to risk of diabetic retinopathy in type 2 diabetes patients
Wang, Y., Lu, J., Shen, Y., Ni, J., Zhang, L., Lu, W., Zhu, W., Bao, Y., & Zhou, J. (2022) · Journal of Diabetes Investigation · doi:10.1111/jdi.13811 · Cited by 23
Beyond A1C: exploring continuous glucose monitoring metrics in managing diabetes
Friedman, J. G., Coyne, K., Aleppo, G., & Szmuilowicz, E. D. (2023) · Endocrine Connections · doi:10.1530/ec-23-0085 · Cited by 22
Time in range—A new gold standard in type 2 diabetes research?
Goshrani, A., Lin, R., O'Neal, D. N., & Ekinci, E. I. (2025) · Diabetes Obesity and Metabolism · doi:10.1111/dom.16279 · Cited by 25
Impacts of glycemic variability on the relationship between glucose management indicator from iPro ™ 2 and laboratory hemoglobin A1c in adult patients with type 1 diabetes mellitus
Liu, H., Yang, D., Deng, H., Xu, W., Lv, J., Zhou, Y., Luo, S., Zheng, X., Liang, H., Yao, B., et al. (2020) · Therapeutic Advances in Endocrinology and Metabolism · doi:10.1177/2042018820931664 · Cited by 22
A head‐to‐head comparison of personal and professional continuous glucose monitoring systems in people with type 1 diabetes: Hypoglycaemia remains the weak spot
Moser, O., Pandis, M., Aberer, F., Kojzar, H., Hochfellner, D. A., Elsayed, H., Motschnig, M., Augustin, T., Kreuzer, P., Pieber, T. R., et al. (2018) · Diabetes Obesity and Metabolism · doi:10.1111/dom.13598 · Cited by 22
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
Identifying Continuous Glucose Monitoring Data Using Machine Learning
Herrero, P., Reddy, M., Georgiou, P., & Oliver, N. S. (2022) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2021.0498 · Cited by 19
Assessment of Hyperglycemia, Hypoglycemia and Inter-Day Glucose Variability Using Continuous Glucose Monitoring among Diabetic Patients on Chronic Hemodialysis
Divani, M., Georgianos, P. I., Didangelos, T., Liakopoulos, V., Makedou, K., Iliadis, F. S., Savopoulos, C. G., & Grekas, D. M. (2021) · Journal of Clinical Medicine · doi:10.3390/jcm10184116 · Cited by 18
Potential cost savings in the United States from a reduction in sensor-detected severe hypoglycemia among users of the InPen smart insulin pen system
Chien, A., THANASEKARAN, S., Gaetano, A., IM, G. H., Wherry, K., MacLeod, J., & Vigersky, R. A. (2023) · Journal of Managed Care & Specialty Pharmacy · doi:10.18553/jmcp.2023.22283 · Cited by 18
Simple Linear Support Vector Machine Classifier Can Distinguish Impaired Glucose Tolerance Versus Type 2 Diabetes Using a Reduced Set of CGM-Based Glycemic Variability Indices
Longato, E., Acciaroli, G., Facchinetti, A., Maran, A., & Sparacino, G. (2019) · Journal of Diabetes Science and Technology · doi:10.1177/1932296819838856 · Cited by 18
The Calculation of the Glucose Management Indicator Is Influenced by the Continuous Glucose Monitoring System and Patient Race
Angellotti, E., Muppavarapu, S., Siegel, R. D., & Pittas, A. G. (2019) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2019.0405 · Cited by 18
Optimal Data Collection Period for Continuous Glucose Monitoring to Assess Long-Term Glycemic Control: Revisited
Cichosz, S. L., Jensen, M. H., & Hejlesen, O. K. (2022) · Journal of Diabetes Science and Technology · doi:10.1177/19322968211069177 · Cited by 19
Impact of Missing Data on the Accuracy of Glucose Metrics from Continuous Glucose Monitoring Assessed Over a 2-Week Period
Smith, G. J., Abraham, M. B., de Bock, M. I., Fairchild, J. M., King, B., Ambler, G. R., Cameron, F. J., McAuley, S. A., KEECH, A. C., Jenkins, A. J., et al. (2023) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2022.0101 · Cited by 17
Scans per day as predictors of optimal glycemic control in people with type 1 diabetes mellitus using flash glucose monitoring: what number of scans per day should raise a red flag?
Sebastián‐Valles, F., Alfonso, J. M., Martín, J. A. A., Jiménez‐Díaz, J., Alday, I. H., Navas-Moreno, V., Joya, T. A., García, M. D. M. F., Gómez, G. L. R., Lobariñas, L. E. L., et al. (2023) · Acta Diabetologica · doi:10.1007/s00592-023-02204-x · Cited by 18
Design Considerations for Artificial Pancreas Pivotal Studies
Russell, S. J., & Beck, R. W. (2015) · Diabetes Care · doi:10.2337/dc15-2449 · Cited by 17
Design of clinical trials to assess diabetes treatment: Minimum duration of continuous glucose monitoring data to estimate time‐in‐ranges with the desired precision
Camerlingo, N., Vettoretti, M., Sparacino, G., Facchinetti, A., Mader, J. K., Choudhary, P., & Favero, S. D. (2021) · Diabetes Obesity and Metabolism · doi:10.1111/dom.14483 · Cited by 16
GlucoMine
Bartolome, A., Shah, S., & Prioleau, T. (2021) · Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies · doi:10.1145/3478109 · Cited by 20
Minimum Sampling Duration for Continuous Glucose Monitoring Metrics to Achieve Representative Glycemic Outcomes in Suboptimal Continuous Glucose Monitor Use
Aktürk, H. K., Sakamoto, C., Vigers, T., Shah, V. N., & Pyle, L. L. (2023) · Journal of Diabetes Science and Technology · doi:10.1177/19322968231200901 · Cited by 15
Hemoglobin A1c and Fructosamine Evaluated in Patients with Type 2 Diabetes Receiving Peritoneal Dialysis Using Long-Term Continuous Glucose Monitoring
Bomholt, T., Feldt‐Rasmussen, B., Butt, R., Borg, R., Sarwary, M. H., Elung‐Jensen, T., Almdal, T., Knop, F. K., Nørgaard, K., Ranjan, A. G., et al. (2021) · The Nephron journals/Nephron journals · doi:10.1159/000519493 · Cited by 15
Baseline Glucose Variability and Interweek Variability Affects the Time to Stability of Continuous Glucose Monitoring-Derived Glycemic Indices
CHANDRAN, S. R., Jacob, P., & Choudhary, P. (2020) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2020.0011 · Cited by 15
RSSDI consensus recommendations on insulin therapy in the management of diabetes
(extended), E. P., Chawla, R., Makkar, B. M., Aggarwal, S., Bajaj, S., Das, A. K., Ghosh, S. K., Gupta, A., Gupta, S., Jaggi, S., et al. (2019) · International Journal of Diabetes in Developing Countries · doi:10.1007/s13410-019-00783-6 · Cited by 15
Limitations of 14-Day Continuous Glucose Monitoring Sampling for Assessment of Hypoglycemia and Glycemic Variability in Type 1 Diabetes
Aktürk, H. K. (2024) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2023.0476 · Cited by 13
“Brittleness” in Diabetes: Easier Spoken than Broken
Voulgari, C., Pagoni, S., Paximadas, S., & Vinik, A. I. (2012) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2012.0058 · Cited by 13
An analytical approach to determine the optimal duration of continuous glucose monitoring data required to reliably estimate time in hypoglycemia
Camerlingo, N., Vettoretti, M., Facchinetti, A., Sparacino, G., Mader, J. K., Choudhary, P., & Favero, S. D. (2020) · Scientific Reports · doi:10.1038/s41598-020-75079-5 · Cited by 13
Standardized Hybrid Closed-Loop System Reporting
Shah, V. N., & Garg, S. K. (2020) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2020.0622 · Cited by 14
Practical Considerations for Using Continuous Glucose Monitoring in Patients with Gestational Diabetes Mellitus
CASTORINO, K. N., Durnwald, C. P., Ehrenberg, S., Ehrhardt, N. M., Isaacs, D., Levy, C. J., Valent, A. M., & Continuous Glucose Monitoring for Gestational Diabetes Management Working Group (2024) · Journal of Women s Health · doi:10.1089/jwh.2023.0864 · Cited by 14
Research progress in the application of time in range: more than a percentage
Wan, J., Lu, J., Li, C., Ma, X., & Zhou, J. (2023) · Chinese Medical Journal · doi:10.1097/cm9.0000000000002582 · Cited by 12
Consequences of Data Loss on Clinical Decision-Making in Continuous Glucose Monitoring: Retrospective Cohort Study
den Braber, N., Braem, C. I. R., Vollenbroek-Hutten, M. M. R., Hermens, H. J., Urgert, T., Yavuz, U. Ş., Veltink, P. H., & Laverman, G. D. (2024) · Interactive Journal of Medical Research · doi:10.2196/50849 · Cited by 9
Early Initiation of Intermittently Scanned Continuous Glucose Monitoring in a Pediatric Population With Type 1 Diabetes: A Real World Study
Franceschi, R., Cauvin, V., Stefani, L., Berchielli, F., Soffiati, M., & Maines, E. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.907517 · Cited by 11
Use of Continuous Glucose Monitoring in Patients Following Bariatric Surgery: A Scoping Review
Yu, Y. H., & Groth, S. W. (2023) · Obesity Surgery · doi:10.1007/s11695-023-06704-1 · Cited by 10
An Examination of the Glucose Management Indicator in Young Children with Type 1 Diabetes
Monzon, A. D., Patton, S. R., & Clements, M. A. (2021) · Journal of Diabetes Science and Technology · doi:10.1177/19322968211023171 · Cited by 10
Choosing the duration of continuous glucose monitoring for reliable assessment of time in range: A new analytical approach to overcome the limitations of correlation‐based methods
Camerlingo, N., Vettoretti, M., Sparacino, G., Facchinetti, A., Mader, J. K., Choudhary, P., & Favero, S. D. (2021) · Diabetic Medicine · doi:10.1111/dme.14758 · Cited by 10
Progress and indication for use of continuous glucose monitoring in patients with diabetes in pregnancy: a review
Song, Y., Zhai, X., Bai, Y., Liu, C., & Zhang, L. (2023) · Frontiers in Endocrinology · doi:10.3389/fendo.2023.1218602 · Cited by 11
Impact of short-term application of continuous glucose monitoring system(CGMS) on long-term glycemic profile in adolescents and adults with type 1 diabetes mellitus: An open-label randomized control cross over study
Gupta, A. V., Mukherjee, S., Bhadada, S. K., Ram, S., Pal, R., Sachdeva, N. K., & Dutta, P. R. (2024) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2024.111610 · Cited by 10
Flash Glucose Monitoring Compared to Capillary Glucose Levels in Patients With Diabetic Ketoacidosis: Potential Clinical Applications
Bichard, L. K., Rushworth, R. L., & Torpy, D. J. (2021) · Endocrine Practice · doi:10.1016/j.eprac.2021.04.005 · Cited by 10
A guide for the use of LibreView digital diabetes platform in clinical practice: Expert paper of the Italian Working Group on Diabetes and Technology
Molfetta, S. D., Rossi, A., Assaloni, R., Cherubini, V., Consoli, A., Bartolo, P. D., Guardasole, V., Laurenzi, A., Lombardo, F., Maffeis, C., et al. (2022) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2022.109867 · Cited by 13
Rationale and design of a randomised phase II multicentre crossover trial investigating a sodium-glucose co-transporter 2 inhibitor, dapagliflozin, combined with a novel continuous ketone monitor in adults with type 1 diabetes to reduce the risk of diabetic ketoacidosis: the PARTNER study
Ngan, J., Kong, Y. W., Goad, J., Huang, M., Jenkins, A. J., Vogrin, S., Trawley, S. L., Manzoney, A., Nakano, M., Ekinci, E. I., et al. (2025) · BMJ Open · doi:10.1136/bmjopen-2024-098457 · Cited by 9
Insulin Metrics: Need for Development of Consensus Standards for Reporting of Insulin Dosing Data
Wolpert, H. A., Polonsky, W. H., & Rodbard, D. (2021) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2020.0631 · Cited by 10
Continuous glucose monitoring as a tool in early-stage type 1 diabetes
Carr, A. L. J., Sutton, H., Agesen, R. M., Bonifacio, E., Bosi, E., Gillard, P., Swaby, R., Vercauteren, J., & Besser, R. E. J. (2026) · Diabetologia · doi:10.1007/s00125-026-06707-4 · Cited by 8
Utilizing the New Glucometrics: A Practical Guide to Ambulatory Glucose Profile Interpretation
Doupis, J., & Horton, E. S. (2022) · touchREVIEWS in Endocrinology · doi:10.17925/ee.2022.18.1.20 · Cited by 11
The Accuracy of Hemoglobin A1c and Fructosamine Evaluated by Long-Term Continuous Glucose Monitoring in Patients with Type 2 Diabetes Undergoing Hemodialysis
Bomholt, T., Rix, M., Almdal, T., Knop, F. K., Rosthøj, S., Heinrich, N. S., Jørgensen, M. B., Larsson, A. O., Hilsted, L. M., Feldt‐Rasmussen, B., et al. (2021) · Blood Purification · doi:10.1159/000519050 · Cited by 10
Evaluation of the relationship between glycated hemoglobin A1c and mean glucose levels derived from the professional continuous flash glucose monitoring system
Yamada, M., Okada, S., Oda, H., Nakajima, Y., Bastie, C. C., Kasai, Y., Osaki, A., Shimoda, Y., Shibusawa, R., Uehara, R., et al. (2020) · Endocrine Journal · doi:10.1507/endocrj.ej19-0502 · Cited by 7
The Changing Landscape of Glycemic Targets: Focus on Continuous Glucose Monitoring
Kushner, P. R., & Kruger, D. F. (2020) · Clinical Diabetes · doi:10.2337/cd19-0093 · Cited by 7
A Large Difference in Dose Timing of Basal Insulin Introduces Risk of Hypoglycemia and Overweight: A Cross-Sectional Study
Nishimura, A., Harashima, S., Fukushige, H., Wang, Y., Liu, Y., Hosoda, K., & Inagaki, N. (2017) · Diabetes Therapy · doi:10.1007/s13300-017-0238-7 · Cited by 8
Practical Considerations for Initiating and Utilizing Flash Continuous Glucose Monitoring in Clinical Practice
Wysham, C., & Kruger, D. F. (2021) · Journal of the Endocrine Society · doi:10.1210/jendso/bvab064 · Cited by 7
The Optimal “Time in Range” and “Time below Range” are Difficult to Coordinate in Patients with Type 1 Diabetes
Sekiguchi, S., Yamada, E., Nakajima, Y., Matsumoto, S., Yoshino, S., Horiguchi, K., Ishida, E., Uehara, R., Okada, S., & Yamada, M. (2021) · The Tohoku Journal of Experimental Medicine · doi:10.1620/tjem.255.221 · Cited by 5
Contribution of glycemic variability to hypoglycemia, and a new marker for diabetes remission after Roux-en-Y gastric bypass surgery
Lu, J., Pan, Y., Tu, Y., Zhang, P., Zhou, J., & Yu, H. (2022) · Surgery for Obesity and Related Diseases · doi:10.1016/j.soard.2022.01.012 · Cited by 5
Determination of Time in Range Associated With HbA1c ≤7% in a Prospective Cohort of Patients With Type 1 Diabetes Using Continuous Glucose Monitoring for Three Months
Gómez, A. M., Diana Cristina Henao, C., Rebolledo, M., Jaramillo, P., Múñoz, Ó., Laura María Niño, G., & Yepes, C. A. (2022) · Journal of Diabetes Science and Technology · doi:10.1177/19322968221108424 · Cited by 5
Improved time in range and postprandial hyperglycemia with canagliflozin in combination with teneligliptin: Secondary analyses of the CALMER study
Cho, K. Y., Nomoto, H., Nakamura, A., Kawata, S., Sugawara, H., Takeuchi, J., Nagai, S., Omori, K., Tsuchida, K., Miya, A., et al. (2021) · Journal of Diabetes Investigation · doi:10.1111/jdi.13498 · Cited by 5
Continuous Glucose Monitor Metrics Are Associated with Emergency Department Visits and Hospitalizations for Hypoglycemia and Hyperglycemia, but Have Low Predictive Value
Gilliam, L. K., Parker, M. M., Moffet, H. H., Lee, A. K., & Karter, A. J. (2024) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2023.0493 · Cited by 4
Investigation of Glucose Metabolism by Continuous Glucose Monitoring and Validation of Dipeptidyl Peptidase 4 Inhibitor Use in Patients with Myotonic Dystrophy Type 1
Takada, H., Matsumura, T., Shimamura, H., Matsui, M., Kon, S., Fukumoto, A., Kubota, T., Yoshida, K., Iwahashi, H., & Takahashi, M. P. (2024) · Journal of Clinical Medicine · doi:10.3390/jcm13175252 · Cited by 4
Personalized sleep and nutritional strategies to combat adverse effects of night shift work: a controlled intervention protocol
van der Rhee, M., Oosterman, J. E., Wopereis, S., van der Horst, G. T. J., Chaves, I., Dollé, M. E. T., Burdorf, A., van Kerkhof, L. W. M., & der Holst, H. M. L. (2024) · BMC Public Health · doi:10.1186/s12889-024-20022-w · Cited by 4
Beyond A1C: A Practical Approach to Interpreting and Optimizing Continuous Glucose Data in Youth
Al-Gadi, I., Menon, S., Lyons, S. K., & DeSalvo, D. J. (2021) · Diabetes Spectrum · doi:10.2337/ds20-0095 · Cited by 4
Pitfalls of intermittent continuous glucose monitoring in patients with steroid diabetes
Yamada, E., Sekiguchi, S., Nakajima, Y., Uehara, R., Okada, S., & Yamada, M. (2021) · Endocrine Journal · doi:10.1507/endocrj.ej21-0498 · Cited by 4
Remote Pharmacist-Assisted Flash Continuous Glucose Monitoring Improves Glycemic Outcomes in Patients With Poorly Controlled Diabetes: A Retrospective Case Series
Siemens, R. L. (2022) · Clinical Diabetes · doi:10.2337/cd21-0088 · Cited by 4
Dealing with diabetes and pregnancy following bariatric surgery: a double-edged sword?
Mancini, M. C. (2016) · Archives of Endocrinology and Metabolism · doi:10.1590/2359-3997000000181 · Cited by 4
Continuous Glucose Monitoring in 2011
Battelino, T., & Bode, B. W. (2012) · doi:10.1002/9781118321508.ch2 · Cited by 4
Impact of Missing Data and Monitoring Duration on Downstream Analyses in Continuous Glucose Monitoring
Kok, N., Williamson, W. T., Lee, J. M., & Gaynanova, I. (2026) · Diabetes Care · doi:10.2337/dc25-2935 · Cited by 3
Can Faster Aspart Be Used to Optimize Glycemic Control With Insulin Pump Therapy? From Expectations to Lessons Learned After a Year of Use in the United States
Aleppo, G., Bode, B. W., & Carlson, A. L. (2022) · Clinical Diabetes · doi:10.2337/cd21-0056 · Cited by 3

Authors: Xing, D., Kollman, C., Beck, R. W., Tamborlane, W. V., Laffel, L., Buckingham, B. A., Wilson, D. M., Weinzimer, S., Fiallo-Scharer, R., & Ruedy for the Juvenile Diabetes Research Foundation Continuo, K. J.
Affiliations: Jaeb Center for Health Research (US)
Yale University (US)
Joslin Diabetes Center (US)
Stanford University (US)
Barbara Davis Center
Jaeb Center for Health Research
Corresponding author: Xing, Dongyuan
ORCID: Xing, Dongyuan
Beck, Roy W.
Tamborlane, William V.
Laffel, Lori
Buckingham, Bruce A.
Wilson, Darrell M.
Weinzimer, Stuart
Fiallo-Scharer, Rosanna
Venue: Diabetes Technology & Therapeutics
Publisher: SAGE Publications
Published: 2011-03
Volume: 13
Issue: 3
Pages: 351-358
ISSN: 1520-9156 (ISSN-L)
1557-8593
DOI: 10.1089/dia.2010.0156
PMC: PMC6468940
OpenAlex: W2007986610
Cited by: 131
References: 12
Citations by year: 2026: 10 · 2025: 7 · 2024: 11 · 2023: 15 · 2022: 18 · 2021: 21 · 2020: 15 · 2019: 10 · 2018: 4 · 2017: 6 · 2016: 4 · 2015: 1 · 2014: 1 · 2013: 1 · 2012: 5
FWCI: 2.10
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: journals.sagepub.com/page/policies/text-and-data-mining-license (tdm)
Locations: Diabetes Technology & Therapeutics (publishedVersion)
Europe PMC (PubMed Central) (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Funders: Eunice Kennedy Shriver National Institute of Child Health and Human Development (U10HD041908)
Topics: Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Treatment and Management
Keywords: continuous glucose monitoring, glycemic control, sampling interval, HbA1c, mean blood glucose, hypoglycemia, hyperglycemia, coefficient of variation, type 1 diabetes
MeSH terms: Adolescent, Adult, Aged, Blood Glucose, Child, Diabetes Mellitus, Type 1, Female, Glycated Hemoglobin, Humans, Longitudinal Studies, Male, Middle Aged, Time Factors, Blood Glucose Self-Monitoring, Young Adult

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

Optimal Sampling Intervals to Assess Long-Term Glycemic Control Using Continuous Glucose Monitoring

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Self-check

Citations

Cites

Cited by

Related

Metadata

Record

About these checks