The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Continuous Glucose Monitoring: A Review of Successes, Challenges, and Opportunities
Open accessAbstract
Continuous glucose monitoring (CGM) provides information unattainable by intermittent capillary blood glucose, including instantaneous real-time display of glucose level and rate of change of glucose, alerts and alarms for actual or impending hypo- and hyperglycemia, "24/7" coverage, and the ability to characterize glycemic variability. Progressively more accurate and precise, reasonably unobtrusive, small, comfortable, user-friendly devices connect to the Internet to share information and are sine qua non for a closed-loop artificial pancreas. CGM can inform, educate, motivate, and alert people with diabetes. CGM is medically indicated for patients with frequent, severe, or nocturnal hypoglycemia, especially in the presence of hypoglycemia unawareness. Surprisingly, despite tremendous advances, utilization of CGM has remained fairly limited to date. Barriers to use have included the following: (1) lack of Food and Drug Administration approval, to date, for insulin dosing ("nonadjuvant use") in the United States and for use in hospital and intensive care unit settings; (2) cost and variable reimbursement; (3) need for recalibrations; (4) periodic replacement of sensors; (5) day-to-day variability in glycemic patterns, which can limit the predictability of findings based on retrospective, masked "professional" use; (6) time, implicit costs, and inconvenience for uploading of data for retrospective analysis; (7) lack of fair and reasonable reimbursement for physician time; (8) inexperience and lack of training of physicians and other healthcare professionals regarding interpretation of CGM results; (9) lack of standardization of software methods for analysis of CGM data; and (10) need for professional medical organizations to develop and disseminate additional clinical practice guidelines regarding the role of CGM. Ongoing advances in technology and clinical research have addressed several of these barriers. Use of CGM in conjunction with an insulin pump with automated suspension of insulin infusion in response to actual observed or predicted hypoglycemia, as well as progressive refinement of closed-loop systems, is expected to dramatically enhance the clinical utility and utilization of CGM.
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Cites
Miller, K. M., Foster, N. C., Beck, R. W., Bergenstal, R. M., DuBose, S. N., DiMeglio, L. A., Maahs, D. M., & Tamborlane, W. V. (2015) · Diabetes Care · doi:10.2337/dc15-0078 · Cited by 1,254
Home Use of an Artificial Beta Cell in Type 1 Diabetes
Thabit, H., Tauschmann, M., Allen, J. M., Leelarathna, L., Hartnell, S., Wilinska, M. E., Acerini, C. L., Dellweg, S., Benesch, C., Heinemann, L., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1509351 · Cited by 450
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
Bergenstal, R. M., Ahmann, A. J., Bailey, T., Beck, R. W., Bissen, J., Buckingham, B., Deeb, L., Dolin, R. H., Garg, S. K., Goland, R., et al. (2013) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2013.0051 · Cited by 307
Ehrhardt, N. M., Chellappa, M., Walker, M. S., Fonda, S. J., & Vigersky, R. A. (2011) · Journal of Diabetes Science and Technology · doi:10.1177/193229681100500320 · Cited by 199
Blevins, T. C., Bode, B. W., Garg, S. K., Grunberger, G., Hirsch, I. B., Jovanovič, L., Nardacci, E., Orzeck, E. A., Roberts, V. L., & Tamborlane, W. V. (2010) · Endocrine Practice · doi:10.4158/ep.16.5.730 · Cited by 98
Cited by
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
“obstacles, clinician inexperience in data interpretation and lack of standardization software for visualization of CGM data have also played a role (73).”
Self-citationWearable biosensors for healthcare monitoring
Kim, J., Campbell, A. S., de Ávila, B. E.-F., & Wang, J. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0045-y · Cited by 3,373
Bolinder, J., Antuna, R., Geelhoed-Duijvestijn, P., Kröger, J., & Weitgasser, R. (2016) · The Lancet · doi:10.1016/s0140-6736(16)31535-5 · Cited by 893
Wearable non-invasive epidermal glucose sensors: A review
Kim, J., Campbell, A. S., & Wang, J. (2018) · Talanta · doi:10.1016/j.talanta.2017.08.077 · Cited by 586
Yetisen, A. K., Martinez‐Hurtado, J. L., Ünal, B., Khademhosseini, A., & Butt, H. (2018) · Advanced Materials · doi:10.1002/adma.201706910 · Cited by 569
Metadata
- Authors
- Rodbard, D.
- Venue
- Diabetes Technology & Therapeutics
- Publisher
- SAGE Publications
- Published
- 2016-02
- Volume
- 18
- Issue
- S2
- Pages
- S2-3-S2-13
- ISSN
- 1520-9156 (ISSN-L)
- 1557-8593
- OpenAlex
- W2278129565
- Cited by
- 737
- References
- 7
- FWCI
- 70.43
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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