Regulation Catches Up to Reality: Nonadjunctive Use of Continuous Glucose Monitoring Data

Journal of Diabetes Science and Technology

Volumn 11, Issue 1, 2017, Pages 160-164

  Edelman, Steven V ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

CGM; FDA panel meeting; nonadjunctive claim; SMBG

Indexed keywords

INSULIN; ANTIDIABETIC AGENT; GLUCOSE BLOOD LEVEL;

BLOOD GLUCOSE METER; BLOOD GLUCOSE MONITORING; CAREGIVER; COMPUTER SIMULATION; CONTINUOUS GLUCOSE MONITORING SYSTEM; CONTROLLED STUDY; DATA ANALYSIS; DRUG LABELING; FOOD AND DRUG ADMINISTRATION; GENERAL MEDICAL DEVICE; GLYCEMIC CONTROL; HEALTH CARE PERSONNEL; HYPOGLYCEMIA; INSULIN DEPENDENT DIABETES MELLITUS; MEASUREMENT ACCURACY; MEDICAL DECISION MAKING; PINPRICK TEST; RANDOMIZED CONTROLLED TRIAL; REVIEW; ANALYSIS; BLOOD; DEVICE APPROVAL; DEVICES; DIABETES MELLITUS, TYPE 1; GLUCOSE BLOOD LEVEL; HUMAN; STANDARDS; UNITED STATES;

BLOOD GLUCOSE; BLOOD GLUCOSE SELF-MONITORING; DEVICE APPROVAL; DIABETES MELLITUS, TYPE 1; HUMANS; HYPOGLYCEMIC AGENTS; INSULIN; UNITED STATES; UNITED STATES FOOD AND DRUG ADMINISTRATION;

EID: 85009238102     PISSN: None     EISSN: 19322968     Source Type: Journal    
DOI: 10.1177/1932296816667749     Document Type: Review

References (10)

1. Food and Drug Administration. Advisory committees. http://www.fda.gov/AdvisoryCommittees/default.htm. Accessed August 12, 2016.
2. Beck RW, Tamborlane WV, Bergenstal RM, et al. The T1D Exchange Clinic Registry. J Clin Endocrinol Metab. 2012; 97: 4383-4389.
3. Pettus J, Price DA, Hill KJ, Edelman S,. How people use direction and rate of change information provided by real-time continuous glucose monitoring (RT-CGM) to adjust insulin dosing. Diabetes Technol Ther. 2014; 16 (S1): 198.
4. Pettus JH, Hirsch IB, Edelman SV,. Practical Management of Type 1 Diabetes. 2nd ed. Greenwich, CT: Professional Communications; 2013.
5. Kovatchev BP, Breton MD, Dalla Man C, Cobelli C,. In silico preclinical trials: a proof of concept in closed-loop control of type 1 diabetes. J Diabetes Sci Technol. 2009; 3: 44-55.
6. Dalla Man C, Micheletto F, Lv D, Breton M, Kovatchev B, Cobelli C,. The UVA/PADOVA Type 1 Diabetes Simulator: new features. J Diabetes Sci Technol. 2014; 8: 26-34.
7. Viceconti M, Cobelli M, Haddad T, Himes A, Kovatchev B, Palmer M,. In silico assessment of biomedical products: the conundrum of rare but not so rare events. J Eng Med (In press).
8. Visentin R, Giegerich C, Jäger R, et al. Improving efficacy of inhaled technosphere insulin (Afrezza) by postmeal dosing: in-silico clinical trial with the University of Virginia/Padova Type 1 Diabetes Simulator. Diabetes Technol Ther. 2016; 18: 574-85.
9. Miller KM, Foster NC, Beck RW, et al. Current state of type 1 diabetes treatment in the US: updated data from the T1D Exchange Clinic Registry. Diabetes Care. 2015; 38 (6): 971-978.
10. Pettus J, Edelman SV,. Recommendations for Using Real-Time Continuous Glucose Monitoring (rtCGM) Data for Insulin Adjustments in Type 1 Diabetes. [published online 16, 2016 ]. J Diabetes Sci Technol.