Literature DB >> 28868899

Rate of Change of Premeal Glucose Measured by Continuous Glucose Monitoring Predicts Postmeal Glycemic Excursions in Patients With Type 1 Diabetes: Implications for Therapy.

Amit R Majithia1,2, Alexander B Wiltschko3, Hui Zheng2, Geoffrey A Walford2, David M Nathan2.   

Abstract

BACKGROUND: Patients with type 1 diabetes routinely utilize a single premeal fingerstick glucose to determine premeal insulin doses. Continuous glucose monitoring (CGM) provides much richer glycemic trend information, including glycemic slope (GS). How to incorporate this information into dosing decisions remains an open question.
METHODS: We examined the relationship between premeal GS and postmeal glycemic excursions in 240 individuals with type 1 diabetes receiving CGM augmented insulin pump therapy. Over 23.5 million CGM values were synchronized with 264 500 meals. CGM values were integrated 2 hours premeal to compute GS and 2 hours postmeal to compute glycemic excursion outcomes. Postmeal hyperglycemia (integrated CGM glucose >180 mg/dL*hr) and postmeal hypoglycemic events (any CGM glucose < 70 mg/dL) were tabulated according to positive/negative premeal GS and according to GS bins commonly displayed as rate-of-change arrows on CGM devices.
RESULTS: Positive versus negative premeal GS was associated with a 2.28-fold (95% CI 2.25-2.32) risk of postmeal hyperglycemia. Negative versus positive premeal GS was associated with a 2.36-fold (95% CI 2.25-2.43) increase in one or more postprandial hypoglycemic events. Premeal GS in the bin currently displayed as "no change" on existing CGM devices (-1 to 1 mg/dL/min), conferred a 1.82-fold (95% CI 1.79-1.86) risk of postprandial hyperglycemia when positive and a 2.06-fold (95% CI 1.99-2.15) increased risk of postprandial hypoglycemia when negative.
CONCLUSION: Premeal GS predicts postmeal glycemic excursions and may help inform insulin dosing decisions. Rate-of-change arrows on existing devices obscure clinically actionable glycemic trend information from CGM users.

Entities:  

Keywords:  continuous glucose monitoring; glucose rate-of-change; insulin dosing; postprandial hyperglycemia; postprandial hypoglycemia; premeal glycemic trends

Mesh:

Substances:

Year:  2017        PMID: 28868899      PMCID: PMC5761983          DOI: 10.1177/1932296817725756

Source DB:  PubMed          Journal:  J Diabetes Sci Technol        ISSN: 1932-2968


  10 in total

Review 1.  Standards of Medical Care in Diabetes-2017: Summary of Revisions.

Authors: 
Journal:  Diabetes Care       Date:  2017-01       Impact factor: 19.112

Review 2.  Continuous Glucose Monitoring in 2016.

Authors:  Bruce W Bode; Tadej Battelino
Journal:  Diabetes Technol Ther       Date:  2017-02       Impact factor: 6.118

3.  TIME TO GET SERIOUS ABOUT INSULIN TIMING.

Authors:  Jeremy Pettus
Journal:  Endocr Pract       Date:  2017-02-03       Impact factor: 3.443

4.  Effectiveness of sensor-augmented insulin-pump therapy in type 1 diabetes.

Authors:  Richard M Bergenstal; William V Tamborlane; Andrew Ahmann; John B Buse; George Dailey; Stephen N Davis; Carol Joyce; Tim Peoples; Bruce A Perkins; John B Welsh; Steven M Willi; Michael A Wood
Journal:  N Engl J Med       Date:  2010-06-29       Impact factor: 91.245

5.  Continuous Glucose Monitoring vs Conventional Therapy for Glycemic Control in Adults With Type 1 Diabetes Treated With Multiple Daily Insulin Injections: The GOLD Randomized Clinical Trial.

Authors:  Marcus Lind; William Polonsky; Irl B Hirsch; Tim Heise; Jan Bolinder; Sofia Dahlqvist; Erik Schwarz; Arndís Finna Ólafsdóttir; Anders Frid; Hans Wedel; Elsa Ahlén; Thomas Nyström; Jarl Hellman
Journal:  JAMA       Date:  2017-01-24       Impact factor: 56.272

6.  Effect of Continuous Glucose Monitoring on Glycemic Control in Adults With Type 1 Diabetes Using Insulin Injections: The DIAMOND Randomized Clinical Trial.

Authors:  Roy W Beck; Tonya Riddlesworth; Katrina Ruedy; Andrew Ahmann; Richard Bergenstal; Stacie Haller; Craig Kollman; Davida Kruger; Janet B McGill; William Polonsky; Elena Toschi; Howard Wolpert; David Price
Journal:  JAMA       Date:  2017-01-24       Impact factor: 56.272

7.  Sensor-augmented pump therapy for A1C reduction (STAR 3) study: results from the 6-month continuation phase.

Authors:  Richard M Bergenstal; William V Tamborlane; Andrew Ahmann; John B Buse; George Dailey; Stephen N Davis; Carol Joyce; Bruce A Perkins; John B Welsh; Steven M Willi; Michael A Wood
Journal:  Diabetes Care       Date:  2011-09-20       Impact factor: 17.152

Review 8.  Hypoglycemia in diabetes.

Authors:  Philip E Cryer; Stephen N Davis; Harry Shamoon
Journal:  Diabetes Care       Date:  2003-06       Impact factor: 19.112

9.  Postprandial blood glucose predicts cardiovascular events and all-cause mortality in type 2 diabetes in a 14-year follow-up: lessons from the San Luigi Gonzaga Diabetes Study.

Authors:  Franco Cavalot; Andrea Pagliarino; Manuela Valle; Leonardo Di Martino; Katia Bonomo; Paola Massucco; Giovanni Anfossi; Mariella Trovati
Journal:  Diabetes Care       Date:  2011-10       Impact factor: 19.112

Review 10.  Recommendations for Using Real-Time Continuous Glucose Monitoring (rtCGM) Data for Insulin Adjustments in Type 1 Diabetes.

Authors:  Jeremy Pettus; Steven V Edelman
Journal:  J Diabetes Sci Technol       Date:  2016-08-20
  10 in total
  1 in total

Review 1.  Use of continuous glucose monitoring trend arrows in the younger population with type 1 diabetes.

Authors:  Nancy Elbarbary; Othmar Moser; Saif Al Yaarubi; Hussain Alsaffar; Adnan Al Shaikh; Ramzi A Ajjan; Asma Deeb
Journal:  Diab Vasc Dis Res       Date:  2021 Nov-Dec       Impact factor: 3.291

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.