The individualized statistical analysis of the continuous glucose monitoring data

Cover Page


Cite item

Full Text

Abstract

Background: Continuous glucose monitoring (CGM) has shown its benefits in pregnant women with diabetes. Flash glucose monitoring (FGM), as one of the CGM types, has not been well assessed in this patient group. The interpretation of a  big volume of information on glycaemia obtained with various CGM devices is possible with statistical analysis according to the algorithms proposed by manufacturers. While these algorithms cannot be comprehensive, evaluation of alternative approaches to the CGM data statistical analysis and comparison of the results obtained with different devices seem reasonable. No unified algorithm for modification of antidiabetic treatment according to the CGM results has been yet developed. This study was performed in a  pregnant patient with type  1 diabetes mellitus (T1DM) to demonstrate the methods to individualized analysis of the data from various devices (CGM, FGM, glucometer) that could be used in routine clinical practice.

Aim: To evaluate the individual advantages and disadvantages of the simultaneous use of FGM, CGM and SMBG in a pregnant woman with type 1 diabetes.

Materials and methods: This was an observational case study with a retrospective assessment of the patient's data obtained with FGM, CGM and a glucometer in a 31-year female patient with T1DM of 6-year duration and 9 weeks of gestation, who had been on pump insulin therapy for one year and had an HbA1c level of 5.4%. During the study the patient continued her pump therapy and performed blood glucose self-monitoring (BGSM) and simultaneously used FGM and CGM. The following FGM data were compared with CGM and glucometer results: measurement numbers, time in range, mean daily glucose, mean absolute difference (MAD), and mean absolute relative difference (MARD).

Results: The FGM-derived mean daily glucose was lower than that measured with the glucometer: 5.1±1.9  mmol/L vs 6.4±2.2  mmol/L (p<0.001). The number of measurements with FGM was 32.0±12.9  times daily and with a  glucometer 15.1±5.5  times daily (p<0.001). MAD values were minimal in the hypoglycemic range (0.5±0.3  mmol/L) and maximal in the hyperglycemic range (1.6±1.2 mmol/L, р<0.001). The MARD values were significantly smaller in the hyperglycemic than in the normoglycemic (16.6±12.6% vs 21.3±14.0%, р=0.035). The highest MAD and MARD were observed on the Day 1 of the sensor installation. The comparison of FGM and the glucometer readings with the Clarke consensus error grid showed that 82% of the FGM readings were in zone A or B. The FGM accuracy was higher from Day 2 to Day 9 (72.5% of the FGM readings in zone A). MAD between FGM and CGM readings was not different from that between FGM and the glucometer: 1.3±1.0  mmol/L and 1.2±0.9  mmol/L, respectively (p=0.09). MARD for the FGM and CGM comparison was higher than that for FGM and glucometer comparison: 24.4±23.0% and 18.8±13.5%, respectively (р<0.001). The Pearson's correlation coefficient FGM and CGM seemed lower than that between FGM and the glucometer (0.837 and 0.889, respectively). FGM has identified more hypoglycemic events compared to CGM: time below range was 29.4% and 8.8%, respectively, p<0.001).

Conclusion: The FGM readings highly correlate with the glucometer. The FGM difference with the glucometer was lower in the hypo- and hyperglycemic ranges. FGM shows higher values for time below range than CGM. It is necessary to continue the study of the clinical acceptability of FGM in pregnant women and determination of its optimal regimen for the treatment of this patient category, as well as to develop an algorithm for treatment modification based on the results of FGM.

About the authors

A. V. Dreval'

Moscow Regional Research and Clinical Institute (MONIKI)

Email: fake@neicon.ru
ORCID iD: 0000-0002-3135-9003

Aleksandr V. Dreval' – MD, PhD, Professor, Head of Chair of Endocrinology, Postgraduate Training Faculty

61/2 Shchepkina ul., Moscow, 129110

Russian Federation

T. P. Shestakova

Moscow Regional Research and Clinical Institute (MONIKI)

Author for correspondence.
Email: t240169@yandex.ru

Tatyana P. Shestakova – MD, PhD, Associate Professor, Chair of Endocrinology, Postgraduate Training Faculty

61/2–9 Shchepkina ul., Moscow, 129110

Russian Federation

A. A. Manukyan

Moscow Regional Research and Clinical Institute (MONIKI)

Email: fake@neicon.ru

Artem A. Manukyan – Endocrinologist, Postgraduate Student, Chair of Endocrinology, Postgraduate Training Faculty

61/2 Shchepkina ul., Moscow, 129110

Russian Federation

O. G. Brezhneva

Moscow Regional Research and Clinical Institute (MONIKI)

Email: fake@neicon.ru

Olga G. Brezhneva – Resident Doctor, Chair of Endocrinology, Postgraduate Training Faculty

61/2 Shchepkina ul., Moscow, 129110

Russian Federation

References

  1. Kristensen K, Ögge LE, Sengpiel V, Kjölhede K, Dotevall A, Elfvin A, Knop FK, Wiberg N, Katsarou A, Shaat N, Kristensen L, Berntorp K. Continuous glucose monitoring in pregnant women with type 1 diabetes: an observational cohort study of 186 pregnancies. Diabetologia. 2019;62(7):1143–53. doi: 10.1007/s00125-019-4850-0.
  2. Дедов ИИ, Шестакова МВ, Майоров АЮ, ред. Алгоритмы специализированной медицинской помощи больным сахарным диабетом. 9-й вып. (дополн.). Сахарный диабет. 2019;22(S1). doi: 10.14341/DM221S1.
  3. Древаль АВ, Шестакова ТП, Туркай М, Древаль ОА, Куликов ДА, Медведев ОС. Cравнение результатов самоконтроля и непрерывного мониторирования гликемии у беременных, больных сахарным диабетом. Альманах клинической медицины. 2015;(43):66–71. doi: 10.18786/2072-0505-2015-43-66-71.
  4. Feig DS, Donovan LE, Corcoy R, Murphy KE, Amiel SA, Hunt KF, Asztalos E, Barrett JFR, Sanchez JJ, de Leiva A, Hod M, Jovanovic L, Keely E, McManus R, Hutton EK, Meek CL, Stewart ZA, Wysocki T, O'Brien R, Ruedy K, Kollman C, Tomlinson G, Murphy HR; CONCEPTT Collaborative Group. Continuous glucose monitoring in pregnant women with type 1 diabetes (CONCEPTT): a multicentre international randomised controlled trial. Lancet. 2017;390(10110):2347–59. doi: 10.1016/S0140-6736(17)32400-5.
  5. Danne T, Nimri R, Battelino T, Bergenstal RM, Close KL, DeVries JH, Garg S, Heinemann L, Hirsch I, Amiel SA, Beck R, Bosi E, Buckingham B, Cobelli C, Dassau E, Doyle FJ 3rd, Heller S, Hovorka R, Jia W, Jones T, Kordonouri O, Kovatchev B, Kowalski A, Laffel L, Maahs D, Murphy HR, Nørgaard K, Parkin CG, Renard E, Saboo B, Scharf M, Tamborlane WV, Weinzimer SA, Phillip M. International Consensus on Use of Continuous Glucose Monitoring. Diabetes Care. 2017;40(12):1631–40. doi: 10.2337/dc17-1600.
  6. Древаль АВ, ред. Помповая инсулинотерапия и непрерывное мониторирование гликемии. Клиническая практика и перспективы. М.: ГЭОТАР-Медиа; 2019. 336 с.
  7. Battelino T, Danne T, Bergenstal RM, Amiel SA, Beck R, Biester T, Bosi E, Buckingham BA, Cefalu WT, Close KL, Cobelli C, Dassau E, DeVries JH, Donaghue KC, Dovc K, Doyle FJ 3rd, Garg S, Grunberger G, Heller S, Heinemann L, Hirsch IB, Hovorka R, Jia W, Kordonouri O, Kovatchev B, Kowalski A, Laffel L, Levine B, Mayorov A, Mathieu C, Murphy HR, Nimri R, Nørgaard K, Parkin CG, Renard E, Rodbard D, Saboo B, Schatz D, Stoner K, Urakami T, Weinzimer SA, Phillip M. Clinical targets for continuous glucose monitoring data interpretation: Recommendations from the International Consensus on Time in Range. Diabetes Care. 2019;42(8):1593–603. doi: 10.2337/dci19-0028.
  8. Clarke WL, Cox D, Gonder-Frederick LA, Carter W, Pohl SL. Evaluating clinical accuracy of systems for self-monitoring of blood glucose. Diabetes Care. 1987;10(5):622–8. doi: 10.2337/diacare.10.5.622.
  9. Koh A, Nichols SP, Schoenfisch MH. Glucose sensor membranes for mitigating the foreign body response. J Diabetes Sci Technol. 2011;5(5):1052–9. doi: 10.1177/193229681100500505.
  10. Ajjan RA, Cummings MH, Jennings P, Leelarathna L, Rayman G, Wilmot EG. Accuracy of flash glucose monitoring and continuous glucose monitoring technologies: Implications for clinical practice. Diab Vasc Dis Res. 2018;15(3):175–84. doi: 10.1177/1479164118756240.
  11. Dunn TC, Xu Y, Hayter G, Ajjan RA. Real-world flash glucose monitoring patterns and associations between self-monitoring frequency and glycaemic measures: A European analysis of over 60 million glucose tests. Diabetes Res Clin Pract. 2018;137:37–46. doi: 10.1016/j.diabres.2017.12.015.
  12. Scott EM, Bilous RW, Kautzky-Willer A. Accuracy, user acceptability, and safety evaluation for the FreeStyle Libre flash glucose monitoring system when used by pregnant women with diabetes. Diabetes Technol Ther. 2018;20(3): 180–8. doi: 10.1089/dia.2017.0386.
  13. Ólafsdóttir AF, Attvall S, Sandgren U, Dahlqvist S, Pivodic A, Skrtic S, Theodorsson E, Lind M. A clinical trial of the accuracy and treatment experience of the flash glucose monitor FreeStyle Libre in adults with Type 1 diabetes. Diabetes Technol Ther. 2017;19(3): 164–72. doi: 10.1089/dia.2016.0392.
  14. Bailey T, Bode BN, Christiansesen M, Klaff L, Shridhara A. The performance and usability of a factory-calibrated flash glucose monitoring system. Diabetes Technol Ther. 2015;17(1): 787–94.
  15. Murphy HR. Continuous glucose monitoring targets in type 1 diabetes pregnancy: every 5% time in range matters. Diabetologia. 2019;62(7):1123–8. doi: 10.1007/s00125-019-4904-3.
  16. Bonora B, Maran A, Ciciliot S, Avogaro A, Fadini GP. Head-to-head comparison between flash and continuous glucose monitoring systems in outpatients with type 1 diabetes. J Endocrinol Invest. 2016;39(12):1391–9. doi: 10.1007/s40618-016-0495-8.
  17. Forlenza GP, Kushner T, Messer LH, Wadwa RP, Sankaranarayanan S. Factory-Calibrated Continuous Glucose Monitoring: How and Why It Works, and the Dangers of Reuse Beyond Approved Duration of Wear. Diabetes Technol Ther. 2019;21(4):222–9. doi: 10.1089/dia.2018.0401.
  18. Liebl A, Henrichs HR, Heinemann L, Freckmann G, Biermann E, Thomas A; Continuous Glucose Monitoring Working Group of the Working Group Diabetes Technology of the German Diabetes Association. Continuous glucose monitoring: evidence and consensus statement for clinical use. J Diabetes Sci Technol. 2013;7(2):500–19. doi: 10.1177/193229681300700227.
  19. Gatti M. Feasibility of FreeStyle Libre Flash Glucose Monitoring System in pregnant woman affected by type 1 diabetes. Acta Diabetol. 2019;56(4):481–3. doi: 10.1007/s00592-018-1252-6.
  20. Bolinder J, Antuna R, Geelhoed-Duijvestijn P, Kröger J, Weitgasser R. Novel glucose-sensing technology and hypoglycaemia in type 1 diabetes: a multicentre, non-masked, randomised controlled trial. Lancet. 2016;388(10057):2254–63. doi: 10.1016/S0140-6736(16)31535-5.
  21. Fokkert MJ, van Dijk PR, Edens MA, Abbes S, de Jong D, Slingerland RJ, Bilo HJ. Performance of the FreeStyle Libre Flash glucose monitoring system in patients with type 1 and 2 diabetes mellitus. BMJ Open Diabetes Res Care. 2017;5(1):e000320. doi: 10.1136/bmjdrc-2016-000320.

Supplementary files

Supplementary Files
Action
1. JATS XML

Copyright (c) 2020 Dreval' A.V., Shestakova T.P., Manukyan A.A., Brezhneva O.G.

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

This website uses cookies

You consent to our cookies if you continue to use our website.

About Cookies