Diminished sensor performance of the Abbott

Freestyle® Libre iCGM system during

hypoglycemia and acute exercise in people

with type 1 diabetes

Othmar Moser, Max L. Eckstein, Olivia McCarthy, Rachel Deere, Jason Pitt,

David M. Williams, Jennifer Hayes, Stephen C. Bain, Richard M. Bracken

Research Support

Sêr Cymru II COFUND fellowship/European Union, Novo

Nordisk A/S and Novo Nordisk AT, Abbott Diabetes Care,

Sanofi, Dexcom, Team Novo Nordisk

Lecture fees

Medtronic AT

Travel Grants

Novo Nordisk A/S, Novo Nordisk AT, Novo Nordisk UK,

Medtronic AT

Presenter Disclosure Othmar Moser

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Twitter: @othmar_moser

Background

FDA approved the iCGM system to monitor interstitial glucose withoutobtaining a blood sample in people with T1D and T2D aged ≥ 18 1

Beneficial effects of iCGM 2-5:

lower HbA1c levels

reduced time spent in hypoglycemia

improved glycemic variability

increased numbers of readings in people with T1D

Background

iCGM accuracy shows Median/Mean Absolute Relative Differences(MARD) ranging from 8% to 15% under routine environmental conditions 6

However, in general CGM accuracy deteriorates during rapidly changingglucose concentrations of more than ± 3 mg/dL/min 7

AimTo assess iCGM system accuracy during glycemic challenges of

carbohydrate-rich meals, bolus insulin-induced glycemic disturbances and acute physical exercise in people with T1D

Methods

This is a secondary outcome analysis of a single-center, randomized, open-label, cross-over trial

Four 23-hour inpatient phases with glycemic challenges and 45-min moderate-intensity cycle ergometer exercises were performed

17 people with T1D (4 women)

Age 34.9 ± 15.5 years

BMI 25.9 ± 3.0 kg/m2

HbA1c 7.3 ± 1.4%

MDI (insulin Degludec, insulin Aspart)

Methods

Methods

Venous BG

Capillary BG(fingertip)

Capillary BG(earlobe)

Methods

iCGM interstitial glucose was compared to reference blood glucose by

fully enzymatic Biosen C-Line system (EKF Diagnostic, GER) via

Median Absolute Relative Difference (MARD)

Clarke Error Grid (CEG)

Bland–Altman analysis

Results (MARD)

iCGM accuracyM

AR

D (

IQR

)

Overall (8 AM – 7 AM) 12.9% (6.1 – 21.5%), n = 1114

Hypoglycemia (≤ 70 mg/dL) 31.6% (14.0 – 46.8%), n = 79

Euglycemia (71 – 179 mg/dL) 14.5% (7.0 – 22.5%), n = 704

Hyperglycemia (≥ 180 mg/dL) 8.7% (4.6 – 14.6%), n = 331

Phase 1, DAY (pre-exercise) 12.5% (6.0 – 21.6%), n = 353

Phase 2, DAY (during exercise) 29.8% (17.5 – 39.8%), n = 475

Phase 2, Hypoglycemia (≤ 70 mg/dL) 45.1% (35.2 – 51.1%), n = 70

Phase 2, Euglycemia (71 – 179 mg/dL) 30.7% (18.7 – 39.2%), n = 311

Phase 2, Hyperglycemia (≥ 180 mg/dL) 16.3% (10.0 – 22.8%), n = 94

Phase 3, DAY (post-exercise) 17.4% (9.5 – 27.1%), n = 410

Phase 4, NIGHT (12 AM – 6 AM) 8.5% (3.9 – 14.7%), n = 282

Results (Clarke Error Grid)

Zone A: 66.07%

Zone B: 26.66%

Zone C: 0.09%

Zone D: 7.18% Zone E: No values

Zone A: 25.68%

Zone B: 52.00%

Zone C: No values

Zone D: 22.32%

Zone E: No values

Results (Bland-Altman)

Results (Rate of Change)

Pre-exercise Exercise Post-exercise Nocturnal

Rate of Change in Glucose

(mg/dL/min)

0.30(0.12 – 0.52)

2.70 (1.78 – 3.78)

0.54(0.26 – 1.10)

0.12(0.01 – 0.30)

MARD (IQR)12.5%

(6.0 – 21.6%)29.8%

(17.5 – 39.8%)17.4%

(9.5 – 27.1%)8.5%

(3.9 – 14.7%)

Conclusion

iCGM performs well during low to moderate rate of glucose change

However, it has weaknesses in its performance around acute exercise

and hypoglycemia

Adjuvant blood glucose measurements are needed during exercise

and hypoglycemia

These blood glucose measurements can reduce the risk of wrong

therapy decisions based on iCGM interstitial glucose readings

Literature

1. Blum JR, Rayfield EJ. an Endocrine Clinic’S Perspective and Experience With the Abbott FreestyleLibre Cgm. Endocr Pract. 2018;24(3):309-311. doi:10.4158/EP-2017-0136

2. Bolinder J, Antuna R, Geelhoed-Duijvestijn P, Kröger J, Weitgasser R. Novel glucose-sensingtechnology and hypoglycaemia in type 1 diabetes: a multicentre, non-masked, randomised controlledtrial. Lancet. 2016;388(10057):2254-2263. doi:10.1016/S0140-6736(16)31535-5

3. Dover AR, Stimson RH, Zammitt NN, Gibb FW. Flash Glucose Monitoring Improves Outcomes in aType 1 Diabetes Clinic. J Diabetes Sci Technol. 2017;11(2):442-443. doi:10.1177/1932296816661560

4. Haak T, Hanaire H, Ajjan R, Hermanns N, Riveline J-P, Rayman G. Flash Glucose-SensingTechnology as a Replacement for Blood Glucose Monitoring for the Management of Insulin-TreatedType 2 Diabetes: a Multicenter, Open-Label Randomized Controlled Trial. Diabetes Ther.2017;8(1):55-73. doi:10.1007/s13300-016-0223-6

5. Edelman S V., Argento NB, Pettus J, Hirsch IB. Clinical Implications of Real-time and IntermittentlyScanned Continuous Glucose Monitoring. Diabetes Care. 2018;41(11):2265-2274. doi:10.2337/dc18-1150

6. Aberer F, Hajnsek M, Rumpler M, et al. Evaluation of subcutaneous glucose monitoring systems underroutine environmental conditions in patients with type 1 diabetes. Diabetes, Obes Metab.2017;19(7):1051-1055. doi:10.1111/dom.12907

7. Pleus S, Schoemaker M, Morgenstern K, et al. Rate-of-change dependence of the performance of twoCGM systems during induced glucose swings. J Diabetes Sci Technol. 2015;9(4):801-807.doi:10.1177/1932296815578716

Thank you for your attention!

Othmar Moser, Max L. Eckstein, Olivia McCarthy, Rachel Deere, Jason Pitt, David M.

Williams, Jennifer Hayes, Stephen C. Bain, Richard M. Bracken

Cardiovascular Diabetology Research Group

Division of Endocrinology and Diabetology

Department of Internal Medicine

Medical University of Graz, Austria

E-Mail: othmar.moser@medunigraz.at