Literature DB >> 26307604

Effect of lipohypertrophy on accuracy of continuous glucose monitoring in patients with type 1 diabetes.

Daniel J DeSalvo1, David M Maahs2, Laurel Messer2, R Paul Wadwa2, Shelby Payne1, Trang T Ly3, Bruce A Buckingham4.   

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Year:  2015        PMID: 26307604      PMCID: PMC4876738          DOI: 10.2337/dc15-1267

Source DB:  PubMed          Journal:  Diabetes Care        ISSN: 0149-5992            Impact factor:   19.112


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Repeated delivery of insulin in the same location induces a local reaction in the subcutaneous adipose tissue, often leading to lipohypertrophy (1,2). Advanced lipohypertrophy leads to slower, erratic insulin absorption due to the fibrous, relatively avascular nature of the tissue (3). Although lipohypertrophied tissue is commonly used for continuous glucose monitoring (CGM) sensor sites, the effect on sensor performance is unknown. Therefore, we analyzed the accuracy of sensors used simultaneously in lipohypertrophied and normal tissue. In this prospective, multicenter study, subjects with type 1 diabetes and lipohypertrophy (≥3 cm diameter) were instructed to wear two Dexcom G4 Platinum sensors simultaneously: one in lipohypertrophied tissue and the second in normal tissue for 2 consecutive weeks. This procedure was then repeated on each subject with new sensors being worn simultaneously for a second 2-week period. Blood glucose (BG) readings from Bayer CONTOUR NEXT meters served as reference (4), with absolute relative difference (ARD) defined as the percent error between sensor and matched BG values. Only data from the first 7 days of sensor life were used in the analysis. The Mann-Whitney U test was used to compare the accuracy of the sensors in lipohypertrophied versus normal tissue. Results are presented as mean ± SD or median (interquartile range [25th%, 75th%]). Twenty-nine subjects enrolled in the study. Baseline characteristics included 48% men, age of 29.6 ± 8.9 years, duration of diabetes of 17.3 ± 9.1 years, and hemoglobin A1c of 7.5 ± 0.8% (58 ± 8.7 mmol/mol). The average diameter of lipohypertrophy was 8.1 ± 3.5 cm. In total, there were 89,853 sensor glucose values between 40 and 400 mg/dL (range of sensor) with 1,547 corresponding BG readings. The median ARD for sensors in lipohypertrophied tissue was 10.0% (4.3, 17.2) versus 11.0% (4.9, 19.3) in normal tissue (P < 0.001). For BG ≤70 mg/dL, mean absolute difference (MAD) for sensors in lipohypertrophied tissue was 15 mg/dL (n = 49) compared with 18 mg/dL (n = 48) in normal tissue (P = 0.14). For BG ≥250 mg/dL, median ARD was 9.8% (4.6, 15.8) (n = 341) for sensors in lipohypertrophied tissue compared with 9.6% (4.8, 16.4) (n = 334) in normal tissue (P = 0.44) (Table 1).
Table 1

Accuracy analysis of sensors in normal tissue compared with sensors in lipohypertrophied tissue

Sensor in normal tissueSensor in lipohypertrophied tissueP value
N of samples paired with reference meter value1,5371,547
Mean ARD14.6 ± 15.0%13.2 ± 14.3%N/A§
Median ARD11.0% (4.9, 19.3)10.0% (4.3, 17.2)<0.001
MAD for BG ≤70 mg/dL18 mg/dL (n = 48)15 mg/dL (n = 49)0.14
Median ARD for BG ≥250 mg/dL9.6% (4.8, 16.4) (n = 334)9.8% (4.6, 15.8) (n = 341)0.44
±20 mg/dL for BG ≤80 mg/dL*66.4% (n = 104)71.4% (n = 105)0.34
±20% for BG >80 mg/dL79.9% (n = 1,433)85.3% (n = 1,442)0.003
Overall %20/2079.0%81.8%0.051

Data are n, mean ± SD, or median (interquartile range [25th%, 75th%]), unless stated otherwise.

Proportion of all sensor values that were within ±20 mg/dL of reference meter value for BG ≤80 mg/dL.

Proportion of all sensor values that were within ±20% of reference meter value for BG >80 mg/dL.

Proportion of all sensor values that were within ±20 mg/dL of reference meter value for BG ≤80 mg/dL or within ±20% of reference meter value for BG >80 mg/dL.

Data not evenly distributed.

Accuracy analysis of sensors in normal tissue compared with sensors in lipohypertrophied tissue Data are n, mean ± SD, or median (interquartile range [25th%, 75th%]), unless stated otherwise. Proportion of all sensor values that were within ±20 mg/dL of reference meter value for BG ≤80 mg/dL. Proportion of all sensor values that were within ±20% of reference meter value for BG >80 mg/dL. Proportion of all sensor values that were within ±20 mg/dL of reference meter value for BG ≤80 mg/dL or within ±20% of reference meter value for BG >80 mg/dL. Data not evenly distributed. In this analysis, CGM sensors in lipohypertrophied tissue showed equal or slightly superior accuracy to sensors in normal tissue. This was evident across all glucose ranges, with an overall median ARD of 10.0% for sensors in lipohypertrophied tissue. The question remains as to whether sensors cause harm to the skin or subcutaneous tissue by repeated insertions in the same area. Although nothing is infused at sensor sites, the insertion and subsequent movement of the sensor tip might induce acute local trauma and possibly more chronic skin reactions (5). However, our data suggest that the flow of interstitial fluid is not adversely affected by the lipohypertrophied tissue. To our knowledge, this is the first study evaluating the effect of lipohypertrophy on CGM performance. Our results suggest that lipohypertrophy does not adversely impact sensor accuracy. Further work is needed to quantify the potential risks of sensor use in areas of lipohypertrophy over longer periods of time.
  5 in total

1.  Prevalence and risk factors of lipohypertrophy in insulin-injecting patients with diabetes.

Authors:  M Blanco; M T Hernández; K W Strauss; M Amaya
Journal:  Diabetes Metab       Date:  2013-07-22       Impact factor: 6.041

2.  Lipohypertrophy and the artificial pancreas: is this an issue?

Authors:  Lutz Heinemann; Larry Hirsch; Roman Hovorka
Journal:  J Diabetes Sci Technol       Date:  2014-06-16

3.  Prevalence of lipohypertrophy in insulin-treated diabetic patients and predisposing factors.

Authors:  H Hauner; B Stockamp; B Haastert
Journal:  Exp Clin Endocrinol Diabetes       Date:  1996       Impact factor: 2.949

Review 4.  Insulin absorption from lipodystrophic areas: a (neglected) source of trouble for insulin therapy?

Authors:  Lutz Heinemann
Journal:  J Diabetes Sci Technol       Date:  2010-05-01

5.  Accuracy evaluation of blood glucose monitoring systems in children on overnight closed-loop control.

Authors:  Daniel J DeSalvo; Satya Shanmugham; Trang T Ly; Darrell M Wilson; Bruce A Buckingham
Journal:  J Diabetes Sci Technol       Date:  2014-05-21
  5 in total
  6 in total

1.  Factory-Calibrated Continuous Glucose Monitoring: How and Why It Works, and the Dangers of Reuse Beyond Approved Duration of Wear.

Authors:  Gregory P Forlenza; Taisa Kushner; Laurel H Messer; R Paul Wadwa; Sriram Sankaranarayanan
Journal:  Diabetes Technol Ther       Date:  2019-02-28       Impact factor: 6.118

2.  Preserving Skin Integrity with Chronic Device Use in Diabetes.

Authors:  Laurel H Messer; Cari Berget; Christie Beatson; Sarit Polsky; Gregory P Forlenza
Journal:  Diabetes Technol Ther       Date:  2018-06       Impact factor: 6.118

3.  Ultrasound characterization of insulin induced lipohypertrophy in type 1 diabetes mellitus.

Authors:  F Bertuzzi; E Meneghini; E Bruschi; L Luzi; M Nichelatti; O Epis
Journal:  J Endocrinol Invest       Date:  2017-04-27       Impact factor: 4.256

4.  Duration of Infusion Set Survival in Lipohypertrophy Versus Nonlipohypertrophied Tissue in Patients with Type 1 Diabetes.

Authors:  Andrew W Karlin; Trang T Ly; Laura Pyle; Gregory P Forlenza; Laurel Messer; R Paul Wadwa; Daniel J DeSalvo; Sydney L Payne; Sarah Hanes; Paula Clinton; David M Maahs; Bruce Buckingham
Journal:  Diabetes Technol Ther       Date:  2016-05-26       Impact factor: 6.118

5.  Continuous Glucose Monitoring in the Real World Using Photosurveillance of #Dexcom on Instagram: Exploratory Mixed Methods Study.

Authors:  Michelle L Litchman; Sarah E Wawrzynski; Whitney S Woodruff; Joseph B Arrington; Quynh C Nguyen; Perry M Gee
Journal:  JMIR Public Health Surveill       Date:  2019-05-24

6.  Diabetes Technology Meeting 2020.

Authors:  Trisha Shang; Jennifer Y Zhang; B Wayne Bequette; Jennifer K Raymond; Gerard Coté; Jennifer L Sherr; Jessica Castle; John Pickup; Yarmela Pavlovic; Juan Espinoza; Laurel H Messer; Tim Heise; Carlos E Mendez; Sarah Kim; Barry H Ginsberg; Umesh Masharani; Rodolfo J Galindo; David C Klonoff
Journal:  J Diabetes Sci Technol       Date:  2021-07
  6 in total

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