Literature DB >> 16800753

Evaluation of factors affecting CGMS calibration.

Bruce A Buckingham, Craig Kollman, Roy Beck, Andrea Kalajian, Rosanna Fiallo-Scharer, Michael J Tansey, Larry A Fox, Darrell M Wilson, Stuart A Weinzimer, Katrina J Ruedy, William V Tamborlane.   

Abstract

BACKGROUND: The optimal number/timing of calibrations entered into the CGMS (Medtronic MiniMed, Northridge, CA) continuous glucose monitoring system have not been previously described.
METHODS: Fifty subjects with Type 1 diabetes mellitus (10-18 years old) were hospitalized in a clinical research center for approximately 24 h on two separate days. CGMS and OneTouch Ultra meter (LifeScan, Milpitas, CA) data were obtained. The CGMS was retrospectively recalibrated using the Ultra data varying the number and timing of calibrations. Resulting CGMS values were compared against laboratory reference values.
RESULTS: There was a modest improvement in accuracy with increasing number of calibrations. The median relative absolute deviation (RAD) was 14%, 15%, 13%, and 13% when using three, four, five, and seven calibration values, respectively (P < 0.001). Corresponding percentages of CGMS-reference pairs meeting the International Organisation for Standardisation criteria were 66%, 67%, 71%, and 72% (P < 0.001). Nighttime accuracy improved when daytime calibrations (pre-lunch and pre-dinner) were removed leaving only two calibrations at 9 p.m. and 6 a.m. (median difference, -2 vs. -9 mg/dL, P < 0.001; median RAD, 12% vs. 15%, P = 0.001). Accuracy was better on visits where the average absolute rate of glucose change at the times of calibration was lower. On visits with average absolute rates <0.5, 0.5 to <1.0, 1.0 to <1.5, and >or=1.5 mg/dL/min, median RAD values were 13% versus 14% versus 17% versus 19%, respectively (P = 0.05).
CONCLUSIONS: Although accuracy is slightly improved with more calibrations, the timing of the calibrations appears more important. Modifying the algorithm to put less weight on daytime calibrations for nighttime values and calibrating during times of relative glucose stability may have greater impact on accuracy.

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Year:  2006        PMID: 16800753      PMCID: PMC1483845          DOI: 10.1089/dia.2006.8.318

Source DB:  PubMed          Journal:  Diabetes Technol Ther        ISSN: 1520-9156            Impact factor:   6.118


  9 in total

1.  Do sensor glucose levels accurately predict plasma glucose concentrations during hypoglycemia and hyperinsulinemia?

Authors:  Teresa P Monsod; Daniel E Flanagan; Fran Rife; Rebecca Saenz; Sonia Caprio; Robert S Sherwin; William V Tamborlane
Journal:  Diabetes Care       Date:  2002-05       Impact factor: 19.112

2.  Calibration of a subcutaneous amperometric glucose sensor implanted for 7 days in diabetic patients. Part 2. Superiority of the one-point calibration method.

Authors:  C Choleau; J C Klein; G Reach; B Aussedat; V Demaria-Pesce; G S Wilson; R Gifford; W K Ward
Journal:  Biosens Bioelectron       Date:  2002-08       Impact factor: 10.618

3.  A continuous glucose sensor based on wired enzyme technology -- results from a 3-day trial in patients with type 1 diabetes.

Authors:  Ben Feldman; Ronald Brazg; Sherwyn Schwartz; Richard Weinstein
Journal:  Diabetes Technol Ther       Date:  2003       Impact factor: 6.118

4.  Evaluation and comparison of 10 glucose methods and the reference method recommended in the proposed product class standard (1974).

Authors:  R B Passey; R L Gillum; J B Fuller; F M Urry; M L Giles
Journal:  Clin Chem       Date:  1977-01       Impact factor: 8.327

5.  Accuracy of the modified Continuous Glucose Monitoring System (CGMS) sensor in an outpatient setting: results from a diabetes research in children network (DirecNet) study.

Authors:  Michael J Tansey; Roy W Beck; Bruce A Buckingham; Nelly Mauras; Rosanna Fiallo-Scharer; Dongyuan Xing; Craig Killman; William V Tamborlane; Katrina J Ruedy
Journal:  Diabetes Technol Ther       Date:  2005-02       Impact factor: 6.118

6.  Impact of exercise on overnight glycemic control in children with type 1 diabetes mellitus.

Authors:  Eva Tsalikian; Nelly Mauras; Roy W Beck; William V Tamborlane; Kathleen F Janz; H Peter Chase; Tim Wysocki; Stuart A Weinzimer; Bruce A Buckingham; Craig Kollman; Dongyuan Xing; Katrina J Ruedy
Journal:  J Pediatr       Date:  2005-10       Impact factor: 4.406

7.  Timing of changes in interstitial and venous blood glucose measured with a continuous subcutaneous glucose sensor.

Authors:  Michael S Boyne; David M Silver; Joy Kaplan; Christopher D Saudek
Journal:  Diabetes       Date:  2003-11       Impact factor: 9.461

8.  The accuracy of the CGMS in children with type 1 diabetes: results of the diabetes research in children network (DirecNet) accuracy study.

Authors: 
Journal:  Diabetes Technol Ther       Date:  2003       Impact factor: 6.118

9.  Spurious reporting of nocturnal hypoglycemia by CGMS in patients with tightly controlled type 1 diabetes.

Authors:  Kilty McGowan; William Thomas; Antoinette Moran
Journal:  Diabetes Care       Date:  2002-09       Impact factor: 19.112

  9 in total
  37 in total

1.  Continuous glucose monitoring to assess the ecologic validity of dietary glycemic index and glycemic load.

Authors:  Anthony N Fabricatore; Cara B Ebbeling; Thomas A Wadden; David S Ludwig
Journal:  Am J Clin Nutr       Date:  2011-11-09       Impact factor: 7.045

2.  Do different glucose levels at calibration influence accuracy of continuous glucose monitoring readings in vitro?

Authors:  Katherine E Iscoe; Raymond J Davey; Paul A Fournier
Journal:  J Diabetes Sci Technol       Date:  2012-03-01

3.  Real-time glucose estimation algorithm for continuous glucose monitoring using autoregressive models.

Authors:  Yenny Leal; Winston Garcia-Gabin; Jorge Bondia; Eduardo Esteve; Wifredo Ricart; Jose-Manuel Fernández-Real; Josep Vehí
Journal:  J Diabetes Sci Technol       Date:  2010-03-01

4.  Continuous glucose monitoring: real-time algorithms for calibration, filtering, and alarms.

Authors:  B Wayne Bequette
Journal:  J Diabetes Sci Technol       Date:  2010-03-01

Review 5.  Toward closing the loop: an update on insulin pumps and continuous glucose monitoring systems.

Authors:  Tandy Aye; Jen Block; Bruce Buckingham
Journal:  Endocrinol Metab Clin North Am       Date:  2010-09       Impact factor: 4.741

6.  In vivo, transcutaneous glucose sensing using surface-enhanced spatially offset Raman spectroscopy: multiple rats, improved hypoglycemic accuracy, low incident power, and continuous monitoring for greater than 17 days.

Authors:  Ke Ma; Jonathan M Yuen; Nilam C Shah; Joseph T Walsh; Matthew R Glucksberg; Richard P Van Duyne
Journal:  Anal Chem       Date:  2011-11-02       Impact factor: 6.986

7.  Glycaemic control is improved by 7 days of aerobic exercise training in patients with type 2 diabetes.

Authors:  C R Mikus; D J Oberlin; J Libla; L J Boyle; J P Thyfault
Journal:  Diabetologia       Date:  2012-02-04       Impact factor: 10.122

8.  Modeling the error of continuous glucose monitoring sensor data: critical aspects discussed through simulation studies.

Authors:  Andrea Facchinetti; Giovanni Sparacino; Claudio Cobelli
Journal:  J Diabetes Sci Technol       Date:  2010-01-01

9.  Continuous glucose monitoring in the subcutaneous tissue over a 14-day sensor wear period.

Authors:  Udo Hoss; Erwin S Budiman; Hanqing Liu; Mark P Christiansen
Journal:  J Diabetes Sci Technol       Date:  2013-09-01

10.  The correlation of hemoglobin A1c to blood glucose.

Authors:  Ken Sikaris
Journal:  J Diabetes Sci Technol       Date:  2009-05-01
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