Sensor-augmented pump therapy lowers HbA(1c) in suboptimally controlled Type 1 diabetes; a randomized controlled trial.

AIMS: To investigate the efficacy of sensor-augmented pump therapy vs. multiple daily injection therapy in patients with suboptimally controlled Type 1 diabetes. METHODS: In this investigator-initiated multi-centre trial (the Eurythmics Trial) in eight outpatient centres in Europe, we randomized 83 patients with Type 1 diabetes (40 women) currently treated with multiple daily injections, age 18-65 years and HbA(1c) ≥ 8.2% (≥ 66 mmol/mol) to 26 weeks of treatment with either a sensor-augmented insulin pump (n = 44) (Paradigm(®) REAL-Time) or continued with multiple daily injections (n = 39). Change in HbA(1c) between baseline and 26 weeks, sensor-derived endpoints and patient-reported outcomes were assessed. RESULTS: The trial was completed by 43/44 (98%) patients in the sensor-augmented insulin pump group and 35/39 (90%) patients in the multiple daily injections group. Mean HbA(1c) at baseline and at 26 weeks changed from 8.46% (SD 0.95) (69 mmol/mol) to 7.23% (SD 0.65) (56 mmol/mol) in the sensor-augmented insulin pump group and from 8.59% (SD 0.82) (70 mmol/mol) to 8.46% (SD 1.04) (69 mmol/mol) in the multiple daily injections group. Mean difference in change in HbA(1c) after 26 weeks was -1.21% (95% confidence interval -1.52 to -0.90, P < 0.001) in favour of the sensor-augmented insulin pump group. This was achieved without an increase in percentage of time spent in hypoglycaemia: between-group difference 0.0% (95% confidence interval -1.6 to 1.7, P = 0.96). There were four episodes of severe hypoglycaemia in the sensor-augmented insulin pump group and one episode in the multiple daily injections group (P = 0.21). Problem Areas in Diabetes and Diabetes Treatment Satisfaction Questionnaire scores improved in the sensor-augmented insulin pump group. CONCLUSIONS: Sensor augmented pump therapy effectively lowers HbA(1c) in patients with Type 1 diabetes suboptimally controlled with multiple daily injections.

How to assess and compare the accuracy of continuous glucose monitors?

Continuous glucose monitors may be valuable tools for improving glycemic control and avoiding hypoglycemia in patients with diabetes. To this goal, sensor readings must adequately reflect the actual blood glucose, emphasizing the need for solid accuracy assessment methods for continuous glucose sensor readings. Analysis of continuous glucose data is challenging, and despite many efforts there still is no all-embracing method to overcome the obstacles in the assessment of continuous data. In this review we disclose the weaknesses of currently available methods and propose a guideline for sensor accuracy assessment and comparison. For accuracy assessment it is best to first plot the sensor readings against the reference values and draw a line of identity, visualizing the degree of agreement. Thereafter data pairs should be given in a Bland-Altman plot to detect a possible relationship between the difference and the mean. The next step is to calculate the absolute relative difference over all paired readings together and per glucose range. A possible lag time between the measurements of both methods can be detected by combined curve fitting. Finally, sensitivity and positive predictive value for detecting hypoglycemia are important indicators of the sensors' performance. For comparing the accuracy between different glucose sensors it is best to use indirect comparison against blood glucose, rather than direct comparison methods, since none of the current glucose sensors is accurate enough to be considered the reference value.

Glucose fluctuations and activation of oxidative stress in patients with type 1 diabetes.

AIMS/HYPOTHESIS: Glucose fluctuations may help predict diabetic complications. We evaluated the relation between glucose variability and oxidative stress in patients with type 1 diabetes. METHODS: Continuous glucose monitors were inserted subcutaneously in 25 patients. During the measurement, patients collected two 24 h urine samples, while 24 healthy controls collected one 24 h urine sample for determination of 15(S)-8-iso-prostaglandin F2alpha(PGF2alpha) using HPLC tandem mass spectrometry. Mean of the daily differences (MODD), mean amplitude of glycaemic excursions (MAGE) and continuous overlapping net glycaemic action calculated with n hour time-intervals (CONGA-n) were calculated as markers for glucose variability and correlation with 15(S)-8-iso-PGF2alpha excretion was calculated. RESULTS: Median [interquartile range (IQR)] urinary 15(S)-8-iso-PGF2alpha was higher in patients than healthy controls: 161 (140-217) pg/mg creatinine vs 118 (101-146) pg/mg creatinine (p = 0.001). Median (IQR) MODD was 3.7 (3.2-5.0) mmol/l, MAGE 7.6 (6.4-9.0) mmol/l and CONGA-1 2.3 (2.1-2.8) mmol/l. Univariate regression did not reveal an association for MODD (r2 = 0.01), MAGE (0.08) or CONGA-1 (0.07) with 15(S)-8-iso-PGF2alpha excretion, nor was an association revealed when corrected for HbA1c, age, sex and smoking. Spearman correlation coefficients (r) between 15(S)-8-iso-PGF2alpha excretion and MODD, MAGE and CONGA-1 were non-significant: -0.112, -0.381 and -0.177. CONCLUSIONS/INTERPRETATION: We report that there is no relationship between glucose variability and urinary 15(S)-8-iso-PGF2alpha. We also confirm that patients with type 1 diabetes have higher levels of urinary 15(S)-8-iso-PGF2alpha than healthy controls, suggesting that in addition to glucose variability, other factors favouring oxidative stress may exist. We did not see a relation between high glucose variability and elevated levels of oxidative stress in patients with type 1 diabetes.

Continuous glucose monitors: the long-awaited watch dogs?

To date, several continuous glucose sensors have been developed and launched in the U.S. and European markets, though large-scale application in standard diabetes care still awaits its breakthrough. This report offers an overview of the current applications and clinically relevant aspects of continuous glucose monitors (CGMs), e.g., the calibration procedure, interpretation of continuous glucose data, and some important limitations. It is still difficult to state with certainty that CGMs allow effective improvement in glycemic control for the majority of patients with type 1 diabetes, in view of the paucity of controlled studies showing an impact on hemoglobin A1c or frequency of hypoglycemia, even if such a tendency seems to emerge from most non-controlled intervention trials. Future controlled trials should also take into account patient-related outcomes, to evaluate the effect of CGMs on health status, treatment satisfaction, and fear of hypoglycemia. Increased accuracy and reimbursement are key to further implementation of CGMs.

Nocturnal hypoglycaemia in Type 1 diabetic patients, assessed with continuous glucose monitoring: frequency, duration and associations.

AIMS: We quantified the occurrence and duration of nocturnal hypoglycaemia in individuals with Type 1 diabetes treated with continuous subcutaneous insulin infusion (CSII) or multiple-injection therapy (MIT) using a continuous subcutaneous glucose sensor. METHODS: A microdialysis sensor was worn at home by 24 patients on CSII (mean HbA(1c) 7.8 +/- 0.9%) and 33 patients on MIT (HbA(1c) 8.7 +/- 1.3%) for 48 h. Occurrence and duration of nocturnal hypoglycaemia were assessed and using multivariate regression analysis, the association between HbA(1c), diabetes duration, treatment type (CSII vs. MIT), fasting and bedtime blood glucose values, total daily insulin dose and mean nocturnal glucose concentrations, and hypoglycaemia occurrence and duration was investigated. RESULTS: Nocturnal hypoglycaemia < or = 3.9 mmol/l occurred in 33.3% of both the CSII- (8/24) and MIT-treated patients (11/33). Mean (+/- sd; median, interquartile range) duration of hypoglycaemia < or = 3.9 mmol/l was 78 (+/- 76; 57, 23-120) min per night for the CSII- and 98 (+/- 80; 81, 32-158) min per night for the MIT-treated group. Multivariate regression analysis showed that bedtime glucose value had the strongest association with the occurrence (P = 0.026) and duration (P = 0.032) of nocturnal hypoglycaemia. CONCLUSIONS: Microdialysis continuous glucose monitoring has enabled more precise quantification of nocturnal hypoglycaemia occurrence and duration in Type 1 diabetic patients. Occurrence and duration of nocturnal hypoglycaemia were mainly associated with bedtime glucose value.

Pendra goes Dutch: lessons for the CE mark in Europe.

The development of a truly non-invasive continuous glucose sensor is an elusive goal. We describe the rise and fall of the Pendra device. In 2000 the company Pendragon Medical introduced a truly non-invasive continuous glucose-monitoring device. This system was supposed to work through so-called impedance spectroscopy. Pendra was Conformité Européenne (CE) approved in May 2003. For a short time the Pendra was available on the Dutch direct-to-consumer market. A post-marketing reliability study was performed in six type 1 diabetes patients. Mean absolute difference between Pendra glucose values and values obtained through self-monitoring of blood glucose was 52%; the Pearson's correlation coefficient was 35.1%; and a Clarke error grid showed 4.3% of the Pendra readings in the potentially dangerous zone E. We argue that the CE certification process for continuous glucose sensors should be made more transparent, and that a consensus on specific requirements for continuous glucose sensors is needed to prevent patient exposure to potentially dangerous situations.