Education on sensor-augmented pump use improves glucose control in type 1 diabetic patients

Abstract

A rather large subset of type 1 diabetic patients fails to achieve their therapeutic goals in spite of a basal-bolus insulin regimen, frequent self-monitoring of capillary blood glucose (CBG) and tight medical follow-up [1]. Therefore, we investigated prospectively the effectiveness of specific education on the use of a sensoraugmented pump for improving glucose control in such poorly controlled type-1 diabetes patients in clinical practice.Nine patients (six men, three women), aged 49 ± 13 (mean ± SD) years, with type 1 diabetes since age 30 ± 11 years and a sustained glycated haemoglobin (HbA 1c ) level greater than 7% were recruited into the study. All had poor metabolic control while under a basal-bolus insulin regimen (six patients by multiple daily insulin injections, three by portable insulin pump), using insulin analogues, and performing daily multiple CBG tests (5.5/day on average), and attending our clinic as outpatients every 2-3 months. All were taught how to use a sensor-augmented insulin pump (Paradigm Real Time ® , Medtronic MiniMed, Northridge, CA, USA) [2]. The enzymatic glucose sensor generates a continuous signal, which is transmitted online wirelessly to a pump, resulting in an estimation of blood glucose every 5 min on the pump screen. Recent glucose profiles, the current trend and hypo or hyperalarms are also available [2]. The glucose sensor was calibrated twice daily against CBG and replaced every 3 days by the patient. Patients were also taught how to adapt insulin delivery and carbohydrate intakes according to glucose levels and trends, while maintaining their usual CBG testing. A CBG test was requested before taking any action in cases of a hypo/hyper alarm. Outpatients visits were scheduled after 1.5, 3 and 6 months. Glucose control was assessed at baseline (BL or MO), and after 3 (M3) and 6 (M6) months of follow-up, from HbA 1c levels. In addition, CBG values recorded during the previous month and still in the metre's memory were carefully analyzed to calculate mean values, distribution across target ranges and indices of variability (standard deviation or SD, or mean amplitude of glycaemic excursions [MAGE]).During the 6-month follow-up, HbA 1c levels were significantly decreased from 8.5 ±1.3% (BL) to 8.2 ±1.6% (M3, P = 0.049) and 7.8 ± 0.7% (M6, P = 0.047). A strongly positive correlation was observed between baseline HbA 1c levels and the reduction in HbA 1c levels after 6 months of follow-up (r = 0.78; P < 0.001). While mean glucose levels were not significantly altered, the distribution of CBG values was improved with, in particular, a higher number of CBG measurements within the targets set (80-140 mg/dL; P < 0.0001). However, no significant changes in indices of glucose variability were detected, perhaps because of the rather small number of participants in the study (Table 1). No severe hypoglycaemia or ketosis occurred during the follow-up, and no adverse events related to sensor-augmented pump use were reported.Our data, as with those obtained in other studies [3][4][5][6]...

Continuous glucose monitoring reduces both hypoglycaemia and HbA1c in hypoglycaemia-prone type 1 diabetic patients treated with a portable pump

“…However, the sustained benefits of CGM use have been controversial in clinical practice so far [8,15]. Permanent use of the Guardian RT device for 3 months significantly improved HbA 1c levels compared with SMBG, while intermittent CGM use showed no significant benefit [6].…”

“…Until now, the demonstrated benefits of CGM have focused on reducing HbA 1c in patients who were far from achieving their targeted HbA 1c levels [7,8], while outcomes of CGM use on the occurrence of hypoglycaemia have been poorly investigated and for short time-periods only [9]. For this reason, the present study aimed to assess glucose control with 12-week CGM use compared with the usual SMBG in hypoglycaemia-prone T1DM patients treated by CSII.…”

Developing a sensor-based learning concentration detection system

“…In recent years, sensors have been used more widely in association with computer networks in various applications (Alberola and Pesch, 2012;Cheng and Chang, 2012;Lohner and Camelli, 2005;Manolas et al, 2000), including resource management (Chow et al, 2006;Poon et al, 2009;Zhao et al, 2012), machine monitoring (Mrad, 2007;Zhou et al, 2012), medical treatment (Dror et al, 2009;Lee et al, 2011;Townsend et al, 2011), home care services (Thielen et al, 2010) and environmental monitoring ( Jiang et al, 2009( Jiang et al, , 2003Marichal et al, 2009). Moreover, educators are also using this technology to improve student learning Chu et al, 2010;Huang et al, , 2012aLin et al, 2011), due to the advantages of low cost and fast data collection.…”