Nocturnal Continuous Glucose Monitoring: Accuracy and Reliability of Hypoglycemia Detection in Patients with Type 1 Diabetes at High Risk of Severe Hypoglycemia

Bay, Christiane; Kristensen, Peter; Pedersen‐Bjergaard, Ulrik; Tarnow, Lise; Thorsteinsson, Birger

doi:10.1089/dia.2013.0004

Cited by 44 publications

(39 citation statements)

References 22 publications

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“…It is well-known that CGM produces a physiological lag time and moreover a lesser precision in the lower glucose concentration range. [26][27][28] Bode et al tested the accuracy of the CGM system used in our study by comparing home blood glucose meter readings with CGM meter readings. 29 With a hypoglycemic threshold of 3.9 mmol/l (70 mg/dl), the system had a sensitivity of 67%, a specificity of 90%, and a false alarm rate of 47%.…”

Section: Discussionmentioning

confidence: 99%

Combining Information of Autonomic Modulation and CGM Measurements Enables Prediction and Improves Detection of Spontaneous Hypoglycemic Events

Cichosz

Frystyk

Tarnow

et al. 2014

J Diabetes Sci Technol

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Were it not for the risk of hypoglycemic episodes, patients with diabetes could have normal glucose levels over a lifetime of diabetes. Hypoglycemia often results in an increase physical as well as psychosocial morbidity, and is a risk factor for an increased mortality.1,2 Hypoglycemia is very common in patients with type 1 diabetes (T1D).3 Patients trying to improve or maintain a tight glycemic control suffer from innumerable episodes of asymptomatic hypoglycemia. Plasma glucose levels may be less than 60 mg/dl (3.3 mmol/l) 10% of the time, and on average, patients with T1D suffer from 2 weekly incidents of symptomatic hypoglycemia. 1,4,5 Accordingly, patients with diabetes experience thousands of hypoglycemic events over a lifetime. In addition, these patients have a 4.7-fold excess mortality risk compared to healthy subjects. 6 This explains why there is a considerable interest in using continuous glucose monitoring (CGM) devices to detect and warn diabetic patients about an Background: We have previously tested, in a laboratory setting, a novel algorithm that enables prediction of hypoglycemia. The algorithm integrates information of autonomic modulation, based on heart rate variability (HRV), and data based on a continuous glucose monitoring (CGM) device. Now, we investigate whether the algorithm is suitable for prediction of hypoglycemia and for improvement of hypoglycemic detection during normal daily activities.Methods: Twenty-one adults (13 men) with T1D prone to hypoglycemia were recruited and monitored with CGM and a Holter device while they performed normal daily activities. We used our developed algorithm (a pattern classification method) to predict spontaneous hypoglycemia based on CGM and HRV. We compared 3 different models; (i) a model containing raw data from the CGM device; (ii) a CGM* model containing data derived from the CGM device signal; and (iii) a CGM+HRV model-combining model (ii) with HRV data.Results: A total of 12 hypoglycemic events (glucose levels < 3.9 mmol/L, 70 mg/dL) and 237 euglycemic measurements were included. For a 20-minute prediction, model (i) resulted in a ROC AUC of 0.69. If a high sensitivity of 100% was chosen, the corresponding specificity was 69%. (ii) The CGM* model yielded a ROC AUC of 0.92 with a corresponding sensitivity of 100% and specificity of 71%. (iii) The CGM+HRV model yielded a ROC AUC of 0.96 with a corresponding sensitivity of 100% and specificity of 91%.Conclusions: Data shows that adding information of autonomic modulation to CGM measurements enables prediction and improves the detection of hypoglycemia.

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Section: Discussionmentioning

confidence: 99%

Combining Information of Autonomic Modulation and CGM Measurements Enables Prediction and Improves Detection of Spontaneous Hypoglycemic Events

Cichosz

Frystyk

Tarnow

et al. 2014

J Diabetes Sci Technol

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“…Low accuracy and ~0.20g/L overestimation of low glucose ranges [6,10] however lead to low sensitivity and high false alert rates [7]: rates of symptomatic hypoglycaemia [11] and fear of hypoglycaemia [10] do not always reduce in patients using CGM systems. Our study quantified the interest of CGM systems to predict, rather than just detect, a later hypoglycaemic event:…”

Section: Discussionmentioning

confidence: 99%

“…We have shown that trending arrows on CGM devices predict later capillary glucose levels [5]. As the accuracy of CGM devices in the hypoglycemic range has been questioned [6,7], we tested whether trending arrows could predict subsequent capillary glucose level lower than 0.80g/L fifteen minutes later, which would enable proactive or corrective actions.…”

Section: Introductionmentioning

confidence: 99%

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2014

DRTOA

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“…57 CGM studies reporting on nocturnal hypoglycemia should be interpreted with caution due to concerns around the accuracy of glucose sensors at night (ie, due to compression artifacts, disconnections and lack of calibrations at night). [58][59][60] The impact of CGM on nocturnal hypoglycemia has seldom been reported. 29,50 In a study by Garg et al, nocturnal hypoglycemia (<55 mg/dl [3.1 mmol/L]) was reduced by 38% in the display on group compared with the control group (P < .001).…”

Section: Nocturnal Hypoglycemiamentioning

confidence: 99%

Continuous Glucose Monitoring

Beers

DeVries

2016

J Diabetes Sci Technol

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The necessity of strict glycemic control is unquestionable. However, hypoglycemia remains a major limiting factor in achieving satisfactory glucose control, and evidence is mounting to show that hypoglycemia is not benign. Over the past decade, evidence has consistently shown that real-time continuous glucose monitoring improves glycemic control in terms of lowering glycated hemoglobin levels. However, real-time continuous glucose monitoring has not met the expectations of the diabetes community with regard to hypoglycemia prevention. The earlier trials did not demonstrate any effect on either mild or severe hypoglycemia and the effect of real-time continuous glucose monitoring on nocturnal hypoglycemia was often not reported. However, trials specifically designed to reduce hypoglycemia in patients with a high hypoglycemia risk have demonstrated a reduction in hypoglycemia, suggesting that real-time continuous glucose monitoring can prevent hypoglycemia when it is specifically used for that purpose. Moreover, the newest generation of diabetes technology currently available commercially, namely sensor-augmented pump therapy with a (predictive) low glucose suspend feature, has provided more convincing evidence for hypoglycemia prevention. This article provides an overview of the hypoglycemia outcomes of randomized controlled trials that investigate the effect of real-time continuous glucose monitoring alone or sensor-augmented pump therapy with a (predictive) low glucose suspend feature. Furthermore, several possible explanations are provided why trials have not shown a reduction in severe hypoglycemia. In addition, existing evidence is presented of real-time continuous glucose monitoring in patients with impaired awareness of hypoglycemia who have the highest risk of severe hypoglycemia.

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Nocturnal Continuous Glucose Monitoring: Accuracy and Reliability of Hypoglycemia Detection in Patients with Type 1 Diabetes at High Risk of Severe Hypoglycemia

Cited by 44 publications

References 22 publications

Combining Information of Autonomic Modulation and CGM Measurements Enables Prediction and Improves Detection of Spontaneous Hypoglycemic Events

Combining Information of Autonomic Modulation and CGM Measurements Enables Prediction and Improves Detection of Spontaneous Hypoglycemic Events

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Continuous Glucose Monitoring

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