Alarm Characterization for Continuous Glucose Monitors Used as Adjuncts to Self-Monitoring of Blood Glucose

McGarraugh, Geoffrey

doi:10.1177/193229681000400106

Cited by 12 publications

(10 citation statements)

References 4 publications

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“…9 There has been extensive study of the effectiveness of alarms for the commercial CGM devices. [10][11][12][13][14] Various algorithmic methods for predictive alarms have also been proposed based on linear regression, 15 time series, 16 and optimal estimation theory. 17 In order to be effective in reducing the incidence of hypoglycemia, alarms must be accompanied by some type of action.…”

Section: Discussionmentioning

confidence: 99%

Hypoglycemia Prevention via Pump Attenuation and Red-Yellow-Green “Traffic” Lights Using Continuous Glucose Monitoring and Insulin Pump Data

Hughes

Patek

Breton

et al. 2010

J Diabetes Sci Technol

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This article offers, for the first time, a method for smoothly reducing insulin delivery rate to prevent hypoglycemia in individuals with type 1 diabetes mellitus based on a mathematically formal assessment of hypoglycemic risk. In silico, we demonstrate the way this method can prevent hypoglycemia while avoiding hyperglycemia rebounds that exceed 180 mg/dl. In conjunction with the pump attenuation algorithms, this article also proposes a system for alerting an individual of their hypoglycemic risk that contains three "levels" of alerts in the form of a traffic light. This alert system can be used in an advisory mode setting to alert the user to take action when hypoglycemia is imminent ("red" light) or in a closed-loop setting where initiation of rescue action begins when the red light alert is triggered.

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Section: Discussionmentioning

confidence: 99%

Hypoglycemia Prevention via Pump Attenuation and Red-Yellow-Green “Traffic” Lights Using Continuous Glucose Monitoring and Insulin Pump Data

Hughes

Patek

Breton

et al. 2010

J Diabetes Sci Technol

View full text Add to dashboard Cite

show abstract

“…False alarms for glucose >85 mg/dl were also evaluated at each setting; when glucose is ≤85 mg/dl and descending, alarms are not necessarily false, because it is prudent to consider raising glucose to a safer level under these conditions. 7 High alarms were evaluated differently than low alarms. Since the FreeStyle Navigator CGM is more accurate in the hyperglycemic range, 1 the detection of a high glucose value was reported only for the alarm set at that value.…”

Section: Analysis Methodsmentioning

confidence: 99%

FreeStyle Navigator Continuous Glucose Monitoring System with TRUstart Algorithm, a 1-Hour Warm-up Time

McGarraugh

Brazg

Weinstein

2011

J Diabetes Sci Technol

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“…A key source of feedback that may help mitigate hypoglycemia and improve driving safety in diabetes is continuous glucose monitoring 27 with real-time feedback of low glucose levels via auditory and tactile alarms. 28 …”

Section: At the Crossroads: Questions For Dr Rizzomentioning

confidence: 99%

Impaired Driving From Medical Conditions

Rizzo¹

2011

JAMA

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Some medical disorders can impair performance, increasing the risk of driving safety errors that can lead to vehicle crashes. The causal pathway often involves a concatenation of factors or events, some of which can be prevented or controlled. Effective interventions can operate before, during, or after a crash occurs at the levels of driver capacity, vehicle and road design, and public policy. A variety of systemic, neurological, psychiatric, and developmental disorders put drivers at potential increased risk of a car crash in the short or long term. Medical diagnosis and age alone are usually insufficient criteria for determining fitness to drive. Strategies are needed for determining what types and levels of reduced function provide a threshold for disqualification in drivers with medical disorders. Evidence of decreased mileage, self-restriction to driving in certain situations, collisions, moving violations, aggressive driving, sleepiness, alcohol abuse, metabolic disorders, and multiple medications may trigger considerations of driver safety. A general framework for evaluating driver fitness relies on a functional evaluation of multiple domains (cognitive, motor, perceptual, and psychiatric) that are important for safe driving and can be applied across many disorders, including conditions that have rarely been studied with respect to driving, and in patients with multiple conditions and medications. Neurocognitive tests, driving simulation, and road tests provide complementary sources of evidence to evaluate driver safety. No single test is sufficient to determine who should drive and who should not.

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Alarm Characterization for Continuous Glucose Monitors Used as Adjuncts to Self-Monitoring of Blood Glucose

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Cited by 12 publications

References 4 publications

Hypoglycemia Prevention via Pump Attenuation and Red-Yellow-Green “Traffic” Lights Using Continuous Glucose Monitoring and Insulin Pump Data

Hypoglycemia Prevention via Pump Attenuation and Red-Yellow-Green “Traffic” Lights Using Continuous Glucose Monitoring and Insulin Pump Data

FreeStyle Navigator Continuous Glucose Monitoring System with TRUstart Algorithm, a 1-Hour Warm-up Time

Impaired Driving From Medical Conditions

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