Assessment of risk for severe hypoglycemia among adults with IDDM: validation of the low blood glucose index.

Kovatchev, Boris; Cox, Daniel J.; Gonder-Frederick, L; Young-Hyman, Deborah Lee; Schlundt, David G.; Clarke, William L.

doi:10.2337/diacare.21.11.1870

Cited by 280 publications

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“…The 90 th percentile HYPO score and LBGI was 377 and 3.97, respectively, lower than the values found in a previous study for high risk of severe hypoglycemia (LBGI of 5; 78 th percentile according to Kovatchev et al) [15]. The HYPO score was correlated with the LBGI (Table 2) and the HYPO score of recalled episodes over the previous year showed a weak correlation with the HYPO score measured over the fourweek SMBG period (r = 0.28, P < 0.05).…”

Section: Discussioncontrasting

confidence: 48%

“…However, in our study group, the 90 th percentile value of the HYPO score was 376.9. In addition, the value of LBGI was lower that the cutoff value for a high risk of hypoglycemia suggested by Kovatchev et al (LBGI > 5) [15]. These differences can be explained by the fact that the duration of diabetes in our group was different from that in Ryan et al We observed that the hypoglycemic index weakly correlated with the duration of diabetes, as was the case in previous studies [15,24].…”

Section: Declaration Of Competing Interestscontrasting

confidence: 48%

“…In addition, the value of LBGI was lower that the cutoff value for a high risk of hypoglycemia suggested by Kovatchev et al (LBGI > 5) [15]. These differences can be explained by the fact that the duration of diabetes in our group was different from that in Ryan et al We observed that the hypoglycemic index weakly correlated with the duration of diabetes, as was the case in previous studies [15,24]. In subgroup analysis of the group with a duration of diabetes longer than five years (median: 13.5 years), the 90 th percentile value of the HYPO score was 351.0, which was still lower than that of Ryan et al Another possible reason for the difference is that the results of recalled frequency of hypoglycemia may be incorrect; however, the hypoglycemic events based on a year of recalled episodes correlated with the results from the four-week records in both this study group (r = 0.28, P < 0.05) and in the study by Ryan et al A recently performed STAR 3 study reported that the incidence of hypoglycemic events was lower than that previously reported in the DCCT study [24] due references…”

Section: Declaration Of Competing Interestsmentioning

confidence: 97%

“…The HYPO score was devised based on the frequency, severity, and degree of unawareness of hypoglycemia recorded over a four-week period and for episodes that could be recalled in the previous year and is used to measures the severity of hypoglycemia [7]. The LBGI is extracted from a series of SMBG data, increases with the frequency and extent of hypoglycemic events and is used to predict the occurrence of severe hypoglycemia [15,16]. An LBGI > 5, which represented the 78 th value in the study of Kovatchev et al, was categorized as indicating high risk for severe hypoglycemia.…”

Section: Measurements and Data Analysismentioning

confidence: 99%

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Assessment of glycemic lability and severity of hypoglycemia in Korean patients with type 1 diabetes

et al. 2011

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Pancreas or islet transplantation is recommended for individuals with type 1 diabetes who present with frequent and severe hypoglycemia and/or severe glycemic lability, despite efforts to optimize glycemic control [1]. For these patients, pancreas or islet transplantation has led to successful treatment of these problems [2][3][4]. Pancreas and islet transplantations have previously been performed in Korea [5,6].Clinicians can judge whether patients with type 1 diabetes have problems with glycemic lability and/or severe hypoglycemia, but it is difficult to quantify the glycemic lability and hypoglycemia.Attempts have been made to quantify both hypoglycemia and glycemic lability to allow for betweenAssessment of glycemic lability and severity of hypoglycemia in Korean patients with type 1 diabetes abstract. Few studies have focused on the quantification of glycemic lability and hypoglycemic events in Asian patients with type 1 diabetes; therefore, we conducted a study to assess glycemic lability and the severity of hypoglycemia in type 1 diabetic patients in Korea. A total of 124 type 1 diabetic patients were enrolled. Several glycemic lability indexes and hypoglycemic indexes were calculated using four-week self-monitoring of blood glucose (SMBG) data. Due to the dependence of the lability index (LI) on the frequency of glucose measurements, we generated a modified LI by dividing by the number of SMBG measurements per day for a given patient. The numbers of patients in our study with a composite hypoglycemic score ≥ 1,047 or LI ≥ 433 mmol/L 2 /h·week -1 , which was found in a previous study to indicate high risk of severe hypoglycemia or lability, were 0 (0%) and 44 (35%), respectively. Compared to previously reported hypoglycemia indexes, the low blood glucose index was lower in our study. However, the glycemic lability indexes were similar to those in previous studies, with the exception of the LI. The modified LI and the average daily risk range (ADRR) showed higher concordance with other glycemic lability indexes than did the LI or mean amplitude of glycemic excursions (MAGE). The results showed that the hypoglycemic indexes in this study population were lower than the results from Ryan et al. Furthermore, the ADRR or modified LI were better measures for high risk of severe lability than were the LI and MAGE.Key words: Glycemic lability, Type 1 diabetes mellitus, Hypoglycemia center comparison as well as to establish standards for pancreas or islet transplantation [7]. Several indexes have been proposed for glycemic lability and hypoglycemia. The most familiar assessment of glycemic lability is the standard deviation (SD) of the glucose profile [8]. However, the SD has limited capacity to identify the extremes of hyperglycemia or hypoglycemia and is affected by the mean glucose [9]. The mean amplitude of glycemic excursions (MAGE) and average daily risk range (ADRR) also measure glucose lability in diabetic patients [10,11]. The MAGE using continuous glucose monitoring is a well-known index of glycemic labil...

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Section: Discussioncontrasting

confidence: 48%

Section: Declaration Of Competing Interestscontrasting

confidence: 48%

Section: Declaration Of Competing Interestsmentioning

confidence: 97%

Section: Measurements and Data Analysismentioning

confidence: 99%

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Assessment of glycemic lability and severity of hypoglycemia in Korean patients with type 1 diabetes

et al. 2011

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“…Youths' ADRR scores were calculated using the original formula 8 and analyzed as continuous and categorical variables based on published adult risk categories: low risk, ADRR < 20; moderate risk, ADRR 20-40; and high risk, ADRR > 40. The LBGI and HBGI were also developed by Kovatchev et al 8,12 and use normalized transformations of SMBG values, similar to the ADRR. However, LBGI and HBGI were designed to generate scores that have a near-zero correlation with each other, making them more highly predictive of episodes of hypo-and hyperglycemia, respectively.…”

Section: Methodsmentioning

confidence: 99%

Evaluation of the Average Daily Risk Range as a Measure of Glycemic Variability in Youths with Type 1 Diabetes

PattonSusana

DeLurgioStephen

Clements

2015

Diabetes Technology & Therapeutics

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Objective: The Average Daily Risk Range (ADRR) is a measure of glycemic variability (GV) developed for adults with diabetes. Although the ADRR is increasingly being reported in pediatric diabetes research and may also be used in clinical management, it has never been examined for its sensitivity to predicting hyper-and hypoglycemia in youths or compared for its predictive ability with other measures of GV in youths. Thus, we present predictive validity data for the ADRR in youths with type 1 diabetes. Materials and Methods: Glucometer data for 436 youths (mean age, 11.8 -3.8 years) were collected from a clinical database. Using these data, we computed the ADRR, SD of blood glucose, coefficient of variation of blood glucose, Low Blood Glucose Index, High Blood Glucose Index, the percentage of glucose values ‡70 and £180 mg/dL, the percentage of high glucose values >180 mg/dL and >400 mg/dL, and the percentage of low glucose values <70 mg/dL and <40 mg/dL in Month 1. We then compared these with episodes of hypo-and hyperglycemia in Month 2. Results: The ADRR showed good concurrent validity with other measures of GV in youths experiencing hyperglycemic events but limited predictive validity in general and specifically with future hypoglycemic events. The percentages of current hyper-and hypoglycemic episodes appeared to be stronger predictors of future hyperand hypoglycemic episodes, respectively. Conclusions: In a large pediatric sample, the ADRR was not the strongest predictor of future glycemic excursion. The percentages of current hyper-and hypoglycemic episodes appear to be stronger predictors.

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A Probabilistic Model for Predicting Hypoglycemia in Type 2 Diabetes Mellitus

Murata¹,

Hoffman²,

Shah³

et al. 2004

Arch Intern Med

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Assessment of risk for severe hypoglycemia among adults with IDDM: validation of the low blood glucose index.

Cited by 280 publications

References 0 publications

Assessment of glycemic lability and severity of hypoglycemia in Korean patients with type 1 diabetes

Assessment of glycemic lability and severity of hypoglycemia in Korean patients with type 1 diabetes

Evaluation of the Average Daily Risk Range as a Measure of Glycemic Variability in Youths with Type 1 Diabetes

A Probabilistic Model for Predicting Hypoglycemia in Type 2 Diabetes Mellitus

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