Average Daily Risk Range (ADRR) in Young Children With Type 1 Diabetes

Abstract

Objective:

The objective was to examine the utility of the average daily risk range (ADRR) in young children with type 1 diabetes.

Methods:

Self-monitored blood glucose (BG) data and A1c values were collected from 134 children (ages 2-6). Other measures of BG variability and diabetes care were calculated using self-monitored BG data. ADRR, A1c, and other glycemic indices were compared to assess their distinctiveness and utility as measures of BG variability and glycemic control.

Results:

Of young children’s ADRR values, 72% were in the “high-risk” range using adult guidelines. ADRR and A1c were highly correlated with indicators of hyperglycemia but only weakly correlated with measures of hypoglycemia. ADRR was moderately correlated with minimum BG value in the past 30 days but not percentage of BG values below 70 mg/dL. A1c was not correlated with either measure of hypoglycemia.

Conclusions:

ADRR values confirm the high degree of BG variability present in young children with type 1 diabetes, particularly as compared with adults. New ADRR risk guidelines are needed for pediatric patients. ADRR and A1c are adequate indicators of hyperglycemia in young children. However, both ADRR and A1c failed to effectively capture hypoglycemia risk in this sample, and neither ADRR nor A1c can take the place of review of raw BG data to evaluate BG variability in young children.

Hemoglobin A1c (A1c) is widely regarded as the gold standard for evaluating glycemic control in youth with type 1 diabetes.¹ However, A1c represents average glucose levels over the past 6-12 weeks and may not adequately represent the degree of blood glucose (BG) excursions experienced, particularly hypoglycemic episodes.^2,3 Greater frequency of BG excursions, even excursions lasting brief periods of time, is related to increased risk for development of diabetes-related complications.⁴ Thus, standardized evaluation of the risk for BG excursions and BG variability may be a critical component in fine-tuning diabetes treatment regimens.

In response to the need for more sensitive measures to assess BG variability, Kovatchev and colleagues created the average daily risk range (ADRR).⁵ ADRR is calculated using ≥14 days of BG values with a minimum of 3 checks/day and is designed to be equally sensitive to hyperglycemic and hypoglycemic episodes. ADRR has been found to be a valid and reliable measure of glycemic variability in adults and has been shown to prospectively predict both hypoglycemia and hyperglycemia within 4 months of ADRR determination.⁵ In adult samples, ADRR has been positively and statistically significantly associated with A1c and other indices of glycemic variability, including mean amplitude of glycemic excursions and standard deviations of mean BG levels.⁶

ADRR may also be a valuable tool in evaluating BG variability and classifying risk of hypoglycemic and hyperglycemic episodes in young children with type 1 diabetes. Minimizing glycemic variability in young children with type 1 diabetes can be challenging due to greater insulin sensitivity and less insulin resistance than pubertal children, susceptibility to hypoglycemia, highly variable and unpredictable eating and activity schedules, and difficulty communicating symptoms of glycemic excursions to caregivers.^7,8 Thus, identification of reliable and valid measures of glycemic variability in addition to measures of overall glycemic control, such as A1c, may be beneficial for clinicians working with young children with diabetes. However, to date, only 1 study has evaluated the use of ADRR in children. Patton and colleagues compared ADRR values calculated from self-monitored BG data to ADRR values calculated from continuous glucose monitoring (CGM) data in 48 young children with diabetes.⁹ Using self-monitored BG data, 69% of ADRR scores fell in the high risk group (ADRR ≥ 40), indicating a high degree of glycemic variability in the sample. CGM-derived ADRR values were higher than ADRR values from self-monitored BG data, suggesting that CGM captures more frequent glycemic excursions. Using CGM-derived ADRR values, 83% of ADRR scores fell in the high risk group (ADRR ≥ 40). However, as Patton et al⁹ did not compare ADRR to A1c, it is unclear if ADRR values derived from self-monitored BG data or CGM provided added information beyond A1c.

ADRR risk categories may provide additional detail about BG variability and risk of hypoglycemic and hyperglycemic episodes in young children with type 1 diabetes. To date, no studies have compared ADRR to other valid measures of glycemic variability and diabetes care in young children. The current study explores relationships among ADRR, A1c, and indices of glycemic variability to evaluate the utility of A1c and ADRR when estimating risk of BG variability in young children with type 1 diabetes. The current study also compares the distribution of ADRR risk categories in this sample to the original ADRR validation sample of adults with type 1 and type 2 diabetes.⁵

Methods

This investigation evaluated baseline data from a randomized controlled trial (RCT) of a parent-support intervention. The RCT included participants at 3 pediatric diabetes care centers meeting the following criteria: child aged 1-6 years with a diagnosis of type 1 diabetes for ≥6 months, English fluency, and no other major medical or developmental comorbidities. In all, 285 parents were initially mailed recruitment letters for the study; 66 of these parents were unable to be contacted, 16 were ineligible, and 36 declined to participate in the RCT. An additional 33 parents expressed interest in participating but did not complete informed consent. Thus, the final sample for this study included 134 young children with a primary caregiver (66% rate of agreement of reached, eligible participants). The sample was evenly divided by sex (51% male children) and primarily Caucasian (78%). Most children were prescribed basal-bolus insulin regimens (48% multiple daily injections; 24% insulin pump), with the remainder using conventional insulin regimens (28%). See Table 1 for demographic details.

Table 1.

Demographic Characteristics of the Sample (n = 134).

Characteristic	%	Mean	SD	Range
Child age (years)		5.33	1.34	2.01-6.98
Child gender (% female)	49
Ethnicity (% Caucasian)	78
Parent marital status (% married)	84
Household income (% ≥$50,000)	76
Disease duration (years)		2.00	1.24	0.54-5.95
Regimen (% basal-bolus)	72

ADRR was calculated from 30 days of downloaded BG values, with a minimum of 14 days with ≥3 BG checks/day.⁵ All BG data were downloaded as part of routine clinical care to the electronic medical record. If a meter was unable to be downloaded (ie, download dysfunction), 30 days of data were handwritten directly from all available meters by a trained research assistant. ADRR is computed by transforming BG data to a symmetric scale, converting BG measures to excursions and eliminating values within the “normal” range, and averaging the level of daily out-of-range excursions. Adult standards define 3 risk groups: low (ADRR < 20), medium (20 ≤ ADRR < 40), and high (ADRR ≥ 40).⁵ At present, no standards exist for ADRR risk groups in children.

Seven other measures of glycemic variability and diabetes care were calculated from self-monitored BG values (30 days): % hyperglycemic (>200 mg/dL) BG values, % hypoglycemic (<70 mg/dL) BG values, % BG checks in range (70-200 mg/dL), BG maximum value, BG minimum value, 30-day mean BG level, and mean number of BG checks/day. These indices of glycemic variability were selected because they can be easily calculated by clinicians as part of a routine diabetes care visit. Glucose values for hypoglycemia and hyperglycemia were selected based on recommendations of the American Diabetes Association and the original evaluation of ADRR.^5,10 A1c and frequency of adverse medical events related to type 1 diabetes (eg, hospitalizations, seizure, loss of consciousness) were recorded from review of medical charts.

All analyses were conducted using SPSS version 20.0.¹¹ Characteristics of the current sample were compared to the adult validation data set detailed by Kovatchev and colleagues in their seminal article on ADRR (n = 254 type 1 diabetes; n = 81 type 2 diabetes).⁵ Pearson product–moment correlations were computed to evaluate associations between ADRR, A1c, and each of the other indices of glycemic variability and diabetes care, including frequency of adverse medical events.

Results

The distribution of ADRR risk groups in the current sample was compared to the adult validation sample of Kovatchev and colleagues.⁵ The adult validation sample and current sample of young children with type 1 diabetes had similar mean A1cs, 8.1% ± 1.3 and 8.1% ± 0.9, respectively. The mean number of BG checks/day was lower in the adult sample (3.8 ± 2.1) compared to the pediatric sample (5.8 ± 2.2), t(133) = 10.50, P < .01. The distributions of risk groups differed in adults and children, χ²(2) = 122.55, P < .01. In the adult sample, 20%, 52%, and 28% were in the low-, medium-, and high-risk groups, respectively.⁵ Using adult cutoffs, 1.5%, 25.4%, and 73.1% of young children were in the low-, medium-, and high-risk groups, respectively. ADRR values did not significantly differ by insulin regimen (basal-bolus M ADRR = 46.37; conventional M ADRR = 50.14; P = .15).

Evaluation of BG data confirmed that considerable glycemic variability is present in young children with type 1 diabetes. The mean ADRR value was 47.41 (SD = 13.38, range = 8-82). Thus, the average ADRR value in this sample was in the high-risk range per adult standards. The mean BG level observed over a 30-day period was 195.95 mg/dL. Hyperglycemia was common, and participants averaged 42.41% of BG values > 200 mg/dL over a 30-day period. In addition, 9.50% of BG values over a 30-day period were < 70 mg/dL. Thus, in this sample, fewer than 50% of BG values fell within 70-200 mg/dL over a 30-day period. See Table 2 for means, standard deviations, and ranges of all indices of glycemic variability.

Table 2.

Indices of Glycemic Variability and Diabetes Care.

	Mean	SD	Range
HbA1c (%)	8.13	0.88	6.40-11.00
ADRR	47.41	13.38	8-82
30-day mean BG level (mg/dL)	195.95	34.92	115-302
% BG readings > 200 mg/dL	42.41	13.68	8-74
% BG readings < 70 mg/dL	9.50	5.47	0-24
% BG readings 70-200 mg/dL	48.09	13.01	24-91
BG maximum (mg/dL)	493.45	80.53	239-600
BG minimum (mg/dL)	42.99	10.77	21-76
Number of BG checks/day	5.76	2.15	2-11
Adverse medical events	0.33	1.17	0-10

ADRR, average daily risk range; BG, blood glucose.

ADRR and A1c were moderately correlated (r = .45, P < .001). ADRR and A1c were also moderately correlated with indices of glycemic variability and diabetes care. Only ADRR was correlated with minimum BG value (r = –.37, P < .01). Only A1c was correlated with the number of BG checks/day (r = –.29, P < .01), with a higher A1c associated with fewer daily BG checks. See Table 3 for correlations among all measures of glycemic variability.

Table 3.

Pearson’s Correlation Coefficients Between ADRR and A1c and Indicators of Glycemic Variability.

	ADRR	A1c
30-day mean BG level	.77**	.65**
% BG readings > 200 mg/dL	.72**	.68**
% BG readings <70 mg/dL	.12	−.12
% BG 70-200 mg/dL	−.80**	−.65**
BG maximum	.77**	.44**
BG minimum	−.37**	−.04
Number of BG checks/day	.07	−.29**
Adverse medical events	.25**	.18*

ADRR, average daily risk range; BG, blood glucose.

^* P < .05; **P < .01.

Discussion

Given the degree of BG variability among children with type 1 diabetes, comprehensive assessment of glycemic control and related glycemic variability is critical. Although this pediatric sample had similar A1c levels to the adult validation sample,⁵ the mean ADRR was much higher for this group, and consequently a much larger proportion of our young child sample was classified in the “high-risk” range. Findings support the literature indicating that children with type 1 diabetes have greater fluctuations in daily BG levels than adults.¹² Thus, adult risk-group cutoffs may not be appropriate for pediatric patients. Results also suggest that ADRR is useful to evaluate BG variability in young children with type 1 diabetes and may be beneficial to review in addition to A1c when evaluating patients at high risk for poor diabetes control.

ADRR was correlated with measures of glycemic variability and diabetes care. Of note, only ADRR was moderately correlated with hypoglycemia (BG minimum value) but neither ADRR nor A1c demonstrated an association with percentage of hypoglycemic BG values. ADRR may be a more sensitive measure of hypoglycemia than A1c, while also adequately representing risk of hyperglycemia. The measures of glycemic variability were selected because they can be calculated relatively easily by a clinician during a routine clinic visit. The inability of ADRR to more fully reflect hypoglycemia risk suggests that neither ADRR nor A1c can take the place of systematic examination of BG data by health care providers to examine patterns in BG variability across a typical day. This can be accomplished by graphical or tabular review of downloaded BG data from a representative period of time (eg, 30 days). Careful review of BG data especially important for young children at risk for frequent BG excursions and acute complications such as hypoglycemic seizure.¹¹

To date, only 1 other study has evaluated the use of ADRR in young children. Patton and colleagues similarly found a very high percentage of young children with type 1 diabetes fall in the high risk range for ADRR values using either self-monitored BG data or glucose data derived from continuous glucose monitoring.⁹ As it is challenging to eliminate all glycemic excursions in young children, the impact of a relatively high ADRR this population is unknown, and only longitudinal investigation of children with early onset diabetes will contribute to understanding the ramifications of high levels of glycemic variability over time. Similarly, further research to allow for greater distinction between risk categories for young children is clearly warranted. For example, it is possible that ADRR risk cutoff groups should be modified for children to more accurately reflect risk.

This study was limited by a cross-sectional design. A prospective relationship between ADRR and future adverse medical events could not be evaluated. ADRR was calculated from self-monitored BG values. If CGM data were used, young children in the current study would likely have demonstrated an even higher risk for glycemic variability and further diverge from adult samples. A prospective study and inclusion of additional glucose data obtained from CGM compared to A1c may provide further insight into the utility of ADRR among children. The study results are limited by a lack of information about the adult validation sample and the multiple comparisons among ADRR, A1c, and measures of glycemic variability and diabetes care. The information about the adult validation sample was drawn from Kovatchev and colleagues,⁵ and therefore information about the insulin regimen distribution in the adult validation sample is unknown. In addition, corrections for multiple comparisons among variables of interest were not applied in this study. However, this study aimed to emphasize the magnitude of the correlation effects rather than determine if the correlations were statistically significant from zero. Thus, correcting for multiple comparisons would mask correlations that indicate a significant relationship between ADRR or A1c and measures of BG variability and diabetes care. Results inform the strengths and weaknesses of ADRR in a large, representative sample of young children with type 1 diabetes.

Conclusion

ADRR provides more specific feedback on risk for BG excursions than A1c values in young children with type 1 diabetes. However, direct examination of BG data, including the number and severity of hyper- and hypoglycemic events, is still of critical importance to assess patterns of glucose control and fine-tune diabetes care. Further validation of ADRR is needed to determine its predictive utility in youth with type 1 diabetes and appropriate pediatric risk-group cutoffs. In addition, the high degree of glycemic variability observed in this large sample underscores the importance of close monitoring of glucose variability over time in very young children with type 1 diabetes. In its current format, ADRR may best be used in conjunction with A1c as a general marker of the effect of BG variability on glycemic control in young children.