Standardized hospital management of pediatric diabetic ketoacidosis reduces frequency of low blood glucose episodes.

OBJECTIVE: In patients treated for DKA, decrease the rate of visits experiencing one or more BG < 80 mg/dl by 10% within 24 months. RESEARCH DESIGN AND METHODS: Plan-do-study-act cycles tested interventions linked to key drivers including: standardized DKA guidelines incorporating a two-bag fluid system, efficient ordering process, and care team education. Inclusion criterion: treatment for DKA with a bicarbonate value (HCO3 ) <15 mEq/L. PRIMARY OUTCOME: the percent of patient visits experiencing a BG < 80 mg/dl while undergoing treatment for DKA. Process measures included: order panel and order set utilization rates. Balancing measures included: emergency department and hospital lengths of stay, time to acidosis resolution (time to HCO3 ≥ 17 mEq/L), and admission rates. Outcomes were analyzed using statistical process control charts. RESULTS: From January 2017 through May 2021, our institution treated 288 different patients during 557 visits for suspected DKA. Following our interventions, the overall percent of patient visits for DKA with a BG < 80 mg/dl improved from 32% to 5%. The team did see small improvements in emergency department and hospital lengths of stay; otherwise, there was no significant change in our balancing measures. CONCLUSIONS: Use of quality improvement methodology and standardized DKA management resulted in a significant reduction of BG < 80 mg/dl in patients treated for DKA.

Measurement properties of Patient Reported Outcomes Measurement Information System domains for children with type 1 diabetes.

OBJECTIVE: Patient Reported Outcomes Measurement Information System (PROMIS) includes numerous domains to assess functioning among the pediatric population. These domains, however, have not been evaluated for use in children with type 1 diabetes (T1D). The objective of this study was to determine the measurement properties of PROMIS domains (pain behavior, pain quality, physical stress experience, physical activity, strength impact, and profile-25) in children with T1D. METHODS: This is a cross-sectional study of children with T1Drecruited from tertiary care facilities. To determine construct validity, we compared PROMIS T-scores between known-groups based on (a) glycemic control, hemoglobin A1c (HbA1c%) and (b) self-reported general health, using t test or analysis of variance. Reliability was determined using Cronbach's alpha and item response theory reliability. We also determined agreement between parent-proxy and child self-report PROMIS scores. RESULTS: Our study included 192 children, mean age 12.7 (SD = 2.9) years, eligible to self-report PROMIS surveys. There were significant differences in physical stress experience and pain intensity between children with HbA1c < 10% and those with HbA1c ≥ 10%. There also were significant differences in T-scores for all domains except physical function mobility and strength impact among children with poor/fair, good, very good/excellent general health. All valid domains had reliability >0.70. More than 40% of child-parent pairs were in agreement, with intraclass correlations coefficients (ICC) ranging between 0.41 and 0.63 for all domains, except pain behavior (%agreement = 23%; ICC = 0.29). CONCLUSIONS: Most of the PROMIS domains tested are valid, reliable, and able to differentiate children with T1D who report different general health states. There is moderate agreement between child-parent pairs for all domains except pain behavior.

Clinical associations of quarterly Patient Health Questionnaire-9 depression screening results in adolescents with type 1 diabetes.

BACKGROUND: Awareness of comorbid depression in type 1 diabetes (T1D) patients is necessary to optimize health and diabetes care. Depression can occur or recur requiring regular review for depression symptoms. A validated tool to screen adolescents for symptoms of depression is the Patient Health Questionnaire (PHQ)-9 Modified for Teens (PHQ91-9 ). METHODS: PHQ91-9 depression screen results, depression-related ICD-codes, demographic data, and information on complications and comorbidities of adolescents ≥11 years old with T1D were obtained. Longitudinal and single observation multivariable analyses identified associations of covariates with positive PHQ91-9 depression screens. RESULTS: 5032 PHQ91-9 surveys were completed by 1225 unique participants. Overall, 6% (286/5032) of the PHQ91-9 depression screens were positive, and 60% (171/286) of the positive screens occurred in 107 unique patients without documented depression. In the longitudinal analysis, positive PHQ91-9 screens were associated (P < .05) with a diagnosis of depression listed in the medical record (OR 9.8), diabetic retinopathy (OR 4.3), female sex (OR 1.9), and use of an insulin pump (OR 0.5), while the single observation analysis at the time of a positive PHQ91-9 indicated presence of depression in the medical record (odds ratio 12.1), female sex (OR 1.9), and obesity (OR 1.8) were significantly (P < .05) associated with positive PHQ91-9 results. CONCLUSION: Quarterly PHQ91-9 depression screening of adolescents with T1D during routine clinic visits can immediately inform care, and previous diagnosis of depression is the most strongly associated covariate, highlighting the importance of documenting depression in the medical record. Additionally, awareness for higher odds of positive PHQ91-9 depression screens in females, obese adolescent, and patients on insulin injections is important.

Impact of family-centered tailoring of pediatric diabetes self-management resources.

BACKGROUND: The American Diabetes Association recommends a family-centered approach that addresses each family's specific type 1 diabetes self-management barriers. OBJECTIVE: To assess an intervention that tailored delivery of self-management resources to families' specific self-management barriers. SUBJECTS: At two sites, 214 children 8-16 years old with type 1 diabetes and their parent(s) were randomized to receive tailored self-management resources (intervention, n = 106) or usual care (n = 108). METHODS: Our intervention (1) identified families' self-management barriers with a validated survey, (2) tailored self-management resources to identified barriers, and (3) delivered the resources as four group sessions coordinated with diabetes visits. Mixed effects models with repeated measures were fit to A1c as well as parent and child QOL during the intervention and 1 year thereafter. RESULTS: Participants were 44% youth (8-12 years) and 56% teens (13-16 years). No intervention effect on A1c or QOL was shown, combining data from sites and age groups. Analyzing results by site and age group, post-intervention A1c for teens at one site declined by 0.06 more per month for intervention teens compared to usual care (P < 0.05). In this group, post-intervention A1c declined significantly when baseline A1c was >8.5 (-0.08, P < 0.05), with an even larger decline when baseline A1c was >10 (-0.19, P < 0.05). In addition, for these teens, the significant improvements in A1c resulted from addressing barriers related to motivation to self-manage. Also at this site, mean QOL increased by 0.61 points per month more during the intervention for parents of intervention youth than for usual care youth (P < 0.05). CONCLUSIONS: Tailored self-management resources may improve outcomes among specific populations, suggesting the need to consider families' self-management barriers and patient characteristics before implementing self-management resources.

Continuous glucose monitoring and intensive treatment of type 1 diabetes.

BACKGROUND: The value of continuous glucose monitoring in the management of type 1 diabetes mellitus has not been determined. METHODS: In a multicenter clinical trial, we randomly assigned 322 adults and children who were already receiving intensive therapy for type 1 diabetes to a group with continuous glucose monitoring or to a control group performing home monitoring with a blood glucose meter. All the patients were stratified into three groups according to age and had a glycated hemoglobin level of 7.0 to 10.0%. The primary outcome was the change in the glycated hemoglobin level at 26 weeks. RESULTS: The changes in glycated hemoglobin levels in the two study groups varied markedly according to age group (P=0.003), with a significant difference among patients 25 years of age or older that favored the continuous-monitoring group (mean difference in change, -0.53%; 95% confidence interval [CI], -0.71 to -0.35; P<0.001). The between-group difference was not significant among those who were 15 to 24 years of age (mean difference, 0.08; 95% CI, -0.17 to 0.33; P=0.52) or among those who were 8 to 14 years of age (mean difference, -0.13; 95% CI, -0.38 to 0.11; P=0.29). Secondary glycated hemoglobin outcomes were better in the continuous-monitoring group than in the control group among the oldest and youngest patients but not among those who were 15 to 24 years of age. The use of continuous glucose monitoring averaged 6.0 or more days per week for 83% of patients 25 years of age or older, 30% of those 15 to 24 years of age, and 50% of those 8 to 14 years of age. The rate of severe hypoglycemia was low and did not differ between the two study groups; however, the trial was not powered to detect such a difference. CONCLUSIONS: Continuous glucose monitoring can be associated with improved glycemic control in adults with type 1 diabetes. Further work is needed to identify barriers to effectiveness of continuous monitoring in children and adolescents. (ClinicalTrials.gov number, NCT00406133.)

Preventing post-exercise nocturnal hypoglycemia in children with type 1 diabetes.

OBJECTIVE: To determine the effects of reducing overnight basal insulin or a bedtime dose of terbutaline on nocturnal blood glucose (BG) nadir and hypoglycemia after exercise in children with type 1 diabetes mellitus. STUDY DESIGN: Sixteen youth (mean age 13.3 years) on insulin pumps were studied overnight on 3 occasions after a 60-minute exercise session with BG measurements every 30 minutes. Admissions were randomized to bedtime treatment with oral terbutaline 2.5 mg, 20% basal rate insulin reduction for 6 hours, or no treatment. RESULTS: Mean overnight nadir BG was 188 mg/dL after terbutaline and 172 mg/dL with basal rate reduction compared with 127 mg/dL on the control night (P = .002 and .042, respectively). Terbutaline eliminated nocturnal hypoglycemia but resulted in significantly more hyperglycemia (≥250 mg/dL) when compared with the control visit (P < .0001). The basal rate reduction resulted in fewer BG readings <80 and <70 mg/dL but more readings ≥250 mg/dL when compared with the control visit. CONCLUSIONS: A basal insulin rate reduction was safe and effective in raising post-exercise nocturnal BG nadir and in reducing hypoglycemia in children with type 1 diabetes mellitus. Although effective at preventing hypoglycemia, a 2.5-mg dose of terbutaline was associated with hyperglycemia.

Continuous glucose monitoring in youth with type 1 diabetes.

Continuous glucose monitoring (CGM) is becoming increasingly popular and represents the third era of diabetes management. Currently available CGM devices have been studied in youth with type 1 diabetes and show similar accuracy across all age groups. Tolerability of these devices relates to alarm settings, sensor skin irritation, and durability of the device. Youth will be most successful on a CGM regimen if they have a personal investment in wearing the CGM device and have a stable support system for their diabetes care. Data indicate that glycemic control improves the most in youth who wear CGM devices >or=5 days per week, allowing for the ability to make more insulin dose changes. CGM has proven useful in alerting youth to hypoglycemia and may be a valuable tool with exercise. Further studies are needed to assess the utility of CGM for prevention of severe hypoglycemic events and increasing time spent in euglycemia. Fear of hypoglycemia may be ameliorated with CGM use; however, the potential for increased stress in families with continuous feedback must also be considered. In the future, CGM use in youth may couple with insulin pump technology to create a "closed-loop" system in which the CGM device will direct insulin administration without user input.

Prolonged use of continuous glucose monitors in children with type 1 diabetes on continuous subcutaneous insulin infusion or intensive multiple-daily injection therapy.

OBJECTIVE: For continuous glucose sensors to improve the treatment of children with type 1 diabetes (T1D), they must be accurate, comfortable to wear, and easy to use. We conducted a pilot study of the FreeStyle Navigator Continuous Glucose Monitoring System (Abbott Diabetes Care) to examine the feasibility of daily use of a continuous glucose monitor (CGM) in an extended ambulatory setting. METHODS: Following a 13-wk trial of daily Navigator use, 45 children with T1D [10.7 +/- 3.7 yr, range 4.6-17.6, 24 using insulin pumps; continuous subcutaneous insulin infusion (CSII) and 21 using glargine-based multiple daily injections (MDI)] used the Navigator for an additional 13 wk. RESULTS: Navigator use was initially slightly higher in the CSII users than in the MDI users but declined similarly in both groups by 22-26 wk. After 26 wk, 11 (46%) of 24 CSII users and 7 (33%) of 21 MDI users were using the CGM at least 5 d a week. No baseline demographic or clinical factors were predictive of the amount of sensor use at 26 wk. However, Navigator use during weeks 1-13 and scores on a CGM satisfaction survey at 13 wk were predictive of use in weeks 22-26. CONCLUSIONS: CGM was generally well-tolerated in children with T1D for more than 6 months, and early acceptance of CGM was predictive of extended use of the device. Although many subjects and parents found CGM valuable, the declining usage over time underscores the need to develop new technologies and strategies to increase acceptance, effectiveness, and long-term use of these devices in youth with T1D.

Use of the DirecNet Applied Treatment Algorithm (DATA) for diabetes management with a real-time continuous glucose monitor (the FreeStyle Navigator).

BACKGROUND: There are no published guidelines for use of real-time continuous glucose monitoring data by a patient; we therefore developed the DirecNet Applied Treatment Algorithm (DATA). The DATA provides algorithms for making diabetes management decisions using glucose values: (i) in real time which include the direction and rate of change of glucose levels, and (ii) retrospectively based on downloaded sensor data. OBJECTIVE: To evaluate the use and effectiveness of the DATA in children with diabetes using a real-time continuous glucose sensor (the FreeStyle Navigator). SUBJECTS: Thirty children and adolescents (mean +/- standard deviation age = 11.2 +/- 4.1 yr) receiving insulin pump therapy. METHODS: Subjects were instructed on use of the DATA and were asked to download their Navigator weekly to review glucose patterns. An Algorithm Satisfaction Questionnaire was completed at 3, 7, and 13 wk. RESULTS: At 13 wk, all of the subjects and all but one parent thought that the DATA gave good, clear directions for insulin dosing, and thought the guidelines improved their postprandial glucose levels. In responding to alarms, 86% of patients used the DATA at least 50% of the time at 3 wk, and 59% reported doing so at 13 wk. Similar results were seen in using the DATA to adjust premeal bolus doses of insulin. CONCLUSIONS: These results show the feasibility of implementing the DATA when real-time continuous glucose monitoring is initiated and support its use in future clinical trials of real-time continuous glucose monitoring.

Continuous glucose monitoring in children with type 1 diabetes.

OBJECTIVE: To examine the feasibility of daily use of a continuous glucose monitor, the FreeStyle Navigator Continuous Glucose Monitoring System ("Navigator"), in children with type 1 diabetes (T1D). STUDY DESIGN: After a masked Navigator was used for 4 to 7 days to establish a baseline level of glycemic control, 30 insulin pump users with T1D (average age 11.2 years) were asked to use the Navigator daily for 13 weeks. RESULTS: Subjects averaged 149 h/wk of Navigator use during the first 4 weeks, which decreased slightly to 134 h/wk during weeks 9 to 13 (P = .006). Mean hemoglobin A1c improved from 7.1% at baseline to 6.8% at 13 weeks (P = .02), and the percentage of glucose values between 71 and 180 mg/dL increased from 52% to 60% (P = .01). Subjects and parents reported high satisfaction with the Navigator on the Continuous Glucose Monitor Satisfaction Scale. Two subjects had severe skin reactions related to sensor mount adhesive. CONCLUSION: This study indicates that incorporating real-time continuous glucose monitoring into the daily treatment of children with T1D is feasible. The results provide a compelling rationale for conducting a randomized trial of daily use of a continuous glucose monitor in children with T1D.

Prevention of hypoglycemia during exercise in children with type 1 diabetes by suspending basal insulin.

OBJECTIVE: Strategies for preventing hypoglycemia during exercise in children with type 1 diabetes have not been well studied. The Diabetes Research in Children Network (DirecNet) Study Group conducted a study to determine whether stopping basal insulin could reduce the frequency of hypoglycemia occurring during exercise. RESEARCH DESIGN AND METHODS: Using a randomized crossover design, 49 children 8-17 years of age with type 1 diabetes on insulin pump therapy were studied during structured exercise sessions on 2 days. On day 1, basal insulin was stopped during exercise, and on day 2 it was continued. Each exercise session, performed from approximately 4:00-5:00 p.m., consisted of four 15-min treadmill cycles at a target heart rate of 140 bpm (interspersed with three 5-min rest breaks over 75 min), followed by a 45-min observation period. Frequently sampled glucose concentrations (measured in the DirecNet Central Laboratory) were measured before, during, and after the exercise. RESULTS: Hypoglycemia (< or = 70 mg/dl) during exercise occurred less frequently when the basal insulin was discontinued than when it was continued (16 vs. 43%; P = 0.003). Hyperglycemia (increase from baseline of > or = 20% to > or = 200 mg/dl) 45 min after the completion of exercise was more frequent without basal insulin (27 vs. 4%; P = 0.002). There were no cases of abnormal blood ketone levels. CONCLUSIONS: Discontinuing basal insulin during exercise is an effective strategy for reducing hypoglycemia in children with type 1 diabetes, but the risk of hyperglycemia is increased.

The use of insulin pumps with meal bolus alarms in children with type 1 diabetes to improve glycemic control.

OBJECTIVE: The aim of this study was to determine whether the use of meal bolus alarms would result in fewer missed meal boluses per week in youth with type 1 diabetes using continuous subcutaneous insulin infusion (CSII) therapy. RESEARCH DESIGN AND METHODS: This was a randomized trial of 48 youth using CSII, who were in suboptimal glycemic control with HbA(1c) (A1C) values > or =8.0%. Twenty-four subjects were randomized to use a Deltec Cozmo insulin pump with meal bolus alarms (experimental group), while the other 24 subjects continued use of their current insulin pumps (control group) without meal bolus alarms. RESULTS: After 3 months of study, the number of missed meal boluses per week was significantly lower in the experimental group (from 4.9 +/- 3.7 to 2.5 +/- 2.5; P = 0.0005) but not significantly lower in the control group (from 4.3 +/- 2.7 to 4.2 +/- 3.9; P = 0.7610). Also after 3 months, the mean A1C value of the experimental group declined significantly (from 9.32 +/- 1.12 to 8.86 +/- 1.10; P = 0.0430). No significant decline in A1C was present for the control group (from 8.93 +/- 1.04 to 8.67 +/- 1.17; P = 0.1940). After 6 months of study, the significant decline in A1C from baseline in the experimental group was no longer present. Pooling of all available data from the control and experimental groups showed that at baseline and 3 and 6 months, the number of missed meal boluses per week was significantly correlated with A1C values. CONCLUSIONS: While meal bolus alarms may have the potential to improve suboptimal glycemic control in youth using CSII, our results demonstrated that these alarms had only a transient, modest effect in doing so.

Design and baseline data from a PCORI-funded randomized controlled trial of family-centered tailoring of diabetes self-management resources.

This article describes the methodology, recruitment, participant characteristics, and sustained, intensive stakeholder engagement for Project ACE (Achieving control, Connecting resources, Empowering families). Project ACE is a randomized controlled trial of children and youth ages 8-16 with type 1 diabetes evaluating the impact of tailored self-management resources on hemoglobin A1c (A1c) and quality of life (QOL). Despite strong evidence that controlling A1c reduces long-term complications, <25% of US youth with type 1 diabetes meet A1c targets. Many interventions are efficacious in improving A1c and QOL for these youth, whose families often struggle with the substantial demands of the treatment regimen. However, most such interventions are ineffective in the real world due to lack of uptake by families and limited healthcare system resources. Project ACE is a multi-site trial designed to improve diabetes outcomes by tailoring existing, evidence-based interventions to meet families' needs and preferences. We hypothesize that this family-centered approach will result in better A1c and QOL than usual care. Project ACE has recruited and randomized 214 eligible 8-16year old youth and their parents. The 9-month intervention consisted of 4 group sessions tailored to families' self-management barriers as identified by a validated instrument. Outcomes including A1c and QOL for parents and youth will be assessed for 1year after the intervention. Stakeholder engagement was used to enhance this trial's recruitment, retention and integration into routine clinical care. Findings will inform implementation and dissemination of family-centered approaches to address self-management barriers. TRIAL REGISTRATION NUMBER: NCT02024750 Trial Registrar: Clinicaltrials.gov, https://clinicaltrials.gov/ct2/show/NCT02024750.

Evaluation of factors affecting CGMS calibration.

BACKGROUND: The optimal number/timing of calibrations entered into the CGMS (Medtronic MiniMed, Northridge, CA) continuous glucose monitoring system have not been previously described. METHODS: Fifty subjects with Type 1 diabetes mellitus (10-18 years old) were hospitalized in a clinical research center for approximately 24 h on two separate days. CGMS and OneTouch Ultra meter (LifeScan, Milpitas, CA) data were obtained. The CGMS was retrospectively recalibrated using the Ultra data varying the number and timing of calibrations. Resulting CGMS values were compared against laboratory reference values. RESULTS: There was a modest improvement in accuracy with increasing number of calibrations. The median relative absolute deviation (RAD) was 14%, 15%, 13%, and 13% when using three, four, five, and seven calibration values, respectively (P < 0.001). Corresponding percentages of CGMS-reference pairs meeting the International Organisation for Standardisation criteria were 66%, 67%, 71%, and 72% (P < 0.001). Nighttime accuracy improved when daytime calibrations (pre-lunch and pre-dinner) were removed leaving only two calibrations at 9 p.m. and 6 a.m. (median difference, -2 vs. -9 mg/dL, P < 0.001; median RAD, 12% vs. 15%, P = 0.001). Accuracy was better on visits where the average absolute rate of glucose change at the times of calibration was lower. On visits with average absolute rates <0.5, 0.5 to <1.0, 1.0 to <1.5, and >or=1.5 mg/dL/min, median RAD values were 13% versus 14% versus 17% versus 19%, respectively (P = 0.05). CONCLUSIONS: Although accuracy is slightly improved with more calibrations, the timing of the calibrations appears more important. Modifying the algorithm to put less weight on daytime calibrations for nighttime values and calibrating during times of relative glucose stability may have greater impact on accuracy.

Secondary attack rate of type 1 diabetes in Colorado families.

OBJECTIVE: Families of children diagnosed with type 1 diabetes require counseling concerning type 1 diabetes risk in nondiabetic siblings and parents. No U.S. population-specific life-table risk estimates are currently available for parents, and those for siblings (2-6% by age 20 years) are based on family studies completed before 1987. RESEARCH DESIGN AND METHODS: We analyzed family histories of 1,586 patients in Colorado with type 1 diabetes (83% non-Hispanic white, 10% Hispanic, and 7% other) diagnosed before 16 years of age and interviewed during 1999-2002. Families of probands with type 2, undetermined, or secondary diabetes (n = 53) or those with incomplete data (n = 137) were excluded. The median age at onset of the proband was 7.1 years and the median diabetes duration 3.5 years. Cumulative risk estimates were calculated using survival analysis for 2,081 full siblings and 3,016 biological parents. RESULTS: In siblings, the overall risk of type 1 diabetes by age 20 years was 4.4%, but it was significantly (P < 0.0001) higher in siblings of probands diagnosed under age 7 years than in those diagnosed later. In parents, the overall risk by age 40 years was 2.6% and higher in fathers (3.6%) than in mothers (1.7%) of probands (P < 0.001). Similar to siblings, the risk was also higher (P = 0.006) in parents of probands diagnosed <7 years of age than in those diagnosed later. CONCLUSIONS: Current risks of type 1 diabetes in Colorado siblings and parents of type 1 diabetic probands are higher than in the 1982 Pittsburgh study but similar to contemporary European rates. Recurrence risk of type 1 diabetes is significantly higher in first-degree relatives of probands diagnosed at a young age.

Eight-point glucose testing versus the continuous glucose monitoring system in evaluation of glycemic control in type 1 diabetes.

CONTEXT: Advantages/disadvantages of continuous vs. discrete glucose monitoring are not well documented. OBJECTIVE: Compare glucose profiles from home meters vs. continuous sensors. DESIGN: Randomized clinical trial conducted by the Diabetes Research in Children Network (DirecNet) to assess the utility of the GlucoWatch G2 Biographer. SETTING: Home glucose measurements. PATIENTS: Two hundred children (age, 7 to < 18 yr) with type 1 diabetes. INTERVENTION: At baseline, subjects were asked to wear the continuous glucose monitoring system (CGMS) sensor and perform meter tests at eight prespecified times of the day (eight-point testing) each for 3 d (2 d using both, 1 d eight-point testing only, 1 d CGMS only). Hemoglobin A1c was measured in a central laboratory. MAIN OUTCOME MEASURE: Six-month hemoglobin A1c. This analysis looked at baseline glucose profiles/hemoglobin A1c. RESULTS: Only 10% of subjects completed full eight-point testing for 3 d, but median CGMS use was 70 h. Mean glucose was lower when measured by the CGMS compared with eight-point testing (183 +/- 37 vs. 188 +/- 41 mg/dl; 10.2 +/- 2.1 vs.10.4 +/- 2.3 mmol/liter; P = 0.009), especially overnight (2400-0400 h; 174 vs. 199 mg/dl; 9.7 vs. 11.1 mmol/liter; P < 0.001). Associations of hemoglobin A1c with mean glucose were similar for eight-point testing [slope 23 mg/dl per 1% (1.3 mmol/liter); correlation 0.40; P < 0.001] and CGMS [slope 19 mg/dl per 1% (1.1 mmol/liter); correlation 0.39; P < 0.001]. Postprandial excursions were lower for eight-point testing vs. CGMS, especially after dinner (mean excursion -17 vs. 63 mg/dl; -1.0 vs. 3.5 mmol/liter; P < 0.001). CONCLUSIONS: Both methods gave similar mean glucose profiles and associations with hemoglobin A1c. Advantages of the CGMS were higher density of data and better detection of postprandial peaks. However, the CGMS may overestimate the frequency of low glucose levels, especially overnight.

Accuracy of the modified Continuous Glucose Monitoring System (CGMS) sensor in an outpatient setting: results from a diabetes research in children network (DirecNet) study.

OBJECTIVE: We previously reported the results of an inpatient accuracy study in children with type 1 diabetes using the Continuous Glucose Monitoring System (CGMS, Medtronic MiniMed, Northridge, CA). During the course of that study, a new process was implemented for manufacturing the CGMS sensor. Accuracy from the resulting modified sensor used by only 14 children was significantly better than the original version [median relative absolute difference (RAD), 11% vs. 19%; P < 0.001]. Baseline data from a subsequent outpatient study provide an opportunity to further assess the accuracy of the modified sensor in a much larger sample of children with type 1 diabetes. RESEARCH DESIGN AND METHODS: As part of a randomized trial to assess the utility of the GlucoWatch G2 Biographer (Cygnus, Inc., Redwood City, CA), 200 children with type 1 diabetes were instructed to wear a CGMS for 48-72 h in an outpatient setting at baseline. Glucose measurements from a OneTouch UltraSmart (Lifescan, Inc., Milpitas, CA) home glucose meter were downloaded and used as reference values to calculate accuracy measures. RESULTS: The overall median RAD was 12%. Accuracy was better during hyperglycemia than during hypoglycemia (median RAD, 10% vs. 20%; P < 0.001) and on optimal versus non-optimal days but did not vary significantly by the number of calibrations entered. CONCLUSIONS: These data confirm the improved accuracy previously reported for the modified version of the CGMS sensor.

GlucoWatch G2 Biographer alarm reliability during hypoglycemia in children.

BACKGROUND: The GlucoWatch G2 Biographer (GW2B) (Cygnus, Inc., Redwood City, CA) provides near-continuous monitoring of glucose values in near real time. This device is equipped with two types of alarms to detect hypoglycemia. The hypoglycemia alarm is triggered when the current glucose measurement falls below the level set by the user. The "down alert" alarm is triggered when extrapolation of the current glucose trend anticipates hypoglycemia to occur within the next 20 min. METHODS: We used data from an inpatient accuracy study to assess the performance of these alarms. During a 24-h clinical research center stay, 89 children and adolescents with Type 1 diabetes mellitus (3.5-17.7 years old) wore 174 GW2B devices and had frequent serum glucose determinations during the day and night. RESULTS: Sensitivity to detect hypoglycemia (reference glucose < or = 60 mg/dL) during an insulin-induced hypoglycemia test was 24% with the hypoglycemia alarm alone and 88% when combined with the down alert alarm. Overnight sensitivity from 11 p.m. to 6 a.m. was 23% with the hypoglycemia alarm alone and 77% when combined with the down alert alarm. For 16% of hypoglycemia alarms, the reference glucose was above 70 mg/dL for 30 min before and after the time of the alarm. For the two alarm types combined, the corresponding false-positive rate increased to 62%. CONCLUSIONS: The down alert alarm substantially improves the sensitivity of the GW2B to detect hypoglycemia at the price of a large increase in the false alarm rate. The utility of these alarms in the day-to-day management of children with diabetes remains to be determined.

Optimal sampling intervals to assess long-term glycemic control using continuous glucose monitoring.

AIMS AND HYPOTHESIS: The optimal duration and frequency of short-term continuous glucose monitoring (CGM) to reflect long-term glycemia have not been determined. The Juvenile Diabetes Research Foundation CGM randomized trials provided a large dataset of longitudinal CGM data for this type of analysis. METHODS: The analysis included 185 subjects who had 334 3-month intervals of CGM data meeting specific criteria. For various glucose indices, correlations (r²) were computed for the entire 3-month interval versus selected sampling periods ranging from 3 to 15 days. Other computed agreement measures included median relative absolute difference, values within ± 10% and ± 20% of full value, and median absolute difference. RESULTS: As would be expected, the more days of glucose data that were sampled, the higher the correlation with the full 3 months of data. For 3 days of sampling, the r² value ranged from 0.32 to 0.47, evaluating mean glucose, percentage of values 71-180 mg/dL, percentage of values > 180 mg/dL, percentage of values ≤ 70 mg/dL, and coefficient of variation; in contrast, for 15 days of sampling, the r² values ranged from 0.66 to 0.75. The results were similar when the analysis intervals were stratified by age group (8-14, 15-24, and ≥ 25 years), by baseline hemoglobin A1c level (< 7.0% and ≥ 7.0%), and by CGM device type. CONCLUSIONS AND INTERPRETATION: Our data suggest that a 12-15-day period of monitoring every 3 months may be needed to optimally assess overall glucose control. Shorter periods of sampling can be useful, but the correlation with 3-month measures of glycemic control is lower.

Factors predictive of severe hypoglycemia in type 1 diabetes: analysis from the Juvenile Diabetes Research Foundation continuous glucose monitoring randomized control trial dataset.

OBJECTIVE: Identify factors predictive of severe hypoglycemia (SH) and assess the clinical utility of continuous glucose monitoring (CGM) to warn of impending SH. RESEARCH DESIGN AND METHODS: In a multicenter randomized clinical trial, 436 children and adults with type 1 diabetes were randomized to a treatment group that used CGM (N = 224), or a control group that used standard home blood glucose monitoring (N = 212) and completed 12 months of follow-up. After 6 months, the original control group initiated CGM while the treatment group continued use of CGM for 6 months. Baseline risk factors for SH were evaluated over 12 months of follow-up using proportional hazards regression. CGM-derived indices of hypoglycemia were used to predict episodes of SH over a 24-h time horizon. RESULTS: The SH rate was 17.9 per 100 person-years, and a higher rate was associated with the occurrence of SH in the prior 6 months and female sex. SH frequency increased eightfold when 30% of CGM values were ≤ 70 mg/dL on the prior day (4.5 vs. 0.5%; P < 0.001), but the positive predictive value (PPV) was low (<5%). Results were similar for hypoglycemic area under the curve and the low blood glucose index calculated by CGM. CONCLUSIONS: SH in the 6 months prior to the study was the strongest predictor of SH during the study. CGM-measured hypoglycemia over a 24-h span is highly associated with SH the following day (P < 0.001), but the PPV is low.