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Eva Tsalikian

Publications and source records attributed to Eva Tsalikian.

12 recordsLinked to original sources

The accuracy of the FreeStyle Navigator continuous glucose monitoring system in children with type 1 diabetes.

OBJECTIVE: To evaluate the accuracy and precision of the FreeStyle Navigator continuous glucose monitoring system in children with type 1 diabetes. RESEARCH DESIGN AND METHODS: In 30 children with type 1 diabetes (mean age 11.2 +/- 4.1 years), the Navigator glucose values were compared with reference serum glucose values of blood samples obtained in an inpatient clinical research center and measured in a central laboratory using a hexokinase enzymatic method and in an outpatient setting with a FreeStyle meter. Median absolute difference (AD) and median relative absolute difference (RAD) were computed for sensor-reference and sensor-sensor pairs. RESULTS: The median AD and RAD were 17 mg/dl and 12%, respectively, for 1,811 inpatient sensor-reference pairs and 20 mg/dl and 14%, respectively, for 8,639 outpatient pairs. The median RAD between two simultaneous Navigator measurements (n = 1,971) was 13%. Ninety-one percent of sensors in the inpatient setting and 81% of sensors in the outpatient setting had a median RAD < or = 20%. CONCLUSIONS: The Navigator's accuracy does not yet approach the accuracy of current-generation home glucose meters, but it is sufficient to believe that the device has the potential to be an important adjunct to treatment of youth with type 1 diabetes.

Adolescent↗

Strategies for salivary cortisol collection and analysis in research with children.

Salivary cortisol has emerged in pediatric research as an easy-to-collect, relatively inexpensive, biologic marker of stress. Cortisol is highly variable and is responsive to a wide range of factors that should be considered when incorporating this measure into research with children. Strategies for sample collection include: (1) standardizing the time for sample collection, including baseline samples; (2) using consistent collection materials and methods; (3) controlling for certain drinks, foods, medications, and diagnoses; and (4) establishing procedures and protocols. Other strategies for laboratory analyses include: (1) selecting the appropriate assay and laboratory; (2) identifying units of measure and norms; and (3) establishing quality controls. These strategies control extraneous variables and produce reliable and valid salivary cortisol results.

Bias↗

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.

Adolescent↗

The effects of aerobic exercise on glucose and counterregulatory hormone concentrations in children with type 1 diabetes.

OBJECTIVE: To examine the acute glucose-lowering effects of aerobic exercise in children and adolescents with type 1 diabetes. RESEARCH DESIGN AND METHODS: Fifty children and adolescents with type 1 diabetes (ages 10 to <18 years) were studied during exercise. The 75-min exercise session consisted of four 15-min periods of walking on a treadmill to a target heart rate of 140 bpm and three 5-min rest periods. Blood glucose and plasma glucagon, cortisol, growth hormone, and norepinephrine concentrations were measured before, during, and after exercise. RESULTS: In most subjects (83%), plasma glucose concentration dropped at least 25% from baseline, and 15 (30%) subjects became hypoglycemic (< or = 60 mg/dl) or were treated for low glucose either during or immediately following the exercise session. The incidence of hypoglycemia and/or treatment for low glucose varied significantly by baseline glucose, occurring in 86 vs. 13 vs. 6% of subjects with baseline values <120, 120-180, and >180 mg/dl, respectively (P < 0.001). Exercise-induced increases in growth hormone and norepinephrine concentrations were marginally higher in subjects whose glucose dropped < or = 70 mg/dl. Treatment of hypoglycemia with 15 g of oral glucose resulted in only about a 20-mg/dl rise in glucose concentrations. CONCLUSIONS: In youth with type 1 diabetes, prolonged moderate aerobic exercise results in a consistent reduction in plasma glucose and the frequent occurrence of hypoglycemia when preexercise glucose concentrations are <120 mg/dl. Moreover, treatment with 15 g of oral glucose is often insufficient to reliably treat hypoglycemia during exercise in these youngsters.

Adolescent↗

Impact of exercise on overnight glycemic control in children with type 1 diabetes mellitus.

OBJECTIVE: To examine the effect of exercise on overnight hypoglycemia in children with type 1 diabetes mellitus (T1DM). STUDY DESIGN: At 5 clinical sites, 50 subjects with T1DM (age 11 to 17 years) were studied in a clinical research center on 2 separate days. One day included an afternoon exercise session on a treadmill. On both days, frequently sampled blood glucose levels were measured at the DirecNet central laboratory. Insulin doses were similar on both days. RESULTS: During exercise, plasma glucose levels fell in almost all subjects; 11 (22%) developed hypoglycemia. Mean glucose level from 10 pm to 6 am was lower on the exercise day than on the sedentary day (131 vs 154 mg/dL; P=.003). Hypoglycemia developed overnight more often on the exercise nights than on the sedentary nights (P=.009), occurring on the exercise night only in 13 (26%), on the sedentary night only in 3 (6%), on both nights in 11 (22%), and on neither night in 23 (46%). Hypoglycemia was unusual on the sedentary night if the pre-bedtime snack glucose level was>130 mg/dL. CONCLUSIONS: These findings indicate that overnight hypoglycemia after exercise is common in children with T1DM and support the importance of modifying diabetes management after afternoon exercise to reduce the risk of hypoglycemia.

Adolescent↗

Comparison of fingerstick hemoglobin A1c levels assayed by DCA 2000 with the DCCT/EDIC central laboratory assay: results of a Diabetes Research in Children Network (DirecNet) Study.

BACKGROUND: The Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) high-performance liquid chromatography (HPLC) method for measuring hemoglobin A1c (HbA1c) serves as a reference standard against which other assays are compared. The DCA 2000 + Analyzer (Bayer Inc., Tarrytown, NY, USA), which uses an immunoassay, is a very popular device for measuring HbA1c levels in pediatric diabetes practices. OBJECTIVE: To determine how HbA1c values measured with the DCA 2000 in a multisite, pediatric diabetes clinic setting compare with corresponding HbA1c values measured in the DCCT/EDIC laboratory. DESIGN/METHODS: To examine this question, the Diabetes Research in Children Network (DirecNet) used the DCA 2000 in five clinical centers to measure baseline HbA1c levels in 200 youth with type 1 diabetes mellitus (T1DM) (aged 12.5 +/- 2.8 yr) who were participating in an outpatient clinical trial. At the same visit, an additional blood sample was obtained, refrigerated, and shipped to the DCCT/EDIC central laboratory for determination of HbA1c values. RESULTS: The central laboratory HbA1c value averaged 8.0 +/- 0.9% (mean +/- SD), with a median (25th and 75th quartiles) of 7.8% (7.3 and 8.5%, respectively). The DCA 2000 HbA1c values were strongly correlated (r = 0.94, p < 0.001), but significantly higher than DCCT/EDIC central laboratory values with a mean difference of +0.2% (95% confidence interval +0.14 to 0.23%, p < 0.001). There was some variation in the differences between DCA 2000 and central laboratory values at the five clinical centers (p < 0.001) with mean differences ranging between 0.0 and 0.3%, but differences between the two methods did not vary significantly by age or gender. CONCLUSION: Measurements of HbA1c by the DCA 2000 compare favorably with the DCCT/EDIC central laboratory method, albeit with slightly higher values.

Adolescent↗

A randomized multicenter trial comparing the GlucoWatch Biographer with standard glucose monitoring in children with type 1 diabetes.

OBJECTIVE: This study assesses whether use of the GlucoWatch G2 Biographer (GW2B) in addition to standard glucose monitoring lowers HbA(1c) and reduces hypoglycemia compared with standard glucose monitoring alone. RESEARCH DESIGN AND METHODS: In all, 200 subjects aged 7 to <18 years with type 1 diabetes were randomly assigned at five centers to standard glucose monitoring (usual care) or standard glucose monitoring plus GW2B use for 6 months. Study outcomes included HbA(1c) values obtained at 6 months and occurrence of severe hypoglycemia. RESULTS: The mean HbA(1c) at baseline was 8.0% in both groups; at 6 months, HbA(1c) was 7.9% in the usual care group and 8.1% in the GW2B group (95% CI for mean reduction in the GW2B group compared with the usual care group -0.4 to 0.1%; P = 0.15). A decrease in HbA(1c) of > or =0.5% was achieved in 21% of the usual care group and 28% of the GW2B group (P = 0.29). Severe hypoglycemia events occurred in 7% of the GW2B group and in 2% of the usual care group (P = 0.10). In the GW2B group, sensor use declined throughout the study from a mean value of 2.1 times/week in the 1st month to 1.5 times/week in the 6th month. Reasons given for declining use included skin irritation (76%), frequent skips (56%), excessive alarms (47%), and inaccurate readings (33%). CONCLUSIONS: Use of the GW2B in addition to standard glucose monitoring did not improve glycemic control or reduce the frequency of severe hypoglycemia. Skin reactions and other problems led to decreasing sensor use over time.

Adolescent↗

Lack of accuracy of continuous glucose sensors in healthy, nondiabetic children: results of the Diabetes Research in Children Network (DirecNet) accuracy study.

OBJECTIVE: The workup of hypoglycemia requires frequent glucose sampling. We designed these studies to determine if the Continuous Glucose Monitoring System (CGMS) and the GlucoWatch G2 Biographer (GW2B) are sufficiently accurate to use in nondiabetic children. Study design Fifteen healthy children (aged 9-17 years, 11 boys) wore a GW2B and a CGMS during a 24-hour period, and reference serum glucose was measured hourly during the day and half-hourly overnight. RESULTS: Compared with the reference glucose, the median absolute difference in concentrations measured by the GW2B (487 pairs) was 13 mg/dL, and the difference measured by the CGMS was 17 mg/dL (668 pairs), with 30% and 42% of values using the GW2B and CGMS, respectively, deviating >20 mg/dL from the reference value. The GW2B reported values <60 mg/dL in 73% of subjects, the CGMS in 60% of subjects. In none of these episodes was serum glucose truly low. Spurious high glucose concentrations also were observed with the sensors. The mean reference glucose was lowest at 5 am (89 mg/dL) and highest at 11:30 pm (106 mg/dL) during the 24-hour period. CONCLUSIONS: Neither the CGMS nor the GW2B is accurate enough to establish population standards of the glycemic profile of healthy children and cannot be recommended in the workup of hypoglycemia in nondiabetic youth.

Adolescent↗

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.

Adolescent↗

Factors associated with academic achievement in children with type 1 diabetes.

OBJECTIVE: To examine academic achievement in children with diabetes and to identify predictors of achievement. RESEARCH DESIGN AND METHODS: Participants were 244 children, ages 8-18 years, with type 1 diabetes. Measures included school-administered standardized achievement tests (Iowa Tests of Basic Skills and Iowa Tests of Educational Development [ITBS/ITED]), grade point averages (GPAs), school absences, behavioral assessment, age at disease onset, hospitalizations, and HbA(1c). Statistical differences between subgroups of children were evaluated using t test and ANOVA, statistically controlling for socioeconomic status. Regression analyses were carried out to examine predictors of academic performance. RESULTS: Reading scores and GPA were lower for children with poor metabolic control than for children with average control. Children with hospitalizations for hyperglycemia had lower overall achievement scores than children with better metabolic control and fewer hospitalizations for hyperglycemia. The small group of children with tight metabolic control and hypoglycemic hospitalizations scored particularly low on the ITBS/ITED. Other variables had less clear relationships with academic achievement. Neither early onset of diabetes nor frequent school absence was associated with lower scores on the ITBS/ITED. Sex comparisons found that boys performed better than girls only in math. Socioeconomic status and parent ratings of behavior problems were significantly correlated with academic achievement, but medical variables added only slightly to predictive precision. CONCLUSIONS: For most children with diabetes, medical variables are not as strongly associated with academic achievement as are factors such as socioeconomic status and behavioral factors. Poor metabolic control and serious hypoglycemia, however, are a potential concern for a subset of these children.

Achievement↗

Effects of diabetes on learning in children.

OBJECTIVE: Subtle neuropsychological deficits have been found in some children with type 1 diabetes. However, these data have been inconsistent, and it is not clear what the impact of these deficits might be on the learning of children with diabetes over time. The purpose of this study was to determine whether type 1 diabetes significantly interferes with the development of functional academic skills. It was hypothesized that 1) children with type 1 diabetes would demonstrate deficits in academic performance and behavior when compared with sibling or classmate control subjects and 2) that academic performance in children with type 1 diabetes would decline slightly but significantly over time whereas the performance of siblings or classmates would not. METHODS: Three groups of children from 5 pediatric diabetes clinics in a primarily rural Midwestern state participated in this study: children with type 1 diabetes (n = 244), a sibling control group (n = 110), and an anonymous matched classmate control group (n = 209). The mean age of the children with diabetes was 14.8 years (standard deviation: 3.2) and of the siblings was 14.6 years (3.2); the mean grades were 8.1 (2.9) for the children with diabetes and 7.9 (3.1) for the siblings. The Hollingshead 2-factor index revealed that the children were from primarily middle- to upper-middle-class families. The mean age of onset of diabetes for the children with diabetes was 8.3 years (3.7) with a mean disease duration of 7.1 years (3.9). Because the matched classmate data were obtained anonymously, demographic information was not available on this group. Academic achievement was measured using both standardized tests and data on classroom performance. The standardized test data included scores from the Iowa Tests of Basic Skills (ITBS) for grades 3 through 8 and the Iowa Tests of Educational Development (ITED) for grades 9 through 12. Scores in 3 broad academic areas that are obtained on children of all ages were examined: math, reading, and core total (a composite score of reading, language, and math). ITBS/ITED data were obtained on all participants. School data including the number of days absent, school years repeated, and grade point averages for math and reading were obtained on the children with diabetes and their siblings. A short, 50-item screening scale (PBS-50d), adapted from the longer 165 item Pediatric Behavior Scale (PBS), was completed by the parents to obtain information on the behavioral characteristics of the children with diabetes and their siblings. Diabetes variables measured included metabolic control (HbA1c), age at onset, and disease duration. This study looked at both the current academic performance of children with diabetes and their performance over time in relation to 2 control groups: siblings and matched classmates. A cross-sectional approach was used to evaluate current performance. Statistical differences between groups were evaluated using matched t tests or McNemar's test for differences between related samples as appropriate. Differences across time were evaluated using hierarchical linear modeling. Comparisons of ITBS/ITED test scores across grades used national percentile ranks that were converted to standard scores (SS) with a mean of 100 and a standard deviation of 15. Students in this study performed above the national average, which is typical of students in the state where this study was conducted. Data from participating clinics were compared, and no differences in current achievement scores, grade point averages, or socioeconomic status were noted for either children with diabetes or their siblings. Therefore, all subsequent analyses used data combined from all sites. RESULTS: Current academic performance on the ITBS/ITED did not show lower performance by children with diabetes compared with either control group; in fact, children with diabetes performed better than their siblings on math (mean SS: 115.0 vs 111.1) and core total scores (mean SS: 113.9 vs 110.5) and better than their matched classmates on reading (mean SS: 108.9 vs 106.8). When subgroup comparisons based on diabetes metabolic control were made among children with diabetes, poorer academic performance tended to occur in children with poorer diabetic control. However, this pattern was also noted in sibling scores when the siblings were grouped on the basis of the level of diabetic control of their brother or sister with diabetes. Children with diabetes had significantly more school absences (Mean = 7.3 per year) than their siblings (M = 5.3) and more behavioral problems. Behaviorally, the 2 groups did not differ on the 4 general factors of Aggression/Opposition, Hyperactivity/Inattention, Depression/Anxiety, and Physical Complaints. However, children with diabetes did differ significantly from their siblings on items that reflected compliance, mood variability, and fatigue, but not learning. These were 4 areas included in the PBS-50d to reflect potential concerns for children with diabetes. Academic achievement growth curves for the ITBS/ITED for each group revealed no statistically significant differences between groups when tested using hierarchical linear modeling. Individual differences in the growth trajectories were too small and inconsistent to be detected. CONCLUSIONS: For most children, type 1 diabetes is not associated with lower academic performance compared with either siblings or classmates, although increased behavioral concerns are reported by parents. The results of this study suggest that the subtle cognitive deficits often documented in children with type 1 diabetes may not significantly limit the functional academic abilities of these children over time. However, careful monitoring is still needed to ensure that episodes of hypoglycemia associated with seizures are not adversely affecting learning.

Adolescent↗