To evaluate glycemia and metrics of glucose variability in youth with type 1 diabetes, and to assess patterns of 24-h glucose variability according to pubertal status.
Metrics of glycemia, glucose ...variability, and glucose patterns were assessed by using 4 weeks of continuous glucose monitoring (CGM) data from 107 youth aged 8-17 years with type 1 diabetes for ≥1 year. Glucose values per hour were expressed as percentages relative to the mean glucose over 24 h for a 4-week period. Glucose data were compared on the basis of pubertal status-prepubertal (Tanner stage T 1), pubertal (T2-4), and postpubertal (T5)-and A1C categories (<7.5% <58 mmol/mol, ≥7.5% ≥58 mmol/mol).
Youth (50% female, 95% white) had a mean ± SD age of 13.1 ± 2.6 years, diabetes duration of 6.3 ± 3.5 years, and A1C of 7.8 ± 0.8% (62 ± 9 mmol/mol); 88% were pump treated. Prepubertal youth had a higher mean glucose SD (86 ± 12 mg/dL 4.8 ± 0.7 mmol/L;
0.01) and coefficient of variation (CV) (43 ± 5%;
0.06) than did pubertal (SD 79 ± 13 mg/dL 4.4 ± 0.7 mmol/L; CV 41 ± 5%) and postpubertal (SD 77 ± 14 mg/dL 4.3 ± 0.8 mmol/L; CV 40 ± 5%) youth. Over 24 h, prepubertal youth had the largest excursions from mean glucose and the highest CV across most hours compared with pubertal and postpubertal youth. Across all youth, CV was strongly correlated with the percentage of time with glucose <70 mg/dL (<3.9 mmol/L) (
= 0.79;
< 0.0001).
Prepubertal youth had greater glucose variability independent of A1C than did pubertal and postpubertal youth. A1C alone does not capture the full range of glycemic parameters, highlighting the added insight of CGM in managing youth with type 1 diabetes.
Aim: Depression is a heterogeneous construct that includes various symptoms (e.g., cognitive, somatic) and is linked to worse diabetes outcomes. We examined the associations of depressive symptom ...clusters with glycemic outcomes using continuous glucose monitoring (CGM) data in youth with T1D.
Methods: Participants (N=120) provided blood samples for HbA1c, completed a validated survey for depressive symptoms (CES-DC) , and wore CGM for one week. CGM glucose metrics were derived: % time in range (TIR) 70-180 mg/dL; % time <70 mg/dL; % time >180 mg/dL; % time >250 mg/dL; mean glucose; and glucose variability (GCV) . CES-DC items were categorized as somatic, cognitive, anhedonic, and interpersonal for analyses.
Results: Youth (49% male) had a mean (±SD) age of 12.7±2.7 years, T1D duration 6.1±3.5 years, HbA1c 7.9±0.8%. Overall, higher total CES-DC score was associated with higher HbA1c (r=0.21, p=0.02) . In youth with HbA1c ≤8% (n=68) , there were no significant associations between depressive clusters and glycemic outcomes, but several significant associations emerged in youth with HbA1c >8% (n=52) . For those with HbA1c >8%, higher CES-DC total score was associated with higher HbA1c (r=0.55, p<0.0001) , greater % time >250 (r=0.29, p=0.03) , and higher mean glucose (r=0.33, p=0.02) . More symptoms on the cognitive and interpersonal clusters were associated with higher HbA1c (r=0.29, p=0.03; r=0.43, p=0.002, respectively) . More somatic symptoms were associated with greater % time >180 (r=0.34, p=0.01) , less % TIR (r=-0.34, p=0.01) , and higher mean glucose (r=0.31, p=0.03) .
Conclusions: In our sample of youth with T1D, associations between depressive symptoms and glucose varied according to overall glycemic control, with notable associations in youth with HbA1c >8%. Somatic depressive symptoms were especially related to uncontrolled glucose levels, highlighting the importance of targeting glucose TIR to reduce adverse physical complaints.
Disclosure
A.Shapira: None. L.K.Volkening: None. L.M.Laffel: Advisory Panel; Medtronic, Roche Diabetes Care, Consultant; Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompé, Insulet Corporation, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk, Provention Bio, Inc.
Funding
T32DK007260, P30DK036836, R01DK089349
Introduction: With increased CGM use in youth with T1D, it is timely to assess diabetes-specific family conflict related to CGM use. We aimed to evaluate the psychometric properties of an updated DFC ...measure that includes CGM items.
Methods: Youth with T1D and their parents completed youth and parent versions, respectively, of the DFC that included 6 CGM-specific items (e.g., responding to CGM alarms) . Higher scores indicate more conflict. Item-to-total correlations and Cronbach’s α assessed internal consistency; correlations determined concurrent and predictive validity.
Results: The sample comprised 1youth (51% male) aged 13.2±2.7 years, with T1D duration 6.6±3.5 years. The final survey had 16 items after removal of those with outdated features, low response variability, or low item-to-total correlation. Cronbach’s α was .91 for youth and .81 for parents. Youth and parent scores were highly correlated (r=.48, p<.0001) . Higher DFC scores were associated with younger youth age (youth: r=-.23, p=.02; parent: r=-.27, p=.004) . Higher youth and parent DFC scores were also associated with adverse psychosocial outcomes: more depressive symptoms (youth: r=.38, p<.0001; parent: r=.35, p=.0002) , more diabetes burden (youth: r=.31, p=.0008; parent: r=.44, p<.0001) , more anxiety traits (youth: r=.23, p=.02; parent: r=.45; p<.0001) , lower youth general quality of life (QoL) (youth: r=-.30, p=.002; parent: r=-.45, p<.0001) and lower youth diabetes-specific QoL (youth: r=-.21, p=.02; parent: r=-.44, p<.0001) . Higher youth and parent DFC scores were associated with lower CGM satisfaction (youth: r=-.36, p<.0001; parent: r=-.28, p=.004) and with less CGM use at the time of DFC scale completion (youth: r=-.33, p=.0004; parent: r=-.31, p=.001) and 3 months later (youth: r=-.19, p=.05; parent: r=-.28, p=.003) .
Conclusion: The updated youth and parent DFC scales demonstrate strong psychometric properties and predictive validity and may be useful in clinical and research settings.
Disclosure
C.Chen: None. A.Shapira: None. L.K.Volkening: None. L.M.Laffel: Advisory Panel; Medtronic, Roche Diabetes Care, Consultant; Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompé, Insulet Corporation, Janssen Pharmaceuticals, Inc., Lilly Diabetes, Novo Nordisk, Provention Bio, Inc.
Funding
National Institutes of Health (P30DK036836, R01DK089349, T32DK007260)
Aim: Providers may resist offering pump therapy to teens with T1D who have challenges with EF (planning, organization) due to concerns for DKA. We evaluated rates of DKA and severe hypoglycemia ...according to pump use in teens with and without EF problems.
Methods: Parents of teens aged 13-17 years with T1D provided proxy reports of teen EF using the Behavior Rating Inventory of Executive Function (BRIEF). Global Executive Composite (GEC) t-score ≥60 defined risk of executive dysfunction. Families reported severe hypoglycemic episodes and ER visits/hospitalizations for hyperglycemia (including DKA) every 3 months for 18 months. Incidence rates (IR) were calculated as events/100 person-years. DKA IR includes ER visits/hospitalizations for either hyperglycemia or DKA. Poisson regressions evaluated differences in IR by pump use, CGM use, and BRIEF score.
Results: 169 teens (54% male) had baseline age 14.9±1.3 years, T1D duration 7.4±3.7 years, A1c 8.5±1.0%; 69% were pump users, 41% used CGM some time during follow-up, and 31% had GEC ≥60. During 297 person-years, severe hypoglycemia IR was 38.3/100 person-years and DKA IR was 7.7/100 person-years. There were no differences in hypoglycemia IR by pump or CGM use or GEC score. There was no difference in DKA IR by CGM use while DKA IR was lower in pump users vs non-users (4.9 vs 14.0, p=.01) and in those with GEC <60 vs ≥60 (4.9 vs 14.0, p=.01). Among those with GEC <60, DKA IR was lower in pump users vs non-users (2.0 vs 13.7, p=.003); in those with GEC ≥60, DKA IR was similar in pump users and non-users (13.7 vs 14.4, p=.94).
Conclusion: In this sample of teens with T1D, hypoglycemia IR did not differ by pump or CGM use or EF status; in the teens with EF challenges, DKA IR was not higher in pump users vs non-users. These observations suggest that hesitation by clinicians to offer insulin pump therapy to teens with clinical suspicion of executive dysfunction due to concerns for increased DKA risk may not be warranted.
Disclosure
R.J.Vitale: None. L.K.Volkening: None. L.M.Laffel: Advisory Panel; Medtronic, Lilly Diabetes, Novo Nordisk, Vertex Pharmaceuticals Incorporated, Roche Diagnostics, Provention Bio, Inc., Consultant; Dexcom, Inc., Janssen Pharmaceuticals, Inc., Medscape.
Funding
National Institutes of Health (P30DK036836, R01DK095273); JDRF (2-SRA-2014-253-M-B); Iacocca Family Foundation
Aim: Many adolescents and young adults (AYAs) with T1D express a desire to meet others with T1D. We designed a pilot peer support program (DiaBuddies) and assessed feasibility of the match process ...and program implementation.
Methods: Eligible participants (13-25 years old) were recruited and enrolled virtually. After informed consent, participants completed questions about preferred match type (peer vs mentor vs mentee), personal interests, and reasons for entry. Study staff “matched” AYAs 1:1 based on shared interests and mutual preferences on match type. Matches were introduced by email and encouraged to interact using any modality (e.g., text, video, in-person) and frequency they preferred. Study staff did not monitor interactions.
Results: Eighteen AYAs (94% female, 89% non-Hispanic white, age 18.9±6.0, T1D duration 8.5±3.3 years) were enrolled from April-December 2022. Median time between first contact and consent was 14 days (range 4-63). The majority (83%) preferred a same-age peer match. Reasons for participation included: not knowing many people with T1D, wanting to discuss T1D with people who shared their experiences, and feeling eager to give advice and support. Six pairs (n=12) have been matched; median time between consent and match was 40 days (range 25-133). Unmatched participants (n=6) have been waiting a median of 131 days (range 21-196) for a suitable match. During the study, 2 participants expressed disappointment that their match was not responsive to messages, and 5 participants expressed excitement about knowing someone new with T1D.
Conclusion: The DiaBuddies pilot study presented challenges with virtual recruitment and matching AYAs on shared interests. Open-ended questions limited opportunity to match objectively, affecting participant wait time and possibly decreasing enthusiasm. Future programs should incorporate lessons learned by modifying the match process to better facilitate AYAs’ desired type and frequency of peer support.
Disclosure
P.Commissariat: None. H.L.Owens: None. L.K.Volkening: None. L.M.Laffel: Advisory Panel; Medtronic, Lilly Diabetes, Novo Nordisk, Vertex Pharmaceuticals Incorporated, Roche Diagnostics, Provention Bio, Inc., Consultant; Dexcom, Inc., Janssen Pharmaceuticals, Inc., Medscape.
Funding
JDRF; National Institutes of Health (P30DK036836)
Background:
Continuous glucose monitoring (CGM) remains underutilized in youth with type 1 diabetes (T1D). There is a need to investigate factors associated with CGM use.
Method:
In 61 T1D youth, CGM ...use was ascertained by downloads reflecting the 4-week periods preceding 3- and 6-month study visits. Demographic and clinical data were obtained from chart review and interview. Youth and parents completed validated psychosocial surveys at baseline and 6 months.
Results:
Youth (52% male, 93% Caucasian, 80% pump treated) were 12.7 ± 2.9 years old, with T1D for 6.3 ± 3.8 years; mean A1c was 7.9 ± 0.9%. Mean CGM use was 4.1 ± 2.1 days/week (median = 4.8) at 3 months and 3.4 ± 2.3 days/week (median = 3.9) at 6 months. At 3 and 6 months, 15% and 20% of youth, respectively, had stopped using CGM. At 6 months, youth using CGM 6-7 days/week had more frequent BG monitoring (P = .05), less insulin omission (P = .02), and greater probability of A1c < 7.5% (P = .01) than youth using CGM less often. Youth using CGM 6-7 days/week consistently over the 6 months demonstrated lower A1c at 3 months compared to baseline (P = .03) and the improvement was sustained at 6 months (P = .5, 3 vs 6 months); youth using CGM less often had no significant A1c change. Baseline BG monitoring ≥8 times/day or A1c within target (<7.5%) predicted greater CGM use (6-7 days/week) at 6 months (OR = 4.6, P = .02). There was no deterioration of psychosocial functioning with CGM use.
Conclusions:
Consistent and durable CGM use in youth with T1D is associated with treatment adherence and improved glycemic control without increasing psychosocial distress.
Youth with T1D often experience emotional distress, which can negatively impact QoL. We sought to understand associations of depressive symptoms and diabetes distress with QoL in youth with T1D. ...Participants (N=420; 50% male; ages 8-17 years; T1D duration 6.4±3.7 (M±SD) years; A1c 8.3±1.0%; 69% pump treated; 70% having parent with college degree) completed the Pediatric Quality of Life Inventory Generic Core Scales (PedsQL)and measures of depressive symptoms (Center for Epidemiologic Studies Depression Scale CESD) and diabetes distress (Problem Areas in Diabetes-Pediatric version PAID-Peds). Multivariable linear modeling determined independent associations of depressive symptoms and diabetes distress with total, physical, and psychosocial QoL, adjusting for sex, age, T1D duration, A1c, pump therapy, insulin dose, and parent education. Total PedsQL score was 85±13, (physical subscale 89±12, psychosocial subscale 82±15); CESD score was 9±9; PAID-Peds score was 37±24. CESD and PAID-Peds were both correlated with A1c (CESD: p=.01, PAID-Peds: p<.0001); QoL scales were not correlated with A1c. CESD and PAID-Peds were correlated with total, physical and psychosocial QoL (all p<.0001). In multivariable analyses, more depressive symptoms were associated with poorer total (∆R2=.52, p<.0001), physical (∆R2=.35, p<.0001), and psychosocial (∆R2=.51, p<.0001) QoL, adjusting for diabetes distress and sociodemographic/diabetes factors. More diabetes distress was associated with poorer total (∆R2=.05, p<.0001) and psychosocial (∆R2=.06, p< .0001) QoL, adjusting for depressive symptoms and sociodemographic/diabetes factors; more diabetes distress marginally contributed to poorer physical QoL (∆R2=.01, p=.002). Findings suggest unique, negative associations of both depressive symptoms and diabetes distress with QoL. Targeting both depressive symptoms and diabetes distress may help improve QoL in youth with T1D.
Disclosure
A. Shapira: None. L. K. Volkening: None. L. M. Laffel: Consultant; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Dexcom, Inc., Dompe, Insulogic LLC, Janssen Pharmaceuticals, Inc., Laxmi Therapeutic Devices, LifeScan, Lilly Diabetes, Medtronic, Provention Bio, Inc.
Funding
National Institutes of Health (R01DK089349, R01DK095273, T32DK007260, P30DK036836); JDRF (2-SRA-2014-253-M-B)
Abstract Purpose Management of type 1 diabetes is complex and benefits from adequate executive function (EF) (planning, organization, problem-solving). Teens with diabetes and executive dysfunction ...may have challenges with the acquisition of self-care skills. Methods Over 18 months, parents of teens with type 1 diabetes aged 13 to 17 completed the Diabetes Family Responsibility Questionnaire (DFRQ) and Readiness for Independent Self-Care Questionnaire (RISQ) every 6 months. Parents assessed teen EF, completing the Behavior Rating Inventory of Executive Function (BRIEF). T-score ≥60 defined EF challenges. EF, demographic, and diabetes treatment variables predicted RISQ score over time using longitudinal mixed modeling with false discovery rate adjustment. Results There were 169 teen participants (54% male) aged 15.9 ± 1.3 years, diabetes duration 8.4 ± 3.7 years, and A1c 8.6 ± 1.2%. About a third (31.4%) of teens had parent-reported BRIEF Global Executive Composite (GEC) scores ≥60. After adjusting for age, sex, and DFRQ, those with GEC <60 had a RISQ score 4.1 points higher than those with GEC ≥60, P = .016. Metacognition index (MI; adjusted for age,sex, and DFRQ) predicted RISQ while behavioral regulation index (adjusted for age, continuous glucose monitor use, DFRQ, and A1c) did not; those with MI <60 had a RISQ score 5.3 points higher than those with MI ≥60, P < .001. In all models, older teen age (P < .05) and less parental involvement (P < .001) predicted higher RISQ score. Conclusion EF skills, especially metacognition, appear important for the acquisition of self-care behaviors in teens with type 1 diabetes. Evaluating EF during adolescence may identify teens needing extra support during the transition process.
The coronavirus disease 2019 (COVID-19) pandemic likely affected youth with type 1 diabetes (T1D). We used electronic health record-extracted data to compare continuous glucose monitoring (CGM) ...metrics during 1 year of the pandemic with those of the previous year. The sample comprised CGM users, aged 1 to <18 years, with T1D duration ≥6 months (age <6 years) or ≥1 year (age ≥6 years). The prepandemic sample comprised 641 youth (52% female, aged 12.3 ± 3.5, T1D duration 6.0 ± 3.5 years). The pandemic sample comprised 648 youth (52% female, age 13.3 ± 3.5, duration 6.7 ± 3.8 years), with care delivered primarily through telemedicine. Mean CGM glucose was 6.3 mg/dL lower during the pandemic (187.3 ± 35.6) versus prepandemic (193.6 ± 33.0) (
< 0.001). A higher percentage of youth achieved glucose management indicator <7% during the pandemic than the prior year (
< 0.001). Lower CGM glucose values were observed during the COVID-19 pandemic. Future studies are needed to assess how changes in health care delivery, including telemedicine, and lifestyle during this time may have supported this improvement.
Objective
Prior to the transfer from paediatric to adult health care transition, teens with type 1 diabetes seek increasing independence in diabetes self‐care while parent involvement in care ...decreases. Yet, few teens attain glycaemic targets. This study aimed to assess changes in perceived readiness for independent self‐care in teens with type 1 diabetes over 18 months, from both teens' and parents' perspectives, and to evaluate its predictive value for diabetes self‐management and haemoglobin A1c (HbA1c).
Research design and methods
At baseline, 6, 12 and 18 months, 178 teens with type 1 diabetes (mean ± SD age 14.9±1.3 years; HbA1c 8.5 ± 1.0% (69 ± 11 mmol/mol); 48% female) and their parents completed the Readiness for Independent Self‐Care Questionnaire (RISQ‐T and RISQ‐P, respectively) and a measure of self‐management. Chart review provided HbA1c values. Statistical analyses encompassed bivariate correlations, paired t‐tests and multivariable longitudinal mixed models.
Results
Teens perceived greater self‐care readiness than their parents at baseline and over 18 months of follow‐up. Both teen and parent perceptions of teen readiness for independent self‐care increased over time, and significantly predicted higher teen self‐ and parent proxy‐reported teen diabetes self‐management, respectively, but not improved HbA1c.
Conclusions
The current findings may point to a disconnect between how increased readiness for independent self‐care may translate into better perceived diabetes self‐management, but not into better HbA1c. In an effort to optimize HbA1c in teens with type 1 diabetes, future research is needed to design interventions that align perceived readiness for independent self‐care with self‐care behaviours that improve HbA1c.
PDF
