Improvement in A1c Levels in Early Adulthood in the T1D Exchange: Impact of Racial, Socioeconomic, and Clinical Factors.

CONTEXT: Glycemic control in adolescents with type 1 diabetes is poor; yet, it typically improves during early adulthood. Factors related to improvement of glycemic control are unclear. OBJECTIVE: This work examines how demographic and clinical variables may affect trajectories of glycemic control over time. METHODS: This retrospective, observational study comprised 1775 participants ages 18 to 30 years at enrollment in the T1D Exchange clinic registry. Latent class trajectory modeling was used to determine subgroups following a similar glycated hemoglobin A1c (HbA1c) trajectory over time. RESULTS: Five distinct trajectories of HbA1c classes were identified: "low-decline" and "moderate-decline" groups had low or moderate HbA1c with a gradual decline, the "high-stable" group had high HbA1c and remained stable, and the "very high-rapid decline" and "very high-slow decline" groups had very high HbA1c with rapid or gradual decline. Compared with the "high-stable" group, the "low-decline" and "moderate-decline" groups were more likely to be male (P = .009), White non-Hispanic (P = .02), nonsmokers (P < .001), check self-monitoring blood glucose (SMBG) more frequently (P < .001), and have higher education (P < .001), lower body mass index (P = .02), and lower daily insulin dose (P < .001). Compared with the "very high-rapid decline" and "very high-slow decline" groups, the "low-decline" and "moderate-decline" groups were more likely to be male (P = .02), have higher education (P < .001), use insulin pumps (P = .01), be nonsmokers (P < .001), and have a higher number of SMBG checks per day at enrollment (P < .001). CONCLUSION: We determined 5 distinct patterns of glycemic control from early adulthood into adulthood. Further evaluation into the modifiable factors associated with a declining HbA1c trajectory would aid in the development of targeted interventions.

Validity of Postmortem Glycated Hemoglobin to Determine Status of Diabetes Mellitus in Corneal Donors.

PURPOSE: To examine the stability of postmortem glycated hemoglobin (HbA1c) measurement and its relationship to premortem glycemia. METHODS: Postmortem blood samples were obtained from 32 donors (8 known diabetic) and shipped on ice to a central laboratory to examine the stability of HbA1c measurements during the first 9 postmortem days. Thirty-nine other suspected diabetic donors underwent comparison of premortem and postmortem HbA1c measurements. RESULTS: Postmortem HbA1c measurements remained stable after 9 postmortem days (all measurements within ±0.2% from baseline with a mean difference of 0.02% ± 0.10%). Of the premortem measurements obtained within 90 days before death, 79% were within ±1.0% of the postmortem measurements compared with 40% for measurements more than 90 days apart. Three of the postmortem HbA1c measurements exceeded 6.5% (considered a threshold for diabetes diagnosis), although the medical histories did not indicate any previous diabetes diagnosis. CONCLUSIONS: Postmortem HbA1c testing is feasible with current eye bank procedures and is reflective of glycemic control of donors during 90 days before death. HbA1c testing could potentially be a useful adjunct to review of the medical history and records for donor assessment for endothelial keratoplasty suitability and long-term graft success.

Efficacy of an Overnight Predictive Low-Glucose Suspend System in Relation to Hypoglycemia Risk Factors in Youth and Adults With Type 1 Diabetes.

BACKGROUND: We developed a system to suspend insulin pump delivery overnight when the glucose trend predicts hypoglycemia. This predictive low-glucose suspend (PLGS) system substantially reduces nocturnal hypoglycemia without an increase in morning ketosis. Evaluation of hypoglycemia risk factors that could potentially influence the efficacy of the system remains critical for understanding possible problems with the system and identifying patients that may have the greatest benefit when using the system. METHODS: The at-home randomized trial consisted of 127 study participants with hemoglobin A1c (A1C) of ≤8.5% (mmol/mol) for patients aged 4-14 years and ≤8.0% for patient aged 15-45 years. Factors assessed included age, gender, A1C, diabetes duration, daily percentage basal insulin, total daily dose of insulin (units/kg-day), bedtime BG, bedtime snack, insulin on board, continuous glucose monitor (CGM) rate of change (ROC), day of the week, time system activated, daytime exercise intensity, and daytime CGM-measured hypoglycemia. RESULTS: The PLGS system was effective in preventing hypoglycemia for each factor subgroup. There was no evidence that the PLGS system was more or less effective in preventing hypoglycemia in any one subgroup compared with the other subgroups based on that factor. In addition, the effect of the system on overnight hyperglycemia did not differ in subgroups. CONCLUSIONS: The PLGS system tested in this study effectively reduced hypoglycemia without a meaningful increase in hyperglycemia across a variety of factors.

Factors associated with nocturnal hypoglycemia in at-risk adolescents and young adults with type 1 diabetes.

BACKGROUND: Hypoglycemia remains an impediment to good glycemic control, with nocturnal hypoglycemia being particularly dangerous. Information on major contributors to nocturnal hypoglycemia remains critical for understanding and mitigating risk. MATERIALS AND METHODS: Continuous glucose monitoring (CGM) data for 855 nights were studied, generated by 45 subjects 15-45 years of age with hemoglobin A1c (HbA1c) levels of ≤8.0% who participated in a larger randomized study. Factors assessed for potential association with nocturnal hypoglycemia (CGM measurement of <60 mg/dL for ≥30 min) included bedtime blood glucose (BG), exercise intensity, bedtime snack, insulin on board, day of the week, previous daytime hypoglycemia, age, gender, HbA1c level, diabetes duration, daily basal insulin, and daily insulin dose. RESULTS: Hypoglycemia occurred during 221 of 885 (25%) nights and was more frequent with younger age (P<0.001), lower HbA1c levels (P=0.006), medium/high-intensity exercise during the preceding day (P=0.003), and the occurrence of antecedent daytime hypoglycemia (P=0.001). There was a trend for lower bedtime BG levels to be associated with more frequent nocturnal hypoglycemia (P=0.10). Bedtime snack, before bedtime insulin bolus, weekend versus weekday, gender, and daily basal and bolus insulin were not associated with nocturnal hypoglycemia. CONCLUSIONS: Awareness that HbA1c level, exercise, bedtime BG level, and daytime hypoglycemia are all modifiable factors associated with nocturnal hypoglycemia may help patients and providers decrease the risk of hypoglycemia at night. Risk for nocturnal hypoglycemia increased in a linear fashion across the range of variables, with no clear-cut thresholds to guide clinicians or patients for any particular night.

Inpatient studies of a Kalman-filter-based predictive pump shutoff algorithm.

BACKGROUND: An insulin pump shutoff system can prevent nocturnal hypoglycemia and is a first step on the pathway toward a closed-loop artificial pancreas. In previous pump shutoff studies using a voting algorithm and a 1 min continuous glucose monitor (CGM), 80% of induced hypoglycemic events were prevented. METHODS: The pump shutoff algorithm used in previous studies was revised to a single Kalman filter to reduce complexity, incorporate CGMs with different sample times, handle sensor signal dropouts, and enforce safety constraints on the allowable pump shutoff time. RESULTS: Retrospective testing of the new algorithm on previous clinical data sets indicated that, for the four cases where the previous algorithm failed (minimum reference glucose less than 60 mg/dl), the mean suspension start time was 30 min earlier than the previous algorithm. Inpatient studies of the new algorithm have been conducted on 16 subjects. The algorithm prevented hypoglycemia in 73% of subjects. Suspension-induced hyperglycemia is not assessed, because this study forced excessive basal insulin infusion rates. CONCLUSIONS: The new algorithm functioned well and is flexible enough to handle variable sensor sample times and sensor dropouts. It also provides a framework for handling sensor signal attenuations, which can be challenging, particularly when they occur overnight.