Search

Context Adults with type 1 diabetes (T1D) face the necessity of balancing the benefits of exercise with the potential hazards of hypoglycemia. Objective This work aimed to assess whether impaired awareness of hypoglycemia (IAH) affects exercise-associated hypoglycemia in adults with T1D. Methods We compared continuous glucose monitoring (CGM)-measured glucose during exercise and for 24 hours following exercise from 95 adults with T1D and IAH (Clarke score ≥4 or ≥1 severe hypoglycemic event within the past year) to 95 "aware" adults (Clarke score ≤2 and no severe hypoglycemic event within the past year) matched on sex, age, insulin delivery modality, and glycated hemoglobin A1c. A total of 4236 exercise sessions, and 1794 exercise days and 839 sedentary days, defined as 24 hours following exercise or a day without exercise, respectively, were available for analysis. Results Participants with IAH exhibited a nonsignificant trend toward greater decline in glucose during exercise compared to "aware" (−21 ± 44 vs −19 ± 43 mg/dL [−1.17 ± 2.44 vs −1.05 ± 2.39 mmol/L], adjusted group difference of −4.2 [95% CI, −8.4 to 0.05] mg/dL [−0.23 95% CI, −.47 to 0.003 mmol/L]; P =.051). Individuals with IAH had a higher proportion of days with hypoglycemic events below 70 mg/dL [3.89 mmol/L] (≥15 minutes <70 mg/dL [<3.89 mmol/L]) both on exercise days (51% vs 43%; P =.006) and sedentary days (48% vs 30%; P =.001). The increased odds of experiencing a hypoglycemic event below 70 mg/dL (<3.89 mmol/L) for individuals with IAH compared to "aware" did not differ significantly between exercise and sedentary days (interaction P =.36). Conclusion Individuals with IAH have a higher underlying risk of hypoglycemia than "aware" individuals. Exercise does not appear to differentially increase risk for hypoglycemia during the activity, or in the subsequent 24 hours for IAH compared to aware individuals with T1D. [ABSTRACT FROM AUTHOR]

PurposeThe aim of this study was to assess the effect of donor and recipient factors on corneal allograft rejection and evaluate whether a rejection event was associated with graft failure.MethodsOne thousand ninety subjects undergoing penetrating keratoplasty for a moderate risk condition (principally Fuchs dystrophy or pseudophakic corneal edema) were followed for up to 12 years. Associations of baseline recipient and donor factors with the occurrence of a rejection event were assessed in univariate and multivariate proportional hazards models.ResultsAmong 651 eyes with a surviving graft at 5 years, the 10-year graft failure (±99% confidence interval) rates were 12% ± 4% among eyes with no rejection events in the first 5 years, 17% ± 12% in eyes with at least 1 probable, but no definite rejection event, and 22% ± 20% in eyes with at least 1 definite rejection event. The only baseline factor significantly associated with a higher risk of definite graft rejection was a preoperative history of glaucoma, particularly when previous glaucoma surgery had been performed and glaucoma medications were being used at the time of transplant (10-year incidence 35% ± 23% compared with 14% ± 4% in eyes with no history of glaucoma/intraocular pressure treatment, P = 0.008).ConclusionsPatients who experienced a definite rejection event frequently developed graft failure raising important questions as to how we might change acute and long-term corneal graft management. Multivariate analysis indicated that previous use of glaucoma medications and glaucoma filtering surgery was a significant risk factor related to a definite rejection event.

OBJECTIVE: To explore 24-h postexercise glycemia and hypoglycemia risk, data from the Type 1 Diabetes Exercise Initiative Pediatric (T1DEXIP) study were analyzed to examine factors that may influence glycemia. RESEARCH DESIGN AND METHODS: This was a real-world observational study with participant self-reported physical activity, food intake, and insulin dosing (multiple daily injection users). Heart rate, continuous glucose data, and available pump data were collected. RESULTS: A total of 251 adolescents (42% females), with a mean ± SD age of 14 ± 2 years, and hemoglobin A1c (HbA1c) of 7.1 ± 1.3% (54 ± 14.2 mmol/mol), recorded 3,319 activities over ∼10 days. Trends for lower mean glucose after exercise were observed in those with shorter disease duration and lower HbA1c; no difference by insulin delivery modality was identified. Larger glucose drops during exercise were associated with lower postexercise mean glucose levels, immediately after activity (P < 0.001) and 12 to <16 h later (P = 0.02). Hypoglycemia occurred on 14% of nights following exercise versus 12% after sedentary days. On nights following exercise, more hypoglycemia occurred when average total activity was ≥60 min/day (17% vs. 8% of nights, P = 0.01) and on days with longer individual exercise sessions. Higher nocturnal hypoglycemia rates were also observed in those with longer disease duration, lower HbA1c, conventional pump use, and if time below range was ≥4% in the previous 24 h. CONCLUSIONS: In this large real-world pediatric exercise study, nocturnal hypoglycemia was higher on nights when average activity duration was higher. Characterizing both participant- and event-level factors that impact glucose in the postexercise recovery period may support development of new guidelines, decision support tools, and refine insulin delivery algorithms to better support exercise in youth with diabetes. [ABSTRACT FROM AUTHOR]

ObjectiveTo examine the effect of donor age and other perioperative factors on long-term endothelial cell loss after penetrating keratoplasty (PKP).DesignMulticenter, prospective, double-masked clinical trial.ParticipantsWe included 176 participants from the Cornea Donor Study cohort who had not experienced graft failure ≥ 10 years after PKP for a moderate risk condition (principally Fuchs' dystrophy or pseudophakic/aphakic corneal edema).MethodsCorneas from donors 12 to 75 years old were assigned to participants using a randomized approach, without respect to recipient factors. Surgery and postoperative care were performed according to the surgeons' usual routines. Images of the central endothelium were obtained preoperatively and at intervals for 10 years postoperatively. Images were analyzed by a central image analysis reading center to determine endothelial cell density (ECD).Main outcome measuresEndothelial cell density at 10 years.ResultsAmong study participants with a clear graft at 10 years, the 125 who received a cornea from a donor 12 to 65 years old experienced a median cell loss of 76%, resulting in a 10-year median ECD of 628 cells/mm(2) (interquartile range [IQR], 522-850 cells/mm(2)), whereas the 51 who received a cornea from a donor 66 to 75 years old experienced a cell loss of 79%, resulting in a median 10-year ECD of 550 cells/mm(2) (IQR, 483-694 cells/mm(2); P adjusted for baseline ECD = 0.03). In addition to younger donor age, higher ECD values were significantly associated with higher baseline ECD (P1000 cells/mm(2).ConclusionsSubstantial cell loss occurs in eyes with a clear graft 10 years after PKP, with the rate of cell loss being slightly greater with older donor age. Greater preoperative ECD and larger donor tissue size are associated with higher ECD at 10 years.

ObjectiveTo determine whether the 10-year success rate of penetrating keratoplasty for corneal endothelial disorders is associated with donor age.DesignMulticenter, prospective, double-masked clinical trial.ParticipantsA total of 1090 participants undergoing penetrating keratoplasty at 80 sites for Fuchs' dystrophy (62%), pseudophakic/aphakic corneal edema (34%), or another corneal endothelial disorder (4%) and followed for up to 12 years.MethodsForty-three eye banks provided corneas from donors aged 12 to 75 years, using a randomized approach to assign donor corneas to study participants without respect to recipient factors. Surgery and postoperative care were performed according to the surgeons' usual routines.Main outcome measuresGraft failure defined as a regraft or, in the absence of a regraft, a cloudy cornea that was sufficiently opaque to compromise vision for 3 consecutive months.ResultsIn the primary analysis, the 10-year success rate was 77% for 707 corneas from donors aged 12 to 65 years compared with 71% for 383 donors aged 66 to 75 years (difference, +6%; 95% confidence interval, -1 to +12; P = 0.11). When analyzed as a continuous variable, higher donor age was associated with lower graft success beyond the first 5 years (P

OBJECTIVE: Data from the Type 1 Diabetes Exercise Initiative Pediatric (T1DEXIP) study were evaluated to understand glucose changes during activity and identify factors that may influence changes. RESEARCH DESIGN AND METHODS: In this real-world observational study, adolescents with type 1 diabetes self-reported physical activity, food intake, and insulin dosing (multiple-daily injection users) using a smartphone application. Heart rate and continuous glucose monitoring data were collected, as well as pump data downloads. RESULTS: Two hundred fifty-one adolescents (age 14 ± 2 years [mean ± SD]; HbA1c 7.1 ± 1.3% [54 ± 14.2 mmol/mol]; 42% female) logged 3,738 activities over ∼10 days of observation. Preactivity glucose was 163 ± 66 mg/dL (9.1 ± 3.7 mmol/L), dropping to 148 ± 66 mg/dL (8.2 ± 3.7 mmol/L) by end of activity; median duration of activity was 40 min (20, 75 [interquartile range]) with a mean and peak heart rate of 109 ± 16 bpm and 130 ± 21 bpm. Drops in glucose were greater in those with lower baseline HbA1c levels (P = 0.002), shorter disease duration (P = 0.02), less hypoglycemia fear (P = 0.04), and a lower BMI (P = 0.05). Event-level predictors of greater drops in glucose included self-classified "noncompetitive" activities, insulin on board >0.05 units/kg body mass, glucose already dropping prior to the activity, preactivity glucose >150 mg/dL (>8.3 mmol/L) and time 70–180 mg/dL >70% in the 24 h before the activity (all P < 0.001). CONCLUSIONS: Participant-level and activity event-level factors can help predict the magnitude of drop in glucose during real-world physical activity in youth with type 1 diabetes. A better appreciation of these factors may improve decision support tools and self-management strategies to reduce activity-induced dysglycemia in active adolescents living with the disease. [ABSTRACT FROM AUTHOR]

Objective Nocturnal hypoglycemia is a known challenge for people with type 1 diabetes, especially for physically active individuals or those on multiple daily injections. We developed an evidential neural network (ENN) to predict at bedtime the probability and timing of nocturnal hypoglycemia (0-4 vs 4-8 h after bedtime) based on several glucose metrics and physical activity patterns. We utilized these predictions in silico to prescribe bedtime carbohydrates with a Smart Snack intervention specific to the predicted minimum nocturnal glucose and timing of nocturnal hypoglycemia. Materials and methods We leveraged free-living datasets collected from 366 individuals from the T1DEXI Study and Glooko. Inputs to the ENN used to model nocturnal hypoglycemia were derived from demographic information, continuous glucose monitoring, and physical activity data. We assessed the accuracy of the ENN using area under the receiver operating curve, and the clinical impact of the Smart Snack intervention through simulations. Results The ENN achieved an area under the receiver operating curve of 0.80 and 0.71 to predict nocturnal hypoglycemic events during 0-4 and 4-8 h after bedtime, respectively, outperforming all evaluated baseline methods. Use of the Smart Snack intervention reduced probability of nocturnal hypoglycemia from 23.9 ± 14.1% to 14.0 ± 13.3% and duration from 7.4 ± 7.0% to 2.4 ± 3.3% in silico. Discussion Our findings indicate that the ENN-based Smart Snack intervention has the potential to significantly reduce the frequency and duration of nocturnal hypoglycemic events. Conclusion A decision support system that combines prediction of minimum nocturnal glucose and proactive recommendations for bedtime carbohydrate intake might effectively prevent nocturnal hypoglycemia and reduce the burden of glycemic self-management. [ABSTRACT FROM AUTHOR]

OBJECTIVE: Maintenance of glycemic control during and after exercise remains a major challenge for individuals with type 1 diabetes. Glycemic responses to exercise may differ by exercise type (aerobic, interval, or resistance), and the effect of activity type on glycemic control after exercise remains unclear. RESEARCH DESIGN AND METHODS: The Type 1 Diabetes Exercise Initiative (T1DEXI) was a real-world study of at-home exercise. Adult participants were randomly assigned to complete six structured aerobic, interval, or resistance exercise sessions over 4 weeks. Participants self-reported study and nonstudy exercise, food intake, and insulin dosing (multiple daily injection [MDI] users) using a custom smart phone application and provided pump (pump users), heart rate, and continuous glucose monitoring data. RESULTS: A total of 497 adults with type 1 diabetes (mean age ± SD 37 ± 14 years; mean HbA1c ± SD 6.6 ± 0.8% [49 ± 8.7 mmol/mol]) assigned to structured aerobic (n = 162), interval (n = 165), or resistance (n = 170) exercise were analyzed. The mean (± SD) change in glucose during assigned exercise was −18 ± 39, −14 ± 32, and −9 ± 36 mg/dL for aerobic, interval, and resistance, respectively (P < 0.001), with similar results for closed-loop, standard pump, and MDI users. Time in range 70–180 mg/dL (3.9–10.0 mmol/L) was higher during the 24 h after study exercise when compared with days without exercise (mean ± SD 76 ± 20% vs. 70 ± 23%; P < 0.001). CONCLUSIONS: Adults with type 1 diabetes experienced the largest drop in glucose level with aerobic exercise, followed by interval and resistance exercise, regardless of insulin delivery modality. Even in adults with well-controlled type 1 diabetes, days with structured exercise sessions contributed to clinically meaningful improvement in glucose time in range but may have slightly increased time below range. [ABSTRACT FROM AUTHOR]

Insulin is commonly used to reverse gluco‐toxicity in youth with newly diagnosed type 2 diabetes (T2D), but many are subsequently weaned off insulin. We analyzed Pediatric Diabetes Consortium (PDC) data to determine how long glycemic control is maintained after termination of initial insulin treatment. Youth with T2D who had previously been on insulin but were on either an intensive lifestyle intervention alone or metformin alone upon enrollment in the PDC T2D Registry were studied (N = 183). The primary outcome was time to treatment failure, defined by need to restart insulin or metformin or another diabetes medication. Data were analyzed using logistic regression to assess risk factors for treatment failure. Of the 183 participants studied (mean age 15 years, diabetes duration 1.7 years), 54% experienced treatment failure (median follow‐up time 1.7 years). In the subgroup on metformin monotherapy (N = 140), 45% subsequently required restart of insulin. Moreover, of participants in the subgroup treated with an intensive lifestyle intervention alone (N = 43), 81% restarted insulin or were treated with metformin or other diabetes medication. In both groups, median time to treatment failure was 1.2 years. Higher HbA1c at enrollment was significantly associated with treatment failure (p < 0.001). Youth with T2D who are initially treated with insulin have a high rate of treatment failure when switched to intensive lifestyle alone or metformin alone. Our data highlight the severe and progressive nature of youth onset T2D, hence patients should be monitored closely for deteriorating glycemic control after being weaned off insulin. [ABSTRACT FROM AUTHOR]