Abstract
Context
Minority young adults (YA) currently represent the largest growing population with type 1 diabetes (T1D) and experience very poor outcomes. Modifiable drivers of disparities need to ...be identified, but are not well-studied.
Objective
To describe racial-ethnic disparities among YA with T1D and identify drivers of glycemic disparity other than socioeconomic status (SES).
Design
Cross-sectional multicenter collection of patient and chart-reported variables, including SES, social determinants of health, and diabetes-specific factors, with comparison between non-Hispanic White, non-Hispanic Black, and Hispanic YA and multilevel modeling to identify variables that account for glycemic disparity apart from SES.
Setting
Six diabetes centers across the United States.
Participants
A total of 300 YA with T1D (18-28 years: 33% non-Hispanic White, 32% non-Hispanic Black, and 34% Hispanic).
Main Outcome
Racial-ethnic disparity in HbA1c levels.
Results
Non-Hispanic Black and Hispanic YA had lower SES, higher HbA1c levels, and much lower diabetes technology use than non-Hispanic White YA (P < 0.001). Non-Hispanic Black YA differed from Hispanic, reporting higher diabetes distress and lower self-management (P < 0.001). After accounting for SES, differences in HbA1c levels disappeared between non-Hispanic White and Hispanic YA, whereas they remained for non-Hispanic Black YA (+ 2.26% 24 mmol/mol, P < 0.001). Diabetes technology use, diabetes distress, and disease self-management accounted for a significant portion of the remaining non-Hispanic Black–White glycemic disparity.
Conclusion
This study demonstrated large racial-ethnic inequity in YA with T1D, especially among non-Hispanic Black participants. Our findings reveal key opportunities for clinicians to potentially mitigate glycemic disparity in minority YA by promoting diabetes technology use, connecting with social programs, and tailoring support for disease self-management and diabetes distress to account for social contextual factors.
Corticosteroids for treating optic neuritis Gal, Robin L; Gal, Robin L; Vedula, S Swaroop ...
Cochrane database of systematic reviews,
08/2015, Letnik:
2021, Številka:
11
Journal Article
Recenzirano
Odprti dostop
Background
Optic neuritis is an inflammatory disease of the optic nerve. It usually presents with an abrupt loss of vision and recovery of vision is almost never complete. It occurs more commonly in ...women than in men. Closely linked in pathogenesis, optic neuritis may be the initial manifestation for multiple sclerosis. In some people, no underlying cause can be found.
Objectives
The objective of this review was to assess the effects of corticosteroids on visual recovery in eyes with acute optic neuritis.
Search methods
We searched CENTRAL (which contains the Cochrane Eyes and Vision Group Trials Register) (The Cochrane Library 2015, Issue 4), MEDLINE (January 1950 to April 2015), EMBASE (January 1980 to April 2015), Latin American and Caribbean Health Sciences Literature (LILACS) (January 1982 to April 2015), PubMed (January 1946 to April 2015), the metaRegister of Controlled Trials (mRCT) (www.controlled-trials.com), ClinicalTrials.gov (www.clinicaltrials.gov), and the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP) (www.who.int/ictrp/search/en). There were no date or language restrictions in the electronic searches for trials. The metaRegister of Controlled Trials (mRCT) was last searched on 6 March 2014. The electronic databases were last searched on 7 April 2015. We also searched reference lists of identified trial reports for additional trials.
Selection criteria
We included randomized controlled trials (RCTs) that evaluated systemic corticosteroids, in any form, dose or route of administration, in people with acute optic neuritis.
Data collection and analysis
We used standard methodological procedures expected by Cochrane.
Main results
We included six RCTs with a total of 750 participants. Each trial was conducted in a different country: Denmark, Germany, India, Japan, UK, and United States. Additionally, we identified two ongoing trials not due to be completed until 2016. Among the six trials included in this review, we judged one to be at high risk of bias. The remaining five trials were judged to be at either low or uncertain risk of biases.
Five trials compared only two intervention groups and one trial had a three‐arm comparison of oral corticosteroids or intravenous corticosteroids with placebo. Of the five trials with only two intervention groups, two trials compared oral corticosteroids versus placebo, two trials compared intravenous corticosteroids with placebo, and one trial compared intravenous dexamethasone with intravenous methylprednisolone plus oral prednisolone.
Three trials evaluating oral corticosteroids used varying doses of corticosteroids versus placebo. In the meta‐analyses to assess visual acuity, the risk ratio (RR) was 1.00 (95% confidence interval (CI) 0.82 to 1.23; participants = 398) at one month; 0.92 (95% CI 0.77 to 1.11; participants = 355) at six months; and 0.93 (95% CI 0.70 to 1.24; participants = 368) at one year. In the meta‐analyses of two trials evaluating corticosteroids with total dose greater than 3000 mg administered intravenously, the RR of normal visual acuity (defined as 20/20 Snellen fraction or equivalent) in the intravenous corticosteroids group compared with the placebo group was 1.05 (95% CI 0.88 to 1.26; participants = 346) at six months. The RR of contrast sensitivity in the normal range for the same comparison was 1.11 (95% CI 0.92 to 1.33; participants = 346) at six months follow‐up. The RR of normal visual field for this comparison was 1.08 (95% CI 0.96 to 1.21; 346 participants) at six months; and 1.01 (95% CI 0.86 to 1.19; participants = 316) at one year. Four trials reported adverse events primarily related to gastrointestinal symptoms and sleep disturbance; one trial reported minor adverse event of acne.
Authors' conclusions
There is no conclusive evidence of benefit in terms of recovery to normal visual acuity, visual field or contrast sensitivity six months after initiation with either intravenous or oral corticosteroids at the doses evaluated in trials included in this review.
To compare races/ethnicities for characteristics, at type 1 diabetes diagnosis and during the first 3 years postdiagnosis, known to influence long-term health outcomes.
We analyzed 927 Pediatric ...Diabetes Consortium (PDC) participants <19 years old (631 non-Hispanic white NHW, 216 Hispanic, and 80 African American AA) diagnosed with type 1 diabetes and followed for a median of 3.0 years (interquartile range 2.2-3.6). Demographic and clinical data were collected from medical records and patient/parent interviews. Partial remission period or "honeymoon" was defined as insulin dose-adjusted hemoglobin A
(IDAA1c) ≤9.0%. We used logistic, linear, and multinomial regression models, as well as repeated-measures logistic and linear regression models. Models were adjusted for known confounders.
AA subjects, compared with NHW, at diagnosis, were in a higher age- and sex-adjusted BMI percentile (BMI%), had more advanced pubertal development, and had higher frequency of presentation in diabetic ketoacidosis, largely explained by socioeconomic factors. During the first 3 years, AA subjects were more likely to have hypertension and severe hypoglycemia events; had trajectories with higher hemoglobin A
, BMI%, insulin doses, and IDAA1c; and were less likely to enter the partial remission period. Hispanics, compared with NHWs, had higher BMI% at diagnosis and over the three subsequent years. During the 3 years postdiagnosis, Hispanics had higher prevalence of dyslipidemia and maintained trajectories of higher insulin doses and IDAA1c.
Youth of minority race/ethnicity have increased markers of poor prognosis of type 1 diabetes at diagnosis and 3 years postdiagnosis, possibly contributing to higher risk of long-term diabetes complications compared with NHWs.
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.
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.
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).
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.
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.
...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.
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.
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.
Some controlled studies have associated afternoon exercise with a biphasic pattern of hypoglycemia (hypo) risk: during exercise and 7-11hrs later. We explored factors relating to nocturnal hypo ...following afternoon exercise (12PM-6PM) among youth in the observational T1DexiP study. Youth with T1D (n=203; mean±SD age14±2 yrs; HbA1c=7.0± 1.2%; 42% female; T1D duration 5.4±3.9yrs; 12% on MDI and 58% on AID) wore a continuous glucose monitor, an activity monitor and logged activity using the Bant app for 10 days. Repeated measures logistic regression adjusted for bedtime glucose and % time below range (TBR < 70mg/dL) in the prior 24hrs. Of the 833 afternoon exercise sessions, 14% led to nocturnal hypo (≥15 consecutive minutes <70 mg/dL). Median TBR was higher in the 24hrs before exercise in youth who developed nocturnal hypo vs those who did not (3% vs 1%), while pre-exercise glucose level, heart rate, and insulin on board were similar. Nocturnal hypo risk was higher among teens who exercised more often during the study (Table). A trend for lower risk was noted with AID use. Our model revealed that participants who exercised >90 min/day had increased risk of nocturnal hypoglycemia, while AID use may reduce risk. This suggests algorithmically modulated insulin delivery may help to mitigate the impact of afternoon exercise on nocturnal glycemia.
Disclosure
J.Sherr: Advisory Panel; Bigfoot Biomedical, Inc., Insulet Corporation, Medtronic, Vertex Pharmaceuticals Incorporated, Cecelia Health, StartUp Health T1D Moonshot, Consultant; Bigfoot Biomedical, Inc., Insulet Corporation, Medtronic, Lilly, Research Support; Insulet Corporation, Medtronic, NIH - National Institutes of Health, Juvenile Diabetes Research Foundation (JDRF), Speaker's Bureau; Insulet Corporation, Zealand Pharma A/S, Lilly, Medtronic. S.Bergford: None. S.R.Patton: None. M.A.Clements: Consultant; Glooko, Inc., Research Support; Dexcom, Inc., Abbott Diabetes. P.Calhoun: None. R.L.Gal: None. M.Riddell: Advisory Panel; Zealand Pharma A/S, Zucara Therapeutics, Indigo Diabetes, Consultant; Lilly Diabetes, Eli Lilly and Company, Jaeb Center for Health Research, Speaker's Bureau; Dexcom, Inc., Novo Nordisk, Sanofi, Stock/Shareholder; Supersapiens, Zucara Therapeutics. T1dexip study group: n/a.
Funding
The Leona M. and Harry B. Helmsley Charitable Trust; Dexcom, Inc.
We explored the association between macronutrient intake and postprandial glucose variability in a large sample of youth living with T1D and consuming free-living meals. In the Type 1 Diabetes ...Exercise Initiative Pediatric (T1DEXIP) Study, youth took photographs before and after their meals on 3 days during a 10 day observation period. We used the remote food photograph method to obtain the macronutrient content of youth's meals. We also collected physical activity, continuous glucose monitoring, and insulin use data. We measured glycemic variability using standard deviation (SD) and coefficient of variation (CV) of glucose for up to 3 h after meals. Our sample included 208 youth with T1D (mean age: 14 ± 2 years, mean HbA1c: 54 ± 14.2 mmol/mol 7.1 ± 1.3%; 40% female). We observed greater postprandial glycemic variability (SD and CV) following meals with more carbohydrates. In contrast, we observed less postprandial variability following meals with more fat (SD and CV) and protein (SD only) after adjusting for carbohydrates. Insulin modality, exercise after meals, and exercise intensity did not influence associations between macronutrients and postprandial glycemic variability. To reduce postprandial glycemic variability in youth with T1D, clinicians should encourage diversified macronutrient meal content, with a goal to approximate dietary guidelines for suggested carbohydrate intake.
To identify recipient factors that may be related to risk of corneal graft failure.
Multicenter, prospective, double-masked, controlled clinical trial.
One thousand ninety subjects undergoing corneal ...transplantation for a moderate-risk condition (principally Fuchs' dystrophy or pseudophakic corneal edema).
Donor corneas were assigned using a random approach without respect to recipient factors, and surgeons were masked to information about the donor cornea, including donor age. Surgery and postoperative care were performed according to the surgeons' usual routines, and subjects were followed up for 5 years. Baseline factors were evaluated for their association with graft failure.
Graft failure, defined as a regraft or a cloudy cornea that was sufficiently opaque to compromise vision for a minimum of 3 consecutive months.
Preoperative diagnosis of pseudophakic or aphakic corneal edema increased graft failure risk approximately 4-fold compared with Fuchs' dystrophy (27% vs. 7%). Prior glaucoma surgery with preoperative glaucoma medication use substantially increased the graft failure rate. Factors not strongly associated with graft failure included age, gender, diabetes, smoking, and graft size.
The risk of graft failure is significantly increased in eyes with pseudophakic or aphakic corneal edema compared with Fuchs' dystrophy, independent of lens status, and in eyes with a history of glaucoma.
Proprietary or commercial disclosure may be found after the references.
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.
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.
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).
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.
To examine the long-term effect of donor diabetes history on graft failure and endothelial cell density (ECD) after penetrating keratoplasty (PK) in the Cornea Donor Study.
Multicenter, prospective, ...double-masked, controlled clinical trial.
One thousand ninety subjects undergoing PK for a moderate risk condition, principally Fuchs' dystrophy or pseudophakic or aphakic corneal edema, were enrolled by 105 surgeons from 80 clinical sites in the United States.
Corneas from donors 12 to 75 years of age were assigned by 43 eye banks to participants without respect to recipient factors. Donor and recipient diabetes status was determined from existing medical records. Images of the central endothelium were obtained before surgery (baseline) and at intervals for 10 years after surgery and were analyzed by a central image analysis reading center to determine ECD.
Time to graft failure (regraft or cloudy cornea for 3 consecutive months) and ECD.
There was no statistically significant association of donor diabetes history with 10-year graft failure, baseline ECD, 10-year ECD, or ECD values longitudinally over time in unadjusted analyses, nor after adjusting for donor age and other significant covariates. The 10-year graft failure rate was 23% in the 199 patients receiving a cornea from a donor with diabetes versus 26% in the 891 patients receiving a cornea from a donor without diabetes (95% confidence interval for the difference, -10% to 6%; unadjusted P=0.60). Baseline ECD (P=0.71), 10-year ECD (P>0.99), and changes in ECD over 10 years (P=0.86) were similar comparing donor groups with and without diabetes.
The study results do not suggest an association between donor diabetes and PK outcome. However, the assessment of donor diabetes was imprecise and based on historical data only. The increasing frequency of diabetes in the aging population in the United States affects the donor pool. Thus, the impact of donor diabetes on long-term endothelial health after PK or endothelial keratoplasty, or both, warrants further study with more precise measures of diabetes and its complications.
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