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BackgroundFollowing the launch of the global COVID-19 vaccination campaign, there have been increased reports of autoimmune diseases developing de novo following vaccination. These cases include rheumatoid arthritis, autoimmune hepatitis, immune thrombotic thrombocytopenia, and connective tissue diseases. Nevertheless, COVID-19 vaccines are considered safe for patients with autoimmune diseases and are strongly recommended.ObjectivesThe aim of this in silico analysis is to investigate the presence of protein epitopes encoded by the BNT-162b2 mRNA vaccine, one of the most commonly administered COVID-19 vaccines, that could elicit an aberrant adaptive immune response in predisposed individuals.MethodsThe FASTA sequence of the protein encoded by the BNT-162b2 vaccine was retrieved from http://genome.ucsc.edu and used as a key input to the Immune Epitope Database and Analysis Resource (www.iedb.org). Linear peptides with 90% BLAST homology were selected, and T-cell, B-cell, and MHC ligand assays without MHC restriction were searched and evaluated. HLA-disease associations were screened on the HLA-SPREAD platform (https://hla-spread.igib.res.in) by selecting only positive markers.ResultsA total of 183 epitopes were found, corresponding to 178 SARS-CoV-2 and 5 SARS-CoV spike epitopes, respectively. Results were obtained from 22 T-cell assays, 398 B-cell assays, and 2 MHC ligand assays. Complementary receptors included 1080 T-cell receptors and 0 B-cell receptors.Specifically, the IEDB_epitope:1329790 (NATNVVIKVCEFQFCNDPFLGVYY) was shown to bind to HLA-DRB1*15:02 and HLA-DRB1*15:03 alleles, whereas the IEDB_epitope:1392457 (TKCTLKSFTVEKGIYQTSNFRVQPT) was reported to bind to HLA-DRB1*07:01, HLA-DRB1*03:01, HLA-DRB3*01:01, and HLA-DRB4*01:01 alleles. The HLA alleles detected were found to be positively associated with various immunological disorders (Table 1).Table 1.MHC-restricted epitopes of the BNT-162b2 vaccine and potentially associated immunological conditionsEpitopeAssayMHC moleculeAssociated disease (population)NATNVVIKVCEFQFCNDPFLGVYY + OX(C10)cellular MHC/mass spectrometry ligand presentationHLA-DRB1*15:02Takayasu arteritis (Japanese) Arthritis (Taiwanese) Scleroderma (Japanese) Colitis (Japanese)HLA-DRB1*15:03Systemic lupus erythematosus (Mexican American)TKCTLKSFTVEKGIYQTSNFRVQPT + SCM(K2)as aboveHLA-DRB1*07:01Allergy, hypersensitivity (Caucasian)HLA-DRB1*03:01Type 1 diabetes (African) Sarcoidosis, good prognosis (Finnish)HLA-DRB3*01:01Graves' disease (Caucasian) Thymoma (Caucasian) Sarcoidosis (Scandinavian) Autoimmune hepatitis (Caucasian)HLA-DRB4*01:01Vitiligo (Saudi Arabian)ConclusionSimilar to the SARS-CoV-2 spike protein, the protein product of the BNT-162b2 mRNA vaccine contains immunogenic epitopes that may trigger autoimmune phenomena in predisposed individuals. Genotyping for HLA alleles may help identify at-risk individuals. However, further research is needed to elucidate the underlying mechanisms and potential clinical implications.References[1]Vita R, Mahajan S, Overton JA et al. The Immune Epitope Database (IEDB): 2018 update. Nucleic Acids Res. 2019 Jan 8;47(D1):D339-D343. doi: 10.1093/nar/gky1006.[2]Dholakia D, Kalra A, Misir BR et al. HLA-SPREAD: a natural language processing based resource for curating HLA association from PubMed s. BMC Genomics 23, 10 (2022). https://doi.org/10.1186/s12864-021-08239-0[3]Parker R, Partridge T, Wormald C et al. Mapping the SARS-CoV-2 spike glycoprotein-derived peptidome presented by HLA class II on dendritic cells. Cell Rep. 2021 May 25;35(8):109179. doi: 10.1016/j.celrep.2021.109179.[4]Knierman MD, Lannan MB, Spindler LJ et al. The Human Leukocyte Antigen Class II Immunopeptidome of the SARS-CoV-2 Spike Glycoprotein. Cell Rep. 2020 Dec 1;33(9):108454. doi: 10.1016/j.celrep.2020.108454.Acknowledgements:NIL.Disclosure of InterestsNone Declared.
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A linked ecological analysis of environmental and demographic variables identified several factors, including poor air quality, outdoor light at night, and higher population density that were negatively associated with the incidence of diabetes (Diabetologia doi:10.1007/s00125-020-05087-7). A case-control study using a database of people known to have autoimmune disease raises anxiety about central nervous system inflammatory events (JAMA Neurol doi:10.1001/jamaneurol.2020.1162). A history of exposure to TNF inhibitors carried a threefold increase in risk both of demyelinating diseases, such as multiple sclerosis and optic neuritis, and of non-demyelinating conditions, such as encephalitis, neurosarcoidosis, and vasculitis.
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Introduction: COVID-19 is a complex disease with several clinical phases of progression, affecting many organs apart from the respiratory tract that has shown a worst prognosis in both patients with type 1 and type 2 diabetes mellitus [1]. Based on these considerations, the vaccination for COVID-19 is a priority for this subpopulation [2]. However, few data have been published on the effects of impaired glucose metabolism induced by COVID-19 vaccines. Objective: We decided to perform a study to describe Individual Case Safety Reports (ICSRs) of impaired glucose metabolism events reported in the European database (Eudravigilance, EV). Methods: ICSRs were retrieved for the period from January 1st, 2021 to December 11th, 2021. An ICSR related to events of impaired glucose metabolism was identified by using selected preferred terms (PTs) from Standardized MedDRA Queries "Hyperglycaemia/new onset diabetes mellitus" and "Hypoglycaemia". Impaired glucose metabolism events were described and analyzed based on the Diabetologists' classification into nine groups: "diabetes in pregnancy", "acute complications of diabetes", "pre-diabetes", "type 1 diabetes mellitus", "type 2 diabetes mellitus", "high glucose levels", "diabetes mellitus inadequate control", "diabetes melli-tus not specified", and "hypoglycaemia". The reporting odds ratios were computed to assess the reporting frequency for COVID-19 mRNA vaccines compared to COVID-19 viral vector-based vaccines. Results: During the study period, 3,917 ICSRs with a COVID-19 vaccine as suspected and at least an event of impaired glucose metabolism were retrieved from the EV, of which 2,027 (51.75%) referred to Pfizer-BioNTech vaccine, 586 (14.96%) to Moderna vaccine, 1,163 (29.70%) to Oxford-AstraZeneca vaccine, and 141 (3.59%) to Janssen vaccine. From 3,917 ICSRs, we observed 4,275 impaired glucose metabolism events (1.09 adverse events per ICSR). Most adverse events were classified as serious (2,694;63.02%), and the most reported events were related to "high glucose levels" (2,012;47.06%). The mRNA vaccines were associated with an increased reporting frequency of "type 1 diabetes mellitus" (ROR 1.86;95% CI 1.33-2.60), "type 2 diabetes mellitus" (ROR 1.58;95% CI 1.03-2.42), "high glucose levels" (ROR 1.16;95% CI 1.06-1.27), "diabetes mellitus inadequate control" (ROR 1.63;95% CI 1.25-2.11), and "hypoglycemia" (ROR 1.62;95% CI 1.41-1.86) compared to viral vector-based vaccines. The highest reporting rate per 100,000 was observed for Oxford-AstraZeneca vaccine (1.87;95% CI 1.77-1.97). Conclusion: In conclusion, mRNA COVID-19 vaccines were associated with an increased reporting frequency of alterations of glucose homeostasis compared to viral-vector COVID-19 vaccines. Clinicians should be aware of these events to better manage glycaemic perturbations. Larger nationwide studies are warranted to verify these findings.
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AimsThe COVID-19 pandemic impacted the daily routine of children by the introduction of remote learning and telemedicine. The impact of these changes is unclear in the management of type 1 diabetes in children. The aim of this study was to evaluate the impact of several lockdowns on glycaemic control in children and adolescents with type 1 diabetes in a large paediatric hospital in the UK.MethodsThis retrospective observational cohort study reviewed real world data from patients with type 1 diabetes who used glucose monitoring devices including continuous glucose monitors, flash glucose monitors or self-monitoring of blood glucose. Data was collected from four timeframes matching the dates of lockdown restrictions in the UK, T1 - 5/11/2019 to 23/3/2020, T2 - 24/3/2020 to 8/8/2020, T3 - 5/11/2020 to 23/3/2021 and T4 - 24/3/2021 to 8/8/2021. Time in Range (TIR), Mean blood sugar and standard deviation (SD) of blood sugar readings were compared across all four timeframes using paired T-tests.ResultsA total of 243 children (128 male and 115 female) were included in the study with a mean age of 14.2 ± 3.71 (standard deviation) years old. The median duration of T1D was 6.15 years (IQR 4.25-8.68). There was an increase in percentage TIR between T2 vs T4(56.8% vs 57.8%, p = 0.037) and improved glucose variability, as shown by SD between T1 vs T2 (4.57 mmol/L vs 4.44 mmol/L, p = 0.0014), T2 vs T4 (4.44 mmol/L vs 4.41 mmol/L, p = 0.0028) and T3 vs T4 (4.42 mmol/L vs 4.41 mmol/L, p = 0.027).ConclusionGlycaemic control did not decline in children and adolescents with T1D as a result of the COVID-19 pandemic, rather%TIR and SD of blood glucose showed improvement across a series of the three UK lockdowns. Enthusiasm to revert back from telemedicine following the pandemic should be tempered by our findings that remote management has not been detrimental to glycaemic control.
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AimsHbA1c levels were measured less frequently in our paediatric diabetes clinics as several restrictions were put in place due to the Covid-19 pandemic. We set out to determine whether these restrictions affected our patients’ HbA1c control.MethodsAll HbA1c levels of patients with type 1 diabetes were collected from the following time period: (i) pre-lockdown HbA1c (Pre-LD), (ii) first lockdown HbA1c (F-LD), (iii) last lockdown HbA1c (L-LD), coinciding with a gradual phased return to quarterly HbA1c measurement in our clinics, and (iv) first post-lockdown HbA1c (Post-LD), after March 2021. Data were tested for significance using Wilcoxon signed-rank test and expressed as median (IQR).Results97 patients aged 14.5 ± 3.3 were included. HbA1c levels increased Post-LD (58 (52-67)mmol/mol) compared to Pre-LD (57 (50-66)mmol/mol;p=0.03). We found no significant differences in all other HbA1c levels. F-LD HbA1c were 58 (50-65)mmol/mol. L-LD HbA1c were 57 (51.5-65)mmol/mol. There was a gradual increase in mean HbA1c level over the time period from 59.0mmol/mol to 61.5mmol/mol.ConclusionOur study showed slightly worse glycaemic control due to the Covid-19 pandemic although whether this disruption is sustained is unknown. The next part of this study aims to ascertain whether glycaemic control will improve as we return to quarterly HbA1c measurement.
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Recent reports suggest a potential relationship between COVID-and onset of diabetes (DM) . We present the case of a 35 yr old female with type 1 DM (T1DM) who following COVID-pneumonia (COVP) developed worsening insulitis suggesting a potential direct effect of COVID-on beta cell function. The patient is a 35 yr old Caucasian female with T1DM first diagnosed 5 yrs ago. She had some residual beta cell secretory function with fasting C-peptide;0.51 (0-8-3.85ng/ml) . She also has hemochromatosis, thyroiditis with thyroid nodular disease and +ve history of T1DM in her older brother and maternal cousin. Since diagnosis she has been on insulin pump therapy and a CGMS device with excellent glycemic control and HBA1c of 6.7-7.1. She had not received the COVID-vaccine and had COVP in July 2021 requiring inpatient care but not intubation. She received oral steroids and Remdesivir with salutary response. She has not had post-acute sequelae of SARS-CoV (PASC) but ˜ 2 months post discharge had acute thyroiditis with no thyroid abscess, elevated sed rate, leucocytosis and peak thyroglobulin;158 (3-40ng/ml) . Since discharge she noted persistent global hyperglycemia requiring increased basal and bolus insulin therapy with peak HBA1c of 8.3. Further evaluation showed active insulitis with reduced C-peptide 0.and increase in islet related antibodies compared to titers obtained at the time of initial diagnosis 5 yrs prior. The clinical presentation of our patient suggests a potential role of COVID-in inducing insulitis with significant implications for at risk patients including T1DM patients with preserved islet function but also type 2 DM and LADA patients. This case provides another compelling reason for advocating COVID-vaccination in at risk patients. The duration of this effect on islet function and whether beta cell functional recovery is possible over time remains to be seen. The insulitis manifests with worsening glycemic profiles as well as possibly impacting islet mediated counterregulatory glycemic responses.
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Introduction: T1D management, age-related stressors and the COVID-pandemic may impair sleep for young adults with T1D. Disparities in A1c and exposure to life stressors may contribute to poorer sleep among people from minoritized racial/ethnic groups. We aimed to describe sleep, correlations with A1c, and sleep patterns across racial/ethnic groups in young adults with T1D during the pandemic. Methods: Young adults with T1D (n=37, M age=20.2±1.6 yrs, 57% female, M A1c=8.9±2.4%) completed an adapted Pittsburgh Sleep Quality Index and 1 sleep-related question from a COVID-questionnaire at baseline of a behavioral trial. Results Overall, 41% endorsed worse sleep during the pandemic, which was correlated with poorer sleep quality (r=-.69, p<.001) and shorter sleep duration (r=-.35, p=.04) . Higher A1c was linked with less frequent T1D management-related sleep disruptions (r=-.44, p=.007) . There were no significant differences in sleep variables among racial/ethnic groups. See Table for sleep descriptions for each racial/ethnic group. Conclusions: Young adults with T1D experienced disrupted sleep, worsened by the pandemic. Clinicians should counsel patients about optimizing sleep and overnight diabetes management, especially those with higher A1c. While small sizes reduced power to detect group differences, initial patterns suggest a need for future research examining disparities in sleep for young adults with T1D.
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Aim: The COVID-pandemic has affected access to healthcare services worldwide, including the pediatric population. This systematic review and meta-analysis aimed to estimate the risk of severe diabetic ketoacidosis (DKA) among children with type 1 diabetes (T1DM) during the COVID-pandemic compared pre-pandemic era. Methods: PubMed, EMBASE, and the Elsevier Coronavirus Research Repository Hub were searched for relevant observational studies. Studies published as an or in non-English language were excluded. The primary outcome is the risk of severe DKA among children with T1DM during the COVID-pandemic compared to the prior-to-COVID-group. The second outcome is the risk of severe DKA among children with newly diagnosed T1DM. A random meta-analysis model was performed using R version 4.0.4 to estimate the relative risk of severe DKA. Results: A total of 18 studies were included in this metanalysis. Severe DKA risk was 76% (RR 1.76, 95%CI 1.33-2.33, I2=44%) higher during the COVID-pandemic than the pre-COVID-period. Among patients with newly diagnosed T1DM, the risk of severe DKA was 44% higher for the during-COVID-group (RR 1.44, 95%CI 1.26-1.65;I2=64%) . The bias assessment of the included studies using the Newcastle-Ottawa Scale (NOS) showed that all studies had quality indicators (>7 points) . In addition, the results of Eager's test did not show potential for publication bias. Conclusions: This study showed that severe DKA risk had increased significantly during the COVID-pandemic compared to the pre-pandemic period.
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Brain changes in people with type 1 diabetes People in middle age or older who have longstanding type 1 diabetes show structural differences in brain volume and white matter hyperintensities compared with a demographically similar control group, according to a magnetic resonance imaging study from North America. Sex differences in sudden cardiac death A review of autopsy reports, death certificates, discharge summaries, and nationwide health registries identified nearly 7000 cases of sudden cardiac death that had occurred in Denmark in 2010. Average age at the time of sudden cardiac death was 71 in men and 79 in women (Heart doi:10.1136/heartjnl-2021-320300).
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Evidence supporting the involvement of EVs in the pathogenesis/severity of SARS-CoV-2 infection is starting to accumulate. However, little is known about their specific associations in the context of COVID-and type 2 diabetes interaction. Our study included 48 plasma samples (N=12/group) obtained from COVID-patients with and without diabetes and from patients with non-COVID-acute respiratory diagnosis (RSP) with and without diabetes. Participants were identified from a set of 494 patients hospitalized at AdventHealth in June-August 2020. Important efforts were made to ensure the homogeneity of the study cohort. Patients with type 1 diabetes, or pregnant, or that went directly into the ICU were excluded, and 4 balanced groups were identified after 10,000 random cohorts were generated and differences in age, gender, race, and ethnicity statistically assessed. EVs were isolated using EVTRAP (Tymora) . Mass spectrometry-based methods were used to detect the global EV proteome and phosphoproteome. Differentially expressed features, enriched pathways, and enriched tissue-specific protein sets were identified. Multidimensional scaling of all EV proteomic and phosphoproteomic data and unsupervised clustering of differentially expressed (absolute fold change ≥ 2, P < 0.05, FDR < 0.05) EV proteins and phosphoproteins successfully distinguished the 4 study groups with close to 100% accuracy. Importantly, we detected enriched pathway networks that suggest the potential therapeutic utility of PKC inhibitors such as bisindolylmaleimide IX, sotrastaurin, and enzastaumn, and inhibitors of ROCK1 such the isoquinoline derivative Fasudil. In conclusion, we characterized the proteomic landscape of the interaction between type 2 diabetes and COVID-and defined disease-specific EV proteomic signatures that provide insight into the disease pathobiology and druggable targets with potential clinical utility.
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Objective: Since the COVID-pandemic began, instead of in-office care alone, many institutions implemented hybrid care (in-office + telemedicine) . It is not known if hybrid care is as effective as in-office visits in regards to achieving glycemic goals. Methods: Clinical characteristics of adults with type 1 diabetes (T1D) (age ≥40 years) were retrieved from electronic health records from two periods: in-office model before the pandemic (April 2019-March 2020) and hybrid-care model during the pandemic (September 20pril 2021) . Patients were stratified by age. Results: Overall, 1,820 patients were evaluated, 66% younger (40-64 years: mean age 52±7yrs, 52% female, 53% CGM users, 56% pump users) and 34% older (≥65 years: mean age 72±5yrs, 55% female, 53% CGM users, 38% pump users) . A1c using hybrid-care improved in both younger (7.8±1.2 vs. 7.6±1.2%;p=0.005) and older adults (7.6±0.9 vs. 7.4±1%;p=0.02) , compared to in-office care. Within the hybrid-care model period, poor glycemic control was associated with a higher number of hybrid visits, and more in-office missed appointments, while pump use was associated with lower A1c. Conclusion: Compared with in-office care, hybrid care was effective at maintaining glycemic control in both younger and older adults with T1D. Prospective studies are needed to understand the use of hybrid-care for the management of adults with T1D.
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During the COVID-pandemic, patients diagnosed with diabetes have been overrepresented among patients admitted to hospital with COVID-19. We explored the impact of diabetes on mortality and clinical outcomes in hospitalized patients with COVID-in the Capital Region of Denmark. All patients from the Capital Region of Denmark admitted to hospital with COVID-in the period from February 2020 to March 2021 were included. Patients with a diabetes diagnosis were compared to patients without a diabetes diagnosis in multivariable adjusted analyses. The primary outcome was death within 30 days from hospitalization. Secondary outcomes included time to discharge, use of oxygen treatment, referral to intensive care unit, and use of respirator. Among 3,997 hospital admitted patients, 1,186 had diabetes (1,090 type 2 diabetes;96 type 1 diabetes) . The patients with diabetes were 59% men, 72±13 years (mean±standard deviation) with BMI 28±6.4 kg/m2, while patients without diabetes were 51% men, 67±years with BMI 26±5.8 kg/m2. Within 30 days, 292 (24.6%) patients with diabetes died compared to 521 (18.5%) without diabetes (adjusted odds ratio (aOR) 1.28 (95% CI 1.02-1.6) for death) . Patients with diabetes were 24% less likely to be discharged alive at any given time compared to patients without diabetes with a hazard ratio of 0.76 (0.70-0.81) . aOR for oxygen treatment was 1. (0.97-1.47) , for referral to intensive care unit 1.37 (1.01-1.85) , and for use of respirator 1. (0.86-1.65) . We found that hospitalized COVID-patients with diabetes had a 28% higher risk of dying within 30 days and were 19% more likely to receive intensive care treatment than hospitalized COVID-patients without diabetes.
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Severe hypoglycemia and hyperglycemia (ketoacidosis, hyperglycemic hyperosmolar state) are common yet potentially preventable acute complications of diabetes. Our objectives were to use national data from OptumLabs® Data Warehouse, 2011-2020, to 1) characterize trends in all-cause mortality among adults with type 1 diabetes (T1D) and type 2 diabetes (T2D) experiencing emergency department visits or hospitalizations for hypoglycemia and hyperglycemia;2) extend analyses through 2020 to assess the impact of the COVID-pandemic;and 3) examine racial/ethnic and gender disparities in subsequent mortality adjusted for relevant patient characteristics. Among 4,164 adults with T1DM experiencing hypoglycemia, 30-day and 1-year mortality increased from 0.5% to 0.9% and 4.7% to 6.1%. Among 49,931 adults with T2DM experiencing hypoglycemia, 30-day and 1-year mortality were stable at 2.1-2.0% and 16.2-16.1%. Among 4,698 adults with T1DM experiencing hyperglycemia, 30-day and 1-year mortality increased from 0.4% to 1.0% and 2.7% to 5.9%, respectively. Among 17,123 adults with T2DM experiencing hyperglycemia, 30-day and 1-year mortality increased from 2.5% to 3.0% and 11.5% to 13.1%. Table shows differences in mortality rates by age, race/ethnicity, gender. These results call for proactive engagement of high risk individuals experiencing severe hypoglycemia and hyperglycemia to reduce their risk of death.
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Racial differences at onset of type 1 diabetes (T1D) in youth during the COVID-pandemic have been documented in the US. Limited data are available in type 2 diabetes (T2D) . No data are available to our knowledge at follow up (FU) . We compared characteristics at onset and 1 year FU in white vs. black children diagnosed with diabetes mellitus (DM) in 2020 at a large pediatric academic center. A total of 276 youth (53% male, 81% white, mean age at onset 10.8±4.5 years, mean HbA1c 12.1±2.7%, 45% with BMI ≥ 85th percentile, 43% presenting in DKA) , were identified via retrospective chart review. 78% were diagnosed with T1D, 21% with T2D and 1% with MODY. Age (10.8±3.9 vs. 10±4.5 years, p=0.5) , prevalence of BMI ≥ 85thile (47 vs. 28%, p=0.12) and mean HbA1c (12.3±2.5 vs. 12.1±2.7, p=0.84) were similar in blacks vs. whites at onset of T1D. In those diagnosed with T2D, blacks compared to whites had a higher mean HbA1c (11.9±2.9 vs. 9.7±2.3%, p=0.04) as well as prevalence of DKA (26 vs. 0% respectively, p=0.02) . Characteristics at 1 year FU by race and type of DM are presented below.
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Objectives: The COVID-pandemic has presented challenges for individuals with chronic diseases in resource-limited settings. Lockdowns and restrictions have decreased access to health care and disrupted medical support. Those challenges might affect the psychological status of children and adolescents with T1D. Methods: The study was conducted with ethics approval in the Endocrinology Clinic Cipto Mangunkusumo Hospital, Jakarta, Indonesia June 2020-June 2021. Demographic background, COVID-knowledge, challenges and psychosocial problems were assesed using a questionnaire. Surveys were given in person and online. Results: There were 148 respondents (23 adolescents, 1parents, 14 relatives) . Median age was 13 (3-18) , 51% female. During the pandemic, median A1C was 8.2% and complications that occurred were frequent hyperglycemia (23%) , hypoglycemia (14%) , and ketoacidosis (8%) . Most patients used national health insurance (90%) in public hospital (80%) . Most of the respondents reported being affected by lockdowns in their area (73%) , although many could still visit healthcare facilities (44%) . Despite getting exemption for healthcare visit in lockdown period, about almost half of them felt that their check-up routines were disrupted (41%) mainly due to fear of getting infected with COVID-during visit (34%) . Many children had some psychological problem (51%) such as irritability (26%) , distress (12%) , anxiety (11%) and insomnia (10%) . As many as 37% of them needed psychological support from either health care workers or their relatives. Conclusions: The COVID-pandemic has presented new challenges for diabetes management in children and adolescents living in resource-limited settings. Patients' routine visits, access to essential diabetes care and psychological states have been affected. Given the ongoing nature of waves during the pandemic, further studies about the impact of COVID-pandemic on psychological well-being are needed.
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The impact of school day routines on glycemic control in children is unclear. We compared continuous glucose monitor (CGM) metrics for youth with type 1 diabetes during weekday school hours (8AM-3PM) between two 4-week periods before and during the COVID-pandemic, when children had transitioned to virtual school. Youth with >70% CGM wear (n=209) were included;46% male, mean±SD age 10.6±1.5 years, hemoglobin A1c 7.5±0.8%, 64% on insulin pumps. Time in range (TIR, 80-180 mg/dL) was similar during the pandemic (51.6±24.1%) compared to pre-pandemic (50.8±23.3%) . Using random coefficient multilevel linear mixed models, younger age (p=0.025) and pump use (p=0.043) predicted TIR, but not race (p=0.76) , diabetes duration (p=0.07) , body mass index (p=0.54) , or insurance status (p=0.45) . TIR pre- vs. during the pandemic varied significantly by time of day (p<0.001) . With in-person school pre-pandemic, TIR increased over school hours;with virtual school during the pandemic, TIR decreased in the morning and then remained steady (Figure) . Time above range (TAR, >180 mg/dL) had the opposite pattern. These findings suggest that in-person school can contribute to better TIR and lower TAR. Possible explanations include classroom and physical activity routines, plus school nurse support. During virtual school, continued routines are important and interventions to optimize diabetes care in school may benefit glycemic control.
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Objective: Historically marginalized groups have higher rates of poor glycemic control linked to barriers in access to care. We sought to examine whether there was a differential effect of the COVID-pandemic on loss-to-follow-up (LTFU) rates among high-risk youth with T1D based on language for care, race, and ethnicity. Methods: Retrospective cohort study of pediatric patients with T1D (HbA1c ≥9%) seen at a tertiary care diabetes clinic between 1/1/18-2/29/20 (pre-COVID period) and 3/1/20-1/31/21 (COVID period) . LTFU was tracked monthly and defined as patients not seen in the preceding 6 months. Preferred language for care, race, and ethnicity data were obtained from visit registration data. Generalized estimating equations were used to examine associations between time-periods (pre-COVID versus COVID) and LTFU rates, adjusted for patient age. In two models, separate interaction terms for (1) language for care and (2) race and ethnicity were introduced to assess for effect modification. Results: 1359 patients were included (9.5% with language other than English [LOE];33.5% from historically marginalized racial and ethnic groups) . We found a 1.27 higher odds (95% CI: 1.08, 1.49) of LTFU after the onset of the pandemic, with differential effects based on language for care. Among patients with LOE, the odds of LTFU in the COVID period was 4.14 higher (95% CI: 2.35, 7.29) compared to the pre-COVID period. LTFU rates did not significantly differ between time periods among English-speaking patients (OR 1.12 [95% CI: 0.95, 1.33]) . Patient's race and ethnicity did not modify the effect of the COVID-pandemic on LTFU rates. Conclusion: The COVID-pandemic has exacerbated LTFU rates in high-risk youth with T1D and disproportionately impacted patients whose preferred language for care is a LOE. Interventions to improve LTFU rates should include targeted efforts to reduce health disparities in access to care in this high-risk population.
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Background: Mississippi ranks second for childhood obesity prevalence (22%) above the national average of 16 % with significant racial and health disparities. Since March 2020, stay-at home orders, virtual learning, stress, and poor lifestyle may have provided a perfect setup leading to new diagnosis of diabetes and accounting for record high hospitalizations. Objective: To determine the impact of the COVID-pandemic on the rate and clinical characteristics of newly diagnosed pediatric diabetes at University of Mississippi Medical Center. Methods: Chart review and data comparison completed for patients with new-onset-diabetes between January 20-February 2020 (pre pandemic) ;and between March 2020-October 2020 (pandemic) . Results: Table 1. African Americans were disproportionately diagnosed with diabetes (64%) . Eighty percent of obese patients had type 2 diabetes with 38% presenting in DKA, 3 patients in HHS. Four patients were COVID-positive on admission. Conclusions: Our observations corroborate the steep rise in the number of new-onset type 1 and type 2 diabetes, particularly in African Americans, in a highly prevalent obese pediatric population. Additional studies are required to determine the detailed effects of SARS-CoV-2 infection and pandemic associated psychosocial, clinical and biochemical effects on development of diabetes in the pediatric population.
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Background: The COVID-pandemic accelerated adoption of telemedicine for diabetes care in 2020. We sought to describe the utilization of telemedicine across the T1DX-QI in 2021. Methods: Twenty four pediatric and nine adult clinics completed a survey about the proportion of televisits performed, center goals and processes in fall of 2021. Results: The majority of clinics reported performing between 11-25% (n=16, 48%) and 0-10% televisits (n=9, 27%) . The majority reported a pre-visit preparation workflow (n=24, 73%) , but most sites reported not having a staff member dedicated to supporting televisits (n=21, 64%) . No major differences in televisit use, goals, and processes were observed between pediatric and adult sites. For diabetes technology data downloads, the majority of clinics integrated data automatically into the EHR (n=25, 73%) . The major barriers to sustaining telemedicine practice across clinics were patient internet access, patient health disparities and access to device data (Figure 1) . Conclusion: More than one year into the pandemic the proportion of televisits performed by the T1DX-QI collaborative is modest. Clinic workflows have been implemented to support telemedicine but insufficient institutional support and technology barriers still represent an obstacle.
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Background: The COVID-pandemic and virtual care has impacted the care delivery of many health care conditions including diabetes. This study aimed to compare how patterns of care for diabetes have changed as a result of virtual care and the COVID-pandemic at a large academic ambulatory care facility in Toronto, Canada. Methods: Patients were included who had an initial diabetes visit between September 15, 20 and September 20, 2020. Fisher's exact test was used to determine differences in care patterns between visits pre and during COVID- (after March 14, 2020) . Results: Pre-COVID-19, there were 240 (72.7%) completed initial visits and 90 (27.3%) follow-up visits, including 27.5% and 36.7% for type 1 diabetes, respectively. During COVID-19, there were 235 (44.1%) initial visits and 298 (56%) follow-up visits including 29.4% and 27.2% for type 1 diabetes, respectively. Including all visits, there were more no-shows during COVID-19, 4.5% vs. 1.5%;p<0.05. Out of 330 pre-COVID-visits, all (100%) were done in-person. During COVID-19, out of 533 visits, 89.3% were done by phone, 7.5% by video, and only 3.2% in-person. Conclusion: During COVID-19, there were more follow-up diabetes visits seen compared to initial visits and more no-shows. Most diabetes visits were done by phone during COVID-19. More data is needed to understand how diabetes care delivery has changed as a result of virtual care during COVID-19.