RESUMEN
AIMS: Continuous glucose monitoring (CGM) metrics can assist diabetes management. Consensus statements recommend > 70 % time in range (TIR) and ≤ 36 % glucose coefficient of variation (CV). However, how these targets perform in clinical practice is unknown. This retrospective, longitudinal cohort study analyzed relationships between TIR, CV, glycated hemoglobin (HbA1c), and hypoglycemia in a real-world setting. METHODS: Data of 542 adults with type 1 diabetes who used CGM (January 2014-July 2020) were analyzed. Associations between TIR and HbA1c at the same and subsequent visits, incidence rate ratios (IRRs) for hypoglycemia at different CVs, and number of hypoglycemic events at cross-sections of HbA1c and CV were estimated by regression. RESULTS: TIR was inversely related to HbA1c; for every 10 % increase in TIR, HbA1c was significantly reduced by 0.34 % (4 mmol/mol) and 0.20 % (2 mmol/mol) at the same and subsequent visits, respectively. Level 2 hypoglycemia was significantly reduced at CV < 30 %, 30-33 %, 33.1-36 %, and 36.1-40 %: adjusted IRRs vs CV ≥ 40.1 % of 0.14, 0.28, 0.32, and 0.50, respectively. Hypoglycemic events were reduced at lower CV across HbA1c levels and at higher HbA1c across CV levels. CONCLUSION: This study quantifies HbA1c improvements with increased TIR and hypoglycemia reductions with improved CV in clinical practice.
Asunto(s)
Automonitorización de la Glucosa Sanguínea , Glucemia , Diabetes Mellitus Tipo 1 , Hemoglobina Glucada , Hipoglucemia , Humanos , Diabetes Mellitus Tipo 1/sangre , Diabetes Mellitus Tipo 1/tratamiento farmacológico , Femenino , Masculino , Estudios Retrospectivos , Adulto , Hemoglobina Glucada/análisis , Hemoglobina Glucada/metabolismo , Automonitorización de la Glucosa Sanguínea/métodos , Hipoglucemia/sangre , Hipoglucemia/epidemiología , Glucemia/análisis , Glucemia/metabolismo , Persona de Mediana Edad , Estudios Longitudinales , Hipoglucemiantes/uso terapéutico , Monitoreo Continuo de GlucosaRESUMEN
AIMS: This study aimed to provide a global insight into initiatives in type 1 diabetes care driven by the COVID-19 pandemic and associations with glycemic outcomes. METHODS: An online questionnaire regarding diabetes care before and during the pandemic was sent to all centers (n = 97, 66,985 youth with type 1 diabetes) active in the SWEET registry. Eighty-two responded, and 70 (42,798 youth with type 1 diabetes) had available data (from individuals with type 1 diabetes duration >3 months, aged ≤21 years) for all 4 years from 2018 to 2021. Statistical models were adjusted, among others, for technology use. RESULTS: Sixty-five centers provided telemedicine during COVID-19. Among those centers naive to telemedicine before the pandemic (n = 22), four continued only face-to-face visits. Centers that transitioned partially to telemedicine (n = 32) showed a steady increase in HbA1c between 2018 and 2021 (p < 0.001). Those that transitioned mainly to telemedicine (n = 33 %) improved HbA1c in 2021 compared to 2018 (p < 0.001). CONCLUSIONS: Changes to models of care delivery driven by the pandemic showed significant associations with HbA1c shortly after the pandemic outbreak and 2 years of follow-up. The association appeared independent of the concomitant increase in technology use among youth with type 1 diabetes.
Asunto(s)
COVID-19 , Diabetes Mellitus Tipo 1 , Telemedicina , Adolescente , Humanos , Niño , COVID-19/epidemiología , Diabetes Mellitus Tipo 1/epidemiología , Diabetes Mellitus Tipo 1/terapia , Pandemias , Hemoglobina Glucada , Sistema de RegistrosRESUMEN
CONTEXT: COVID-19 morbidity and mortality are increased in type 1 diabetes (T1D), but few data focus on age-based outcomes. OBJECTIVE: This work aimed to quantify the risk for COVID-19-related hospitalization and adverse outcomes by age in people with T1D. METHODS: For this observational, multisite, cross-sectional study of patients with T1D and laboratory-confirmed COVID-19 from 56 clinical sites in the United States, data were collected from April 2020 to March 2021. The distribution of patient factors and outcomes across age groups (0-18, 19-40, and >â 40 years) was examined. Descriptive statistics were used to describe the study population, and multivariate logistic regression models were used to analyze the relationship between age, adverse outcomes, and hospitalization. The main outcome measure was hospitalization for COVID-19. RESULTS: A total of 767 patients were analyzed. Fifty-four percent (nâ =â 415) were aged 0 to 18 years, 32% (nâ =â 247) were aged 19 to 40 years, and 14% (nâ =â 105) were older than 40 years. A total of 170 patients were hospitalized, and 5 patients died. Compared to the 0- to 18-years age group, those older than 40 years had an adjusted odds ratio of 4.2 (95% CI, 2.28-7.83) for hospitalization after adjustment for sex, glycated hemoglobin A1c, race, insurance type, and comorbidities. CONCLUSION: Age older than 40 years is a risk factor for patients with T1D and COVID-19, with children and younger adults experiencing milder disease and better prognosis. This indicates a need for age-tailored treatments, immunization, and clinical management of individuals affected by T1D.