Incidence and severity of new onset diabetes associated with SARS-CoV-2 infection

我们 的 和 将使用国家COVID队列合作组织(N3C)的数据来进行流行病学研究 发病时糖尿病的发病率和严重程度及其与新冠肺炎大流行的潜在关联 致病病毒SARS-CoV-2“N3C数据飞地是最大的公开可用的HIPAA-LIMITED 美国历史上的数据集，来自72个贡献站点的1300多万名患者。由于其规模、人口统计和 由于住院患者和门诊数据的地理多样性，N3C非常适合我们的研究目标。 假设：新冠肺炎感染与糖尿病和重症糖尿病的发病率增加有关 疾病表现，以及与患者和感染相关的因素会增加患者风险和 影响长期结果。具体目标1：检验新冠肺炎感染和感染- 相关因素与糖尿病发病率的增加和确诊时的严重症状有关。 我们将检查新冠肺炎的效果和感染相关因素，包括新冠肺炎疾病的严重程度， 皮质类固醇治疗、生化标志物和病毒变异(根据大流行的时间或直接 测量)，在成人和儿童患者中。我们将分析发生糖尿病的时间和与 新冠肺炎感染患者与对照组急性上呼吸道感染相关因素的比较 呼吸道感染(AURI)。具体目标2：检验新冠肺炎感染和患者- 相关因素与糖尿病发病率的增加和确诊时的严重症状有关。 我们将探讨患者相关因素的影响，包括人口统计学、BMI、HbA1c和血脂 新冠肺炎、并存疾病(如血脂异常、高血压、自身免疫/炎症性疾病)、疫苗接种 糖尿病和严重疾病的状况、用药和健康的社会决定因素(SDOH) 成人和儿童新冠肺炎患者和匹配的急性上呼吸道疾病对照患者的临床表现 感染(AURI)。具体目标3：检验新冠肺炎后发生糖尿病患者的假设 与那些没有感染新冠肺炎的人相比，长期结果会更差。我们会比较一下 成人和儿童糖尿病患者在90天内被诊断为糖尿病患者的预后 既往新冠肺炎感染与有尿路感染的匹配对照组的比较。12-18个月的长期结果将 包括糖尿病缓解、血糖控制以及胰岛素和其他降血糖药物的治疗。 影响：NIH支持的N3C数据飞地凭借其人口和地理多样性而创建 这恰恰是为了应对大流行的长期后果。拟议的研究将1.建立和 描述新冠肺炎感染增加的糖尿病发病率和严重程度；2.阐明感染-和 与糖尿病发病和诊断时出现的严重疾病相关的患者相关因素。 在全国有代表性的人群中评估糖尿病患者的长期预后。

We of and will use data from t he National COVID Cohort Collaborative (N3C) to “conduct an epidemiologic study diabetes incidence and severity at onset and its potential association with the COVID-19 pandemic the causative virus SARS-CoV-2”The N3C data enclave is the largest publicly available HIPAA-limited data set in U.S. history, over 13 million patients from 72 contributing sites. Due to its scale, demographic and geographic diversity of inpatient and ambulatory data, N3C is uniquely suited to address our research objectives. Hypothesis: COVID-19 infection is associated with an increased incidence of diabetes and severe disease presentation, and there are patient- and infection-related factors that increase patient risk and impact long-term outcomes. Specific Aim 1: Test the hypothesis that COVID-19 infection and infection- related factors are associated with increased incidence of diabetes and severe presentation at diagnosis. We will examine the effect of COVID-19 and infection-related factors, including COVID-19 disease severity, corticosteroid treatment, biochemical markers and virus variant (based on timing in the pandemic or direct measurement), in adult and pediatric patients. We will analyze time to incident diabetes and association of infection-related factors in patients with COVID-19 infection compared to matched controls with acute upper respiratory infection (AURI). Specific Aim 2: Test the hypothesis that COVID-19 infection and patient- related factors are associated with increased incidence of diabetes and severe presentation at diagnosis. We will explore the effect of patient-related factors, including demographics, BMI, HbA1c and lipids prior to COVID-19, comorbidities (e.g., dyslipidemia, hypertension, autoimmune/inflammatory conditions), vaccination status, medication use and social determinants of health (SDOH) on incident diabetes and severe disease presentation in adult and pediatric patients with COVID-19 and matched controls with acute upper respiratory infection (AURI). Specific Aim 3: Test the hypothesis that patients with incident diabetes after COVID-19 will have worse long-term outcomes compared to those without COVID-19 infection. We will compare outcomes in adult and pediatric patients with incident diabetes diagnosed within 90 days of their index date with prior COVID-19 infection compared to matched controls with AURI. Long-term outcomes over 12-18 months will include diabetes remission, glycemic control and treatment with insulin and other glucose lowering medications. Impact: The NIH-supported N3C Data Enclave, with its demographic and geographic diversity, was created precisely to address the long-term consequences of the pandemic. The proposed studies will 1. Establish and characterize increased incidence and severity of diabetes with COVID-19 infection; 2. Elucidate infection- and patient-related factors associated with incident diabetes and severe disease presentation at diagnosis, and 3. Evaluate the long-term outcomes of patients with incident diabetes in a nationally representative population.