Incidence and severity of new onset diabetes associated with SARS-CoV-2 infection
Incidence and severity of new onset diabetes associated with SARS-CoV-2 infection
批准号:
10632720
负责人:
JANE E REUSCH
金额:
$40.6万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-09-15 至 2024-08-31
关键词:
2019-nCoVAcuteAddressAdrenal Cortex HormonesAdultAffectAutoimmuneBiochemical MarkersBody mass indexCOVID-19COVID-19 impactCOVID-19 pandemicCOVID-19 patientCOVID-19 severityCaringDataData AnalyticsData SetDiabetes MellitusDiabetic KetoacidosisDiagnosisDiseaseDisease remissionDyslipidemiasEndotheliumGeographyGlucoseGlycosylated hemoglobin AGoalsHealth Insurance Portability and Accountability ActHealthcareHypertensionIatrogenesisIncidenceInfectionInflammationInflammatoryInjuryInpatientsInsulinInsulin ResistanceLipidsLongterm Follow-upMeasurementMedical InformaticsNatural ImmunityOutcomePatient riskPatient-Focused OutcomesPatientsPharmaceutical PreparationsPopulationPositioning AttributePrognosisPublishingRecording of previous eventsResearchRiskSARS-CoV-2 infectionSeveritiesSiteStructure of beta Cell of isletTestingTimeUnited States National Institutes of HealthUpper Respiratory InfectionsVaccinationVariantVirusWorkanalytic epidemiologybaseclinical phenotypeclinically significantcohortcomorbiditycoronavirus diseasedata enclavedemographicsdiabetogenicepidemiology studyglycemic controlhealth care economicshigh riskindexingmalemultidisciplinarypandemic diseasepediatric patientspost SARS-CoV-2 infectionresponsesocial health determinantsstatisticstheories
中文摘要
我们
的
和
我将使用国家新冠肺炎队列协作组织(N3 C)的数据进行流行病学研究
糖尿病发病率和发病时的严重程度及其与COVID-19大流行的潜在关联
致病病毒SARS-CoV-2“N3 C数据飞地是最大的公开可用的HIPAA有限
美国历史上的数据集,来自72个贡献站点的1300多万患者。由于其规模、人口和
由于住院和门诊数据的地理多样性,N3 C非常适合实现我们的研究目标。
假设:COVID-19感染与糖尿病发病率增加和严重
疾病表现,并且存在增加患者风险的患者和感染相关因素,
影响长期成果。具体目标1:检验COVID-19感染和感染-
相关因素与糖尿病发病率的增加和诊断时的严重表现有关。
我们将研究COVID-19和感染相关因素的影响,包括COVID-19疾病的严重程度,
皮质类固醇治疗、生化标志物和病毒变体(基于大流行的时间或直接
测量),在成人和儿科患者中。我们将分析发生糖尿病的时间以及
COVID-19感染患者的感染相关因素与急性上呼吸道感染的匹配对照相比
呼吸道感染(AURI)。具体目标2:检验COVID-19感染和患者-
相关因素与糖尿病发病率的增加和诊断时的严重表现有关。
我们将探讨患者相关因素的影响,包括人口统计学、BMI、HbA 1c和血脂,
COVID-19、合并症(例如,血脂异常、高血压、自身免疫性/炎症性疾病)、疫苗接种
糖尿病和严重疾病发病率、药物使用和社会健康决定因素(SDOH)
COVID-19成人和儿童患者以及匹配的急性上呼吸道疾病对照组的临床表现
感染(AURI)。具体目标3:检验COVID-19后发生糖尿病的患者
与未感染COVID-19的人相比,长期结果会更差。我们将比较
在索引日期后90天内诊断为偶发糖尿病的成人和儿童患者的结局,
既往COVID-19感染与AURI的匹配对照相比。12-18个月的长期结果将
包括糖尿病缓解、血糖控制和用胰岛素和其它降糖药物治疗。
影响:NIH支持的N3 C数据飞地,其人口和地理多样性,被创建
正是为了解决这一流行病的长期后果。这些研究将1。树立和
表征伴随COVID-19感染的糖尿病的发病率和严重程度增加; 2.阐明感染-和
与糖尿病事件和诊断时的严重疾病表现相关的患者相关因素,以及3.
在具有全国代表性的人群中评价新发糖尿病患者的长期结局。
英文摘要
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.
期刊论文(0)
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