Investigation of Heart and Vascular Outcomes in Older Veterans

老年退伍军人心脏和血管结局的调查

• 批准号: 10618301
• 负责人: Kelly Cho
• 金额: --
• 依托单位: VETERANS HEALTH ADMINISTRATION
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-04-01 至 2026-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10618301
• 关键词: Adult; Affect; Age; Age Factors; Age Years; Alcohol consumption; Algorithms; Ambulatory Care; American; American Heart Association; Aortic Valve Stenosis; Assessment tool; Atherosclerosis; Atrial Fibrillation; Biological Assay; Biological Markers; Black Populations; Blood; Blood Cells; Blood Pressure; Blood Vessels; Body mass index; Calendar; Cardiology; Cardiovascular Diseases; Cardiovascular system; Cause of Death; Cessation of life; Chronic Disease; Chronic Kidney Failure; Classification; Code; Complex; County; Data; Data Sources; Databases; Development; Diabetes Mellitus; Diagnosis; Diagnostic; Disease; Disease Outcome; EFRAC; Elderly; Electronic Health Record; Equation; Erythrocyte Indices; Ethnic Origin; Evaluation; Event; Formulation; Funding; Glomerular Filtration Rate; Glucose; Glycosylated hemoglobin A; Health care facility; Heart; Heart Diseases; Heart failure; Hemoglobin; High Density Lipoprotein Cholesterol; High Density Lipoproteins; Hispanic Populations; Hospitalization; ICD-9; Incidence; Insurance; Investigation; LDL Cholesterol Lipoproteins; Laboratories; Length of Stay; Leukocytes; Link; Lipids; Maps; Measurement; Measures; Mediation; Medical; Modeling; Modernization; Myocardial Infarction; Non-Insulin-Dependent Diabetes Mellitus; Obstructive Sleep Apnea; Outcome; Outpatients; Pharmaceutical Preparations; Phenotype; Population; Preventive; Preventive therapy; Productivity; Prognosis; Progress Reports; Publishing; Race; Recurrence; Renal function; Reporting; Research; Research Personnel; Risk; Risk Assessment; Risk Estimate; Risk Factors; Role; Serum Albumin; Stroke; Testing; Thyrotropin; Time; United States; United States Centers for Medicare and Medicaid Services; United States Department of Veterans Affairs; Validation; Vascular Diseases; Veterans; Veterans Health Administration; Visit; Visualization; White Blood Cell Count procedure; alcohol use disorder; aortic valve replacement; cardiovascular disorder risk; cardiovascular risk factor; cigarette smoking; cohort; college; data curation; data modeling; disease prognosis; experience; follow-up; frailty; hospital laboratories; hospital readmission; indexing; innovation; interest; lifestyle factors; lipoprotein cholesterol; male; mortality; multimodality; novel; prediction algorithm; preservation; prospective; risk prediction; sex; stroke risk; suburb; venous thromboembolism; virtual

The objective of this project is to utilize a longitudinal, VA national cardiovascular disease virtual cohort to investigate traditional, and [new] risk factors (RFs), for Heart Failure (HF), Atrial Fibrillation (AF), and stroke among United States Veterans ≥ 65. This cohort will consist of contemporary and comprehensive electronic health record (EHR) data and will include continued curation and validation of complex phenotypes using innovative analytics. [The specific aims of this research in older Veterans are to: 1) Assess determinants of HF risk and prognosis after HF diagnosis in a VA Healthcare facility, 2), Assess determinants of AF risk and prognosis and 3) Assess determinants of Stroke risk and prognosis.] [During the previous funding cycle, we leveraged the VA’s large scale national longitudinal EHR data, linked to additional data sources including the Centers for Medicare and Medicaid Services (CMS) and the National Death Index (NDI) to create a comprehensive cardiovascular database. Data curation for traditional RFs, ASCVD preventive therapies, and several ASCVD outcomes was also completed in the previous funding cycle. Our new proposal will include continued data curation to include novel RFs, such as red cell indices, white blood cell indices, obstructive sleep apnea, frailty, alcohol intake, aortic stenosis, medication use, lifestyle factors, and blood measures [estimated glomerular filtration rate (eGFR), serum albumin]. We will achieve this by employing high-throughput probabilistic phenotyping and multimodal and network data modeling. Outcomes and risk factors will be evaluated over time where appropriate.] Electronic health record (EHR) data will be used to identify a baseline index date for Veterans based on an outpatient VAMC visit at which time the Veteran had blood assayed for traditional lipids. Information from the baseline and follow up visits will be obtained with database programming and will include: age, sex, systolic BP, diabetes status, cholesterol, HDL-C, TG, and CVD preventive medications. Filtering algorithms will be used for laboratory measures across the different hospital laboratories, as has already been undertaken by this research team. Similarly, BMI, glucose and hemoglobin A1c (HbA1c) measurements, and vascular disease ICD-9/10 codes will be added. [Incidence and prognosis of HF, AF, and stroke will assess the role of established and novel risk profiles. Outcomes to be analyzed include myocardial infarction, stroke, cardiovascular mortality, and all-cause mortality. For HF we will also examine HF hospital admissions and HF re-admissions within 30 days of diagnosis. We will compare currently published algorithms for the three conditions where appropriate and compare the results to our own developed regression models that include novel RFs using mediation analyses and reclassification strategies where appropriate. We will also report county- specific mapping of outcomes.]

该项目的目标是利用纵向的 VA 国家心血管疾病虚拟队列 调查心力衰竭 (HF)、心房颤动 (AF) 和中风的传统和[新]危险因素 (RF) 美国退伍军人中 ≥ 65 岁。该群体将包括当代和综合电子 健康记录（EHR）数据，并将包括使用复杂表型的持续管理和验证 [这项针对老年退伍军人的研究的具体目标是：1) 评估心力衰竭的决定因素。 在 VA 医疗机构诊断出 HF 后的风险和预后，2)、评估 AF 风险的决定因素和 预后和 3) 评估中风风险和预后的决定因素。] [在上一个资助周期中，我们利用了 VA 的大规模全国纵向 EHR 数据， 链接到其他数据源，包括医疗保险和医疗补助服务中心 (CMS) 以及 国家死亡指数 (NDI) 为传统的心血管数据创建一个全面的数据库。 RF、ASCVD 预防性治疗和多项 ASCVD 成果也在之前的资助中完成 我们的新提案将包括持续的数据管理，以包括新的 RF，例如红细胞指数、 白细胞指数、阻塞性睡眠呼吸暂停、虚弱、酒精摄入、主动脉瓣狭窄、药物使用、生活方式 因素和血液测量[估计肾小球滤过率（eGFR）、血清白蛋白]我们将实现这一目标。 通过采用高通量概率表型分析以及多模式和网络数据建模。 风险因素将在适当的情况下随着时间的推移进行评估。] 电子健康记录 (EHR) 数据将用于确定退伍军人的基准指数日期 VAMC 门诊就诊，当时退伍军人对血液进行了传统血脂信息检测。 基线和后续访问将通过数据库编程获得，包括：年龄、性别、收缩压 血压、糖尿病状况、胆固醇、HDL-C、TG 和 CVD 预防药物将成为过滤算法。 用于不同医院实验室的实验室测量，正如本中心已经采取的那样 同样，BMI、葡萄糖和糖化血红蛋白 (HbA1c) 测量以及血管疾病。 将添加 ICD-9/10 代码。 [心力衰竭、房颤和卒中的发病率和预后将评估既定风险和新风险的作用 待分析的结果包括心肌梗塞、中风、心血管死亡率和全因死亡率。 对于心衰死亡率，我们还将检查心衰入院情况和心衰发生后 30 天内的再入院情况。 我们将在适当的情况下比较当前发布的三种情况的算法。 将结果与我们自己开发的回归模型进行比较，其中包括使用中介分析的新颖 RF 以及适当时的重新分类策略。]