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Identification of the Components of Frailty Using Administrative Data and Metabolite Profiling

Identification of the Components of Frailty Using Administrative Data and Metabolite Profiling
使用管理数据和代谢物分析识别虚弱的组成部分
批准号:
10657394
负责人:
Jordan Blair Strom
金额:
$17.28万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-07-01 至 2024-06-30
关键词:
AdultAdverse eventAgeAortic Valve StenosisAreaBiochemicalBiologicalBiological MarkersBioprosthesis deviceCardiologyCardiovascular DiseasesCardiovascular systemChronologyCitric Acid CycleClinicalClinical InvestigatorClinical ResearchClinical TrialsCodeCollectionConsensusDataData SourcesDecision MakingEnergy MetabolismEnvironmentEpidemiologyEtiologyFacultyFundingGoalsHealthHealthcareHeterogeneityHumanImpairmentIndividualInternal MedicineInternationalIsraelK-Series Research Career ProgramsKnowledgeLeadLinkLongevityMachine LearningMeasuresMediatingMedicalMedical centerMedicareMedicineMentorsMentorshipMethodologyOperative Surgical ProceduresOutcomeOutcomes ResearchPatient CarePatientsPersonsPhenotypePhysician ExecutivesPhysiciansPhysiologicalPopulationProceduresProspective cohortProteomicsProviderPublic Health SchoolsQuality of lifeRecoveryRegistriesResearchResearch PersonnelRiskRisk FactorsScientistSelection for TreatmentsStrokeSubgroupSyndromeTechniquesTimeTrainingTreatment outcomeUnited States National Institutes of HealthVulnerable PopulationsWorkadministrative databaseadverse event riskadverse outcomeaortic valve replacementbiomarker identificationclinical trainingcomorbidityend of lifefrailtyhealth datahealth service useheart imaginghigh riskhuman old age (65+)improvedindividual variationinsightmedical schoolsmembermetabolomicsmid-career facultyminimally invasivemolecular phenotypemortalitynew technologynovelnovel markeroptimal treatmentsparticipant enrollmentpatient oriented researchpersonalized medicinepredictive modelingprofessorprogramsprospectiverandomized, clinical trialssurgical risktreatment effecttreatment responsetrial enrollment

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中文摘要
翻译
项目摘要 候选人:Strom博士获得了哈佛医学院(HMS)的医学博士学位,并完成了临床 内科(MGH)、心脏病学(BIDMC)和非侵入性心脏成像(BIDMC)培训。 此外,他还在哈佛T.H.完成了流行病学硕士课程。Chan公共卫生学院, 2018年5月。他现在是BIDMC的一名初级教员,有75%的时间进行临床研究。 research.通过这项拟议的5年计划,Strom博士将在高级 预测建模、机器学习、面向患者的研究和代谢组学。候选人很长- 长期目标是成为R 01资助的应用成果研究领域的调查员。 环境:候选人将由罗伯特W。叶(小学导师),香港中文大学副教授 史密斯心脏病学结果研究中心主任罗伯特·E·史密斯说,盖尔斯滕 (联合导师),HMS医学教授和BIDMC心血管内科主任,Changyu Shen(联合导师),即将在HMS医学副教授和史密斯首席生物统计学家 中心叶博士拥有领先的实践改变研究和临床医生成功指导的记录 investigators. Gerszten博士是国际公认的心血管疾病分子表型专家, 疾病使用代谢组学和蛋白质组学,并指导了几个K奖和R 01资助的临床 investigators.沈博士有着长期的NIH资助记录,在评估 在心血管疾病的治疗效果,并指导了多个先前的学员。 研究:对于特定的主动脉瓣狭窄患者的最佳治疗仍然不确定。这项建议 旨在定义改变主动脉瓣置换术后风险的虚弱的临床和生物学成分 (AVR)并改变治疗效果。对于目标1-2,我们将利用Medicare数据与 美国CoreValve心脏试验,一组随机化重度主动脉瓣狭窄患者的临床试验 自膨式生物瓣膜经导管主动脉瓣置换术(TAVR)与外科主动脉瓣置换术(SAVR)。在目标1中,我们 我们将确定哪些变量与虚弱和候选虚弱代码的亲自评估相关, 预测AVR后的不良结局。在目标2中,我们将确定目标1中确定的新变量, 接受主动脉瓣置换术的个体中的异质性治疗反应。在目标3中,我们将前瞻性地招募 在BIDMC接受TAVR的患者,同时进行虚弱表型分析,以确定代谢产物是否 与长寿相关的基因与虚弱相关,并预测不良结局,与年龄无关, 合并症。这项研究将确定脆弱带来不利风险和差异的机制, AVR的治疗益处,提供可个性化治疗选择和改善患者护理的见解。
英文摘要
PROJECT SUMMARY Candidate: Dr. Strom received an MD from Harvard Medical School (HMS), and has completed clinical training in internal medicine (MGH), cardiology (BIDMC), and non-invasive cardiac imaging (BIDMC). Additionally, he completed an MSc in Epidemiology program at the Harvard T.H. Chan School of Public Health, in May, 2018. He is now a junior faculty member at BIDMC with 75% protected time to conduct clinical research. Through this proposed 5-year program, Dr. Strom will pursue additional training in advanced prediction modeling, machine learning, patient-oriented research, and metabolomics. The candidate’s long- term goal is to become an R01-funded investigator in the area of applied outcomes research. Environment: The candidate will be mentored by Robert W. Yeh (Primary Mentor), Associate Professor of Medicine at HMS and Director of the Smith Center for Outcomes Research in Cardiology, Robert E. Gerszten (Co-Mentor), Professor of Medicine at HMS and Chief of Cardiovascular Medicine at BIDMC, and Changyu Shen (Co-Mentor), upcoming Associate Professor of Medicine at HMS and Lead Biostatistician for the Smith Center. Dr. Yeh has a track record of leading practice-changing studies and successful mentorship of clinician investigators. Dr. Gerszten is an internationally recognized expert in molecular phenotyping of cardiovascular diseases using metabolomics and proteomics and has mentored several K-award and R01 funded clinical investigators. Dr. Shen has a long track record of NIH funding, expertise in evaluating heterogeneity of treatment effect in cardiovascular diseases, and has mentored multiple prior trainees. Research: The optimal therapy for a given individual with aortic stenosis remains uncertain. This proposal seeks to define the clinical and biologic components of frailty that modify risk after aortic valve replacement (AVR) and alter treatment benefit. For Aims 1-2, we will leverage the unique linkage of Medicare data to the US CoreValve Pivotal trials, a collection of clinical trials that randomized individuals with severe aortic stenosis to transcatheter AVR (TAVR) with a self-expanding bioprosthesis vs. surgical AVR (SAVR). In Aim 1, we will we will identify which variables, related to in-person assessments of frailty and candidate frailty codes, best predict adverse outcomes after AVR. In Aim 2, we will identify if novel variables identified in Aim 1, identify a heterogeneous treatment response in individuals undergoing AVR. In Aim 3, we will prospectively enroll patients undergoing TAVR at BIDMC with concurrent frailty phenotyping to identify whether metabolites associated with longevity correlate with frailty and predict adverse outcomes, independent of age and comorbidities. The research will identify the mechanisms by which frailty confers adverse risk and differential treatment benefit in AVR, providing insights that may personalize treatment selection and improve patient care.
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会议论文
Chronic Renal Insufficiency and Silent Progression of Aortic Stenosis (CRISP-AS)
Identification of the Components of Frailty Using Administrative Data and Metabolite Profiling
Identification of the Components of Frailty Using Administrative Data and Metabolite Profiling
Frailty, Aging, and Risk of Adverse Outcomes in Mitral Valve Prolapse (FAR-OUT-MVP Study)
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