BEST-VIVA Registry (vCLI)
BEST-VIVA 注册表 (vCLI)
基本信息
- 批准号:9913570
- 负责人:
- 金额:$ 77.04万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-04-15 至 2022-03-31
- 项目状态:已结题
- 来源:
- 关键词:AdherenceAdoptionAffectAmericanAmerican Heart AssociationAnatomyAnkleBlood VesselsBlood flowCardiacCardiovascular DiseasesCardiovascular systemCaringChronic Kidney FailureClinicalCompanionsComparative Effectiveness ResearchConsensusCritical CareDataDevicesDiabetes MellitusDiabetic MicroangiopathiesDiseaseDisease-Free SurvivalEnrollmentEventFundingFutureGenderGeographic FactorGeographyGrantGuidelinesHealth Care CostsHealth StatusHealthcareHealthcare SystemsHeartHospitalsHyperlipidemiaHypertensionImageIncidenceInstitute of Medicine (U.S.)InterventionKidneyKneeLegLesionLimb structureLocationLower ExtremityLungMedicineMethodsModelingNational Heart, Lung, and Blood InstituteNecrosisObservational StudyOperative Surgical ProceduresOutcomePain in lower limbPatient CarePatient Outcomes AssessmentsPatientsPatternPeripheral arterial diseasePharmaceutical PreparationsPhysiciansPrevalenceProceduresQuality of lifeRegistriesReportingResearch PersonnelResourcesRestRiskSiteSourceSpecialistSpeedSubgroupSurgeonSurvival RateTechniquesTissuesTreatment CostTreatment outcomeUlcerUnited StatesUnited States National Institutes of HealthVariantWomanWorkbaseclinical practiceclinical riskcomorbiditycomparative effectivenesscostcost effectivenesscritical limb Ischemiademographicsdesignfoothealth care qualityimprovedinterestlimb amputationminimally invasivemortalityoptimal treatmentspatient populationpatient subsetspopulation basedpublic-private partnershipradiologistrestorationtreatment strategyworking groupwound carewound healing
项目摘要
Project Summary / Abstract
Critical limb ischemia (CLI), a lack of blood flow to the leg characterized by leg pain at rest or by tissue loss,
affects approximately 2 million Americans and is characterized by increased rates of cardiovascular and limb
complications. Management of CLI is rapidly evolving, with the advent of minimally invasive techniques to
restore blood flow and advances in wound care. However, there is little consensus regarding optimal
treatment. The ongoing NIH funded BEST-CLI is designed to assess the comparative effectiveness of
minimally invasive versus full surgical restoration of blood flow in CLI, however, little is known about current
nationwide practice patterns, outcomes, quality of life, and healthcare resource utilization in CLI. Additionally,
the BEST-CLI trial will enroll a selected patient population that may not be fully representative of “real world”
CLI patients. As a result, in conjunction with the BEST-CLI investigators and BEST-CLI Trial, we
propose the companion BEST-VIVA registry (vCLI) to investigate the following aims: 1) Describe the
baseline demographics, comorbidities, and treatment strategies of consecutive patients excluded from the
BEST-CLI Trial and included in the vCLI registry, with a focus on variations in care 2) Describe the clinical
outcomes – specifically major adverse limb events (MALE) free survival, wound healing, and major adverse
cardiovascular events (MACE) - by treatment strategy in CLI patients, with a focus on causes of outcome
variation within treatment strategy 3) Describe healthcare related quality of life and healthcare costs, by
treatment strategy in the vCLI registry, with a focus on causes of variation in quality of life and costs.
Methods: The vCLI registry will be funded by a unique public / private partnership with governance from both
vCLI primary investigators and BEST-CLI primary investigators. For Aim 1, Multilevel multivariate regression
will be used to identify patient, physician/hospital, and geographic factors associated with variations in
treatment strategies. For Aim 2, Kaplan Meier and cumulative incidence estimates of limb and cardiovascular
outcomes will be stratified by treatment strategy and other subgroups of interest. The impact of diabetes and
CKD will be quantified by multivariable modeling and clinical risk prediction scores will be developed separately
for each treatment strategy. For Aim 3, quality of life, costs, and cost effectiveness will be described for each
treatment strategy and sources of variation within each treatment strategy will be identified via multivariable
regression. Impact: The results of the grant will help to illuminate current practices and outcomes in the care
of CLI. Data generated regarding patient demographics, variations in clinical outcomes, and variations in costs
/ cost effectiveness will serve to 1) identify targets for future healthcare systems interventions to improve
adherence to guideline recommended care and 2) provide context and generalizability for the findings of the
BEST-CLI Trial and 3) identify specific healthcare systems targets to help speed the adoption of BEST-CLI trial
findings into clinical practice.
项目摘要 /摘要
临界肢体缺血(CLI),缺乏血液流向腿部的血液流动,其特征是腿部疼痛或组织损失,
影响大约200万美国人,其特征是心血管和肢体的率提高
并发症。 CLI的管理正在迅速发展,随着微创技术的冒险
恢复血流和伤口护理的进展。但是,关于最佳的共识几乎没有
治疗。正在进行的NIH资助的最佳CLI旨在评估比较有效性
然而,CLI中血流的最小侵入性与完全手术恢复,对电流知之甚少
CLI中的全国实践模式,成果,生活质量和医疗资源利用。此外,
最佳CLI试验将招募可能无法完全代表“现实世界”的选定患者人群
CLI患者。结果,与最佳CLI研究者和最佳CLI试验结合在一起,我们
提案伴侣最佳视觉注册表(VCLI)调查以下目的:1)描述
连续患者的基线人口统计,合并症和治疗策略排除在外
最佳CLI试验并包括在VCLI注册表中,重点是护理的变化2)描述临床
结果 - 特别是主要的不良肢体事件(男性)自由生存,伤口愈合和主要广告
心血管事件(MACE) - 通过CLI患者的治疗策略,重点是结果
治疗策略内的变化3)描述与医疗保健相关的生活质量和医疗保健成本,
VCLI注册表中的治疗策略,重点是导致生活质量和成本差异的原因。
方法:VCLI注册表将由独特的公共 /私人合作伙伴关系以及两者的治理资助
VCLI主要研究人员和最佳CLI主要研究人员。对于AIM 1,多级多元回归
将用于识别患者,身体/医院以及与变化相关的地理因素
治疗策略。对于AIM 2,Kaplan Meier和肢体和心血管的累积事件估计值
结果将按照治疗策略和其他感兴趣的亚组进行分层。糖尿病和
CKD将通过多变量建模来量化,临床风险预测分数将分别开发
对于每个治疗策略。对于AIM 3,将描述每个人的生活质量,成本和成本效益
治疗策略和每个治疗策略内的变异来源将通过多变量确定
回归。影响:赠款的结果将有助于阐明当前的做法和护理的结果
CLI。生成有关患者人口统计学,临床结果差异和成本变化的数据
/成本有效性将有助于1)确定未来医疗保健系统干预措施的目标
遵守指南建议的护理和2)为调查结果提供背景和普遍性
最佳CLI试验和3)确定特定的医疗保健系统目标,以帮助加速最佳CLI试验
发现临床实践。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Manesh R Patel其他文献
1040-69 The effect of state mandated continuing medical education on the use of proven therapies in patients with an acute myocardial infarction
- DOI:
10.1016/s0735-1097(04)91695-6 - 发表时间:
2004-03-03 - 期刊:
- 影响因子:
- 作者:
Manesh R Patel;Trip J Meine;Jasmina Radeva;Lesley Curtis;Sunil V Rao;Kevin J Schulman;James Jollis - 通讯作者:
James Jollis
1077-76 Holiday heart: Decreased use of evidence-based therapies in patients with acute myocardial infarction admitted during holiday weeks
- DOI:
10.1016/s0735-1097(04)91719-6 - 发表时间:
2004-03-03 - 期刊:
- 影响因子:
- 作者:
Trip J Meine;Manesh R Patel;Venita DePuy;Lesley Curtis;Sunil V Rao;Kevin J Schulman;James G Jollis - 通讯作者:
James G Jollis
Prognostic Value of Coronary CT Angiography-derived Fractional Flow Reserve on 3-year Outcomes in Patients with Stable Angina.
冠状动脉 CT 血管造影得出的血流储备分数对稳定型心绞痛患者 3 年结果的预后价值。
- DOI:
10.1148/radiol.230524 - 发表时间:
2023 - 期刊:
- 影响因子:19.7
- 作者:
Kristian T Madsen;B. Nørgaard;Kristian A. Øvrehus;J. M. Jensen;Erik Parner;E. L. Grove;T. Fairbairn;Koen Nieman;Manesh R Patel;Campbell Rogers;S. Mullen;H. Mickley;A. Rohold;H. Bøtker;J. Leipsic;Niels P R Sand - 通讯作者:
Niels P R Sand
University of Southern Denmark Real-world clinical utility and impact on clinical decision-making of coronary computed tomography angiography-derived fractional flow reserve Lessons from the ADVANCE Registry
南丹麦大学 冠状动脉计算机断层扫描血管造影衍生的血流储备分数的真实临床效用及其对临床决策的影响 ADVANCE 注册中心的经验教训
- DOI:
- 发表时间:
2018 - 期刊:
- 影响因子:0
- 作者:
T. Fairbairn;Koen Nieman;Takashi Akasaka;B. Nørgaard;Daniel S Berman;G. Raff;L. Hurwitz;G. Pontone;Tomohiro Kawasaki;Niels P R Sand;J. M. Jensen;Tetsuya Amano;M. Poon;Kristian A. Øvrehus;J. Sonck;M. Rabbat;S. Mullen;B. Bruyne;Campbell Rogers;H. Matsuo;Jeroen J. Bax;J. Leipsic;Manesh R Patel - 通讯作者:
Manesh R Patel
1118-102 Baseline white blood cell count and interleukin-6 levels provide complementary prognostic information in acute myocardial infarction: Results from the CARDINAL trial
- DOI:
10.1016/s0735-1097(04)91234-x - 发表时间:
2004-03-03 - 期刊:
- 影响因子:
- 作者:
Manesh R Patel;Kenneth W Mahaffey;Paul W Armstrong;W.Douglas Weaver;Gudaye Tasissa;Judith S Hochman;Thomas G Todaro;Kevin J Malloy;Thomas H Parish;Scottt Rollins;Pierre Theroux;Wiltold Ruzyllo;Jose C Nicolau;Christopher B Granger - 通讯作者:
Christopher B Granger
Manesh R Patel的其他文献
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{{ truncateString('Manesh R Patel', 18)}}的其他基金
Solving Sepsis: Early Identification and Prompt Management Using Machine Learning
解决脓毒症:利用机器学习进行早期识别和及时管理
- 批准号:
10623375 - 财政年份:2022
- 资助金额:
$ 77.04万 - 项目类别:
Solving Sepsis: Early Identification and Prompt Management Using Machine Learning
解决脓毒症:利用机器学习进行早期识别和及时管理
- 批准号:
10384254 - 财政年份:2022
- 资助金额:
$ 77.04万 - 项目类别:
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