Jeremy Provance

ORCID: 0000-0002-2734-4634
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About
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Research Areas
  • Peripheral Artery Disease Management
  • Diagnosis and Treatment of Venous Diseases
  • Cerebrovascular and Carotid Artery Diseases
  • Diabetic Foot Ulcer Assessment and Management
  • Health Systems, Economic Evaluations, Quality of Life
  • Antiplatelet Therapy and Cardiovascular Diseases
  • Venous Thromboembolism Diagnosis and Management
  • RNA modifications and cancer
  • Pharmaceutical industry and healthcare
  • Head and Neck Cancer Studies
  • Radiomics and Machine Learning in Medical Imaging
  • Epigenetics and DNA Methylation
  • Cardiac Health and Mental Health
  • Stroke Rehabilitation and Recovery
  • Lymphatic System and Diseases
  • Fibromyalgia and Chronic Fatigue Syndrome Research
  • Musculoskeletal pain and rehabilitation
  • Diversity and Career in Medicine
  • Educational Games and Gamification
  • Cancer Genomics and Diagnostics
  • Cardiac pacing and defibrillation studies
  • Coronary Interventions and Diagnostics
  • Patient-Provider Communication in Healthcare
  • Heart Rate Variability and Autonomic Control
  • Biomedical Ethics and Regulation

Yale University
2021-2023

University of Missouri–Kansas City
2017-2021

Saint Luke's Hospital
2019-2020

<h3>Importance</h3> Identifying modifiable risk factors, such as stress, that could inform the design of peripheral artery disease (PAD) management strategies is critical for reducing mortality. Few studies have examined association self-perceived stress with outcomes in patients PAD. <h3>Objective</h3> To examine high levels mortality <h3>Design, Setting, and Participants</h3> This cohort study analyzed data from registry Patient-Centered Outcomes Related to Treatment Practices Peripheral...

10.1001/jamanetworkopen.2020.8741 article EN cc-by-nc-nd JAMA Network Open 2020-06-23

Background: Shared medical decision making requires patients’ understanding of their disease and its treatment options. Peripheral artery (PAD) is a condition for which preference-sensitive treatments are available, but little known about knowledge preferences as it relates to specific goals. Methods: In prospective, multicenter registry that involved patients with PAD experiencing claudication, the PORTRAIT Knowledge Preferences Survey was administered at 1 year. It asks questions choices,...

10.1177/1358863x231181613 article EN Vascular Medicine 2023-08-28

Critical limb ischemia (CLI), the most severe form of peripheral artery disease, is associated with pain, poor wound healing, high rates amputation, and mortality (>20% at 1 year). Little known about processes care, patients' preferences, or outcomes, as seen from perspectives. The SCOPE-CLI study was co-designed patients to holistically document patient characteristics, treatment patterns patient-centered outcomes for CLI. This 11-center prospective observational registry will enroll...

10.1016/j.ijcha.2022.100971 article EN cc-by-nc-nd IJC Heart & Vasculature 2022-02-12

Guideline-directed medical therapy (GDMT) is imperative to improve cardiovascular and limb outcomes for patients with critical ischemia (CLI), especially amongst those at highest risk poor outcomes, including comorbid chronic kidney disease (CKD). Our objective was examine GDMT prescription rates their variation across individual sites CLI undergoing peripheral vascular interventions (PVIs), by CKD status.Patients who underwent PVI (October 2016-April 2019) were included from the Vascular...

10.1159/000519484 article EN American Journal of Nephrology 2021-01-01

Introduction: Patients with critical limb ischemia (CLI) can undergo endovascular peripheral vascular intervention (PVI) to restore blood flow and decrease risk of amputation. As a potential indicator quality for CLI care, we sought describe 30-day major amputation rates following PVI. We also examined rate variability, patient-level site-level factors predicting amputations, using national electronic health record (EHR) database. Methods: Using the Cerner Health Facts de-identified EHR...

10.1177/1358863x221098097 article EN Vascular Medicine 2022-05-23

Abstract Background: Plasma-based tests to quantify circulating cell-free DNA cancer signal have emerged as viable applications across the continuum, from early detection optimal disease management. Here we demonstrate feasibility of a tissue-agnostic, genome-wide methylome enrichment platform based on methylated immunoprecipitation and high throughput sequencing (cfMEDIP-seq) for detection, quantification, prognostication in head neck (HNC). Methods: Pre-treatment plasma samples individuals...

10.1158/1538-7445.am2024-2427 article EN Cancer Research 2024-03-22

3009 Background: Plasma cell-free DNA (cfDNA) tests have emerged as a promising approach for cancer management. cfDNA methylome approaches are well-suited molecular residual disease (MRD) detection. Here we present data using tissue-agnostic, genome-wide enrichment platform based on methylated immunoprecipitation and high throughput sequencing (cfMEDIP-seq) in head neck (HNC) to predict relapse purposes of guiding adjuvant therapy after completion curative-intent treatment detect early...

10.1200/jco.2024.42.16_suppl.3009 article EN Journal of Clinical Oncology 2024-06-01

Background: Patients with chronic limb-threatening ischemia (CLTI) have high mortality rates after revascularization. Balancing short-term risk against limb salvage gains is important when triaging patients CLTI to Data for stratification limited. We aimed develop machine learning models rank predictive variables 30-day and 90-day all-cause peripheral vascular intervention (PVI). Methods: undergoing PVI between 2017 2018 in the Medicare-linked Vascular Quality Initiative (VQI) were included....

10.1161/circ.148.suppl_1.16870 article EN Circulation 2023-11-07

Introduction: Optimizing limb survival in patients with chronic limb-threatening ischemia (CLTI) undergoing peripheral vascular intervention (PVI) is a major focus. Care plans that consider patients’ high-mortality risk are less common. Understanding which have the highest mortality would enable more personalized care plan designs to person-centered care. We aimed leverage random forest machine learning (RFML) model predict long-term CLTI PVI. Methods: A cohort of PVI from 2017 2019 Medicare...

10.1161/circ.148.suppl_1.16867 article EN Circulation 2023-11-07
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