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The objective of the proposed project is to quantify the prevalence and disparities of undiagnosed left ventricular hypertrophy (LVH) in Emergency Department (ED) patients with persistently elevated asymptomatic BP, and to measure the effect of disclosure, education, and expedited referral on 3-month outpatient follow-up and treatment rates for ED patients with newly diagnosed LVH by POCUS. Additionally, investigators will create a database of annotated clips for future development of a machine learning algorithm for LVH detection on POCUS.
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The rationale for the proposed project is that, through bedside LVH detection, ED POCUS can be leveraged to identify those high-risk patients with asymptomatic hypertension (HTN) and improve disease prevention equity, while also ultimately decrease cardiovascular disease burden. The objective of the proposed project is to evaluate the feasibility and impact of LVH determination by POCUS on ED patients with elevated BP, and to quantify disparities in diagnosis and treatment.
This study has 3 Aims:
Aim 1: To quantify the prevalence and disparities of undiagnosed LVH in ED patients with persistently elevated asymptomatic BP. The investigators will enroll a prospective cohort of ED patients with BP > 140/90mmHg on two measurements who will receive POCUS to assess for LVH. The investigators hypothesize an overall LVH prevalence of at least 30%.
Aim 2: To measure the effect of disclosure, education, and expedited referral on 3-month outpatient follow-up and treatment rates for ED patients with newly diagnosed LVH by POCUS. In a single arm feasibility clinical trial, subjects enrolled in the Aim 1 cohort with LVH on POCUS will receive the study intervention consisting of disclosure, counseling with set discharge instructions and expedited referral (communication to existing primary care physician OR referral to a follow-up clinic if no existing primary care). The investigators hypothesize a 50% follow-up rate and a 40% treatment rate.
Aim 3: To create a database of annotated clips for development of an artificial intelligence (AI) algorithm for LVH detection on POCUS. A collection of annotated clips would support subsequent training, validation, and eventual integration into POCUS technology to facilitate larger scale screening and referral efforts.
Aim 1 will have a prospective observational study design. Aim 2 will occur sequentially based on results of POCUS performed as part of Aim 1. Aim 3 will follow a repository creation protocol utilizing the ultrasound clips obtained during Aim 1.
This study will lay the groundwork for future research to evaluate the impact of interventions informed by LVH assessment by POCUS on hypertension control, referral, and cardiovascular outcomes, as well as effectiveness of implementation strategies.
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200 participants in 1 patient group
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Cristiana Baloescu, MD, MPH
Data sourced from clinicaltrials.gov
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