Medicine and Health Sciences Commons^™

Using An Automated Model To Identify Older Patients At Risk For 30-Day Hospital Readmission And 30-Day Mortality, Ariba Khan, Mary L. Hook, Maharaj Singh, Marsha Vollbrecht, Aaron Malsch, Michael L. Malone

Mary Hook

Background: A real-time electronic health record (EHR) predictive model that identifies older patients at risk for readmission and mortality may assist the health care team in improved patient care.

Purpose: This study was performed to generate an automated 30-day readmission and 30-day mortality risk model using data from the EHR in hospitalized older adults.

Methods: This was a retrospective cohort study. Included were patients age 65 years and older admitted to the hospital from July 2012 to December 2013. An automated predictive model was derived from variables collected from the EHR including socioeconomic factors, medical diagnoses and health care utilization. …

Http://Www.Supplementcave.Com/Balanced-Body-Keto/, Locuse Bravo

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Changes In Anticoagulant Utilization Among United States Nursing Home Residents With Atrial Fibrillation From 2011 To 2016, Matthew Alcusky, David D. Mcmanus, Anne L. Hume, Marc Fisher, Jennifer Tjia, Kate L. Lapane

Jennifer Tjia

Background: Nursing home residents with atrial fibrillation are at high risk for ischemic stroke and bleeding events. The most recent national estimate (2004) indicated less than one third of this high-risk population was anticoagulated. Whether direct-acting oral anticoagulant ( DOAC ) use has disseminated into nursing homes and increased anticoagulant use is unknown.

Methods and Results: A repeated cross-sectional design was used to estimate the point prevalence of oral anticoagulant use on July 1 and December 31 of calendar years 2011 to 2016 among Medicare fee-for-service beneficiaries with atrial fibrillation residing in long-stay nursing homes. Nursing home residence was determined …

Developing A Community-Based Screening And Referral Mechanism For Atrial Fibrillation In Low Resource Settings: “Smartphone Monitoring For Atrial Fibrillation In Real-Time – India (Smart-India)”, Apurv Soni, Nisha Fahey, Harshil Patel, Kandarp Talati, Anna Handorf, John A. Bostrom, Shyamsundar Raihatha, Ravi Shah, Sunil Karna, Robert J. Goldberg, Jeroan J. Allison, Ki Chon, Somashekhar M. Nimbalkar, David D. Mcmanus

Apurv Soni

BACKGROUND: Atrial fibrillation (AF), the world’s most common arrhythmia, often goes undetected and untreated in low-resource communities, including India. Moreover, AF is an important risk factor for stroke, which plagues an estimated 1.6 million Indians annually. As such, early detection of AF and management of high-risk patients is critically important to decrease stroke burden in individuals with AF.

OBJECTIVE: The objectives of this study are to evaluate the age- and sex-stratified epidemiology of AF in Anand District, Gujarat India; characterize the profile of individuals who are diagnosed with AF; and determine the performance of two mobile technologies for community-based AF …

High Burden Of Unrecognized Atrial Fibrillation In Rural India: An Innovative Community-Based Cross-Sectional Screening Program, Apurv Soni, Allison Earon, Anna Handorf, Nisha Fahey, Kandarp Talati, John Bostrom, Ki Chon, Craig Napolitano, Michael S. Chin, John Stephen Sullivan, Shyamsundar Raithatha, Robert J. Goldberg, Somashekhar Nimbalkar, Jeroan J. Allison, Sunil Thanvi, David D. Mcmanus

Apurv Soni

BACKGROUND: Atrial fibrillation, the world's most common arrhythmia, is a leading risk factor for stroke, a disease striking nearly 1.6 million Indians annually. Early detection and management of atrial fibrillation is a promising opportunity to prevent stroke but widespread screening programs in limited resource settings using conventional methods is difficult and costly.

OBJECTIVE: The objective of this study is to screen people for atrial fibrillation in rural western India using a US Food and Drug Administration-approved single-lead electrocardiography device, Alivecor.

METHODS: Residents from 6 villages in Anand District, Gujarat, India, comprised the base population. After obtaining informed consent, a team …

Using Mobile-Based Technology To Screen For Atrial Fibrillation In India, Apurv Soni

Apurv Soni

As part of the mini-symposium entitled "Interdiscipllinary Mobile Health and Sensing Research," this presentation discusses use of a novel smartphone app for cardiovascular screening in rural India.

Role Of Serum Biomarkers In Early Detection Of Diabetic Cardiomyopathy In The West Virginian Population, Adam Shaver, Alexandra Nichols, Ellen A. Thompson, Amrita Mallick, Nandini Manne, Shanmuga Sundaram, Joseph I. Shapiro Md, Komal Sodhi

Joseph I Shapiro MD

Objectives: Diabetic cardiomyopathy (DCM) is an established complication of diabetes mellitus. In West Virginia, the especially high incidence of diabetes and heart failure validate the necessity of developing new strategies for earlier detection of DCM. Since most DCM patients remain asymptomatic until the later stages of the disease when the fibrotic complications become irreversible, we aimed to explore biomarkers that can identify early-stage DCM.

Methods: The patients were grouped into 4 categories based on clinical diabetic and cardiac parameters: Control, Diabetes (DM), Diastolic dysfunction (DD), and Diabetes with diastolic dysfunction (DM+DD), the last group being the preclinical DCM group.

Results: …

Role Of Serum Biomarkers In Early Detection Of Diabetic Cardiomyopathy In The West Virginian Population, Adam Shaver, Alexandra Nichols, Ellen A. Thompson, Amrita Mallick, Nandini Manne, Shanmuga Sundaram, Joseph I. Shapiro Md, Komal Sodhi

Komal Sodhi

Objectives: Diabetic cardiomyopathy (DCM) is an established complication of diabetes mellitus. In West Virginia, the especially high incidence of diabetes and heart failure validate the necessity of developing new strategies for earlier detection of DCM. Since most DCM patients remain asymptomatic until the later stages of the disease when the fibrotic complications become irreversible, we aimed to explore biomarkers that can identify early-stage DCM.

Methods: The patients were grouped into 4 categories based on clinical diabetic and cardiac parameters: Control, Diabetes (DM), Diastolic dysfunction (DD), and Diabetes with diastolic dysfunction (DM+DD), the last group being the preclinical DCM group.

Results: …