256 results match your criteria: "Center for Outcomes Research and Evaluation (CORE)[Affiliation]"

Article Synopsis
  • The study investigates sex differences in treatment approaches for pulmonary embolism (PE) among older adults, revealing that existing evidence on disparities is limited and often inconclusive due to small sample sizes and inadequate methods.
  • Analysis of data from a European PE registry and US Medicare beneficiaries shows no significant overall sex differences in the use of anticoagulation or advanced therapies, although fewer women received fibrinolytic therapy compared to men with intermediate-risk PE.
  • The authors suggest that future research should explore whether the observed sex disparities in treatment correlate with different clinical outcomes, especially regarding fibrinolytic therapy and advanced treatment utilization in older adults in the US.
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A Multicenter Evaluation of the Impact of Therapies on Deep Learning-Based Electrocardiographic Hypertrophic Cardiomyopathy Markers.

Am J Cardiol

November 2024

Section of Cardiovascular Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut; Center for Outcomes Research and Evaluation (CORE), Yale New Haven Hospital, New Haven, Connecticut; Section of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, Connecticut; Section of Health Informatics, Department of Biostatistics, Yale School of Public Health, New Haven, Connecticut. Electronic address:

Article Synopsis
  • AI-ECG can effectively detect hypertrophic cardiomyopathy (HCM) and track treatment responses using 12-lead ECGs.
  • The study analyzed data from patients undergoing surgical reduction and those receiving mavacamten at multiple healthcare centers, finding no improvement in HCM scores after surgery, but a significant decrease in scores among patients taking mavacamten.
  • This highlights AI-ECG's potential for ongoing monitoring of heart condition improvements following medication rather than surgical interventions.
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Purpose Of Review: Acute exacerbations of chronic obstructive pulmonary disease (COPD) are important events in the natural course of COPD, as they increase morbidity and mortality. Acute pulmonary embolism may mimic the symptoms of COPD exacerbations. However, the exact prevalence of pulmonary embolism in unexplained exacerbations of COPD is unclear based on the current data.

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Automated Identification of Heart Failure With Reduced Ejection Fraction Using Deep Learning-Based Natural Language Processing.

JACC Heart Fail

October 2024

Section of Cardiovascular Medicine, Department of Internal Medicine, Yale University, New Haven, Connecticut, USA; Center for Outcomes Research and Evaluation (CORE), Yale New Haven Hospital, New Haven, Connecticut, USA. Electronic address:

Background: The lack of automated tools for measuring care quality limits the implementation of a national program to assess guideline-directed care in heart failure with reduced ejection fraction (HFrEF).

Objectives: The authors aimed to automate the identification of patients with HFrEF at hospital discharge, an opportunity to evaluate and improve the quality of care.

Methods: The authors developed a novel deep-learning language model for identifying patients with HFrEF from discharge summaries of hospitalizations with heart failure at Yale New Haven Hospital during 2015 to 2019.

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Article Synopsis
  • Acute pulmonary embolism (PE) negatively impacts right ventricular function, which can be evaluated using the TAPSE/PASP ratio to predict patient outcomes.
  • A study analyzed data from over 4,400 patients with PE and found lower TAPSE/PASP ratios correlated with higher 30-day mortality rates, especially in intermediate-risk patients.
  • The TAPSE/PASP ratio is suggested to be a valuable tool for enhancing clinical decision-making and identifying patients at greater risk of mortality, beyond existing risk assessment methods.
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Background And Aims: AI-enhanced 12-lead ECG can detect a range of structural heart diseases (SHDs) but has a limited role in community-based screening. We developed and externally validated a noise-resilient single-lead AI-ECG algorithm that can detect SHD and predict the risk of their development using wearable/portable devices.

Methods: Using 266,740 ECGs from 99,205 patients with paired echocardiographic data at Yale New Haven Hospital, we developed ADAPT-HEART, a noise-resilient, deep-learning algorithm, to detect SHD using lead I ECG.

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Article Synopsis
  • Rich cardiovascular data is often hidden in unstructured reports, making it difficult to use in real-time patient care and research due to manual abstraction requirements.
  • A two-step process was developed using generative and interpretative large language models (LLMs) to convert these unstructured reports into usable formats, specifically focusing on transthoracic echocardiograms (TTE).
  • The HeartDX-LM model demonstrated impressive accuracy, extracting 98.7% of values from unstructured reports across various datasets, proving its effectiveness in improving data accessibility for clinical analysis.
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Prognostic significance of saddle pulmonary embolism a post hoc analysis of the PROTECT cohort study.

Thromb Res

December 2024

Respiratory Department, Hospital Ramón y Cajal and Instituto Ramón y Cajal de Investigación Sanitaria IRYCIS, Madrid, Spain; Medicine Department, Universidad de Alcalá, Madrid, Spain; CIBER Enfermedades Respiratorias (CIBERES), Madrid, Spain. Electronic address:

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Management of antithrombotic therapy in patients undergoing dental procedures.

J Thromb Haemost

October 2024

Department of Medicine, Thrombosis Research Group, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA; Cardiovascular Medicine Division, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA; Yale-New Haven Hospital/Yale Center for Outcomes Research and Evaluation (CORE), New Haven, Connecticut, USA. Electronic address:

A growing number of patients receiving antithrombotic therapy require dental procedures. Dental interventions in these patients can be challenging, as the risk of bleeding from the continuation of antithrombotic therapy needs to be weighed against the thromboembolic risk associated with drug interruption or de-escalation. Most minor dental procedures, including simple dental cleaning and filling, pose minimal bleeding risk, and antiplatelet or anticoagulation therapy can be continued without interruption.

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International Clinical Practice Guideline Recommendations for Acute Pulmonary Embolism: Harmony, Dissonance, and Silence.

J Am Coll Cardiol

October 2024

Division of Cardiovascular Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA; Thrombosis Research Group, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

Article Synopsis
  • Despite advancements in clinical practices, pulmonary embolism (PE) remains a significant challenge in diagnosis and treatment due to factors like aging populations and health disparities.
  • Clinicians often rely on various international guidelines for managing PE, but inconsistencies and gaps in recommendations can lead to confusion.
  • This review focuses on key similarities and differences in PE guidelines and emphasizes the need for clearer management strategies and further research in this area.
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Article Synopsis
  • - The BRIGHT-4 study showed that using bivalirudin with a high-dose infusion after PCI led to lower overall mortality and bleeding risks compared to heparin, without raising rates of reinfarction or stent thrombosis in STEMI patients.
  • - A meta-analysis of six trials involving over 15,000 patients found that while bivalirudin reduced overall and cardiac mortality and major bleeding, it was associated with higher rates of reinfarction and stent thrombosis compared to heparin.
  • - When specifically looking at a subset of trials similar to the BRIGHT-4 approach, bivalirudin also showed a decrease in 30-day mortality and major bleeding, with comparable rates of reinfar
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Objective: To systematically review the literature of existing evidence on the measurement properties of the Quality of Life in Neurological Disorders (Neuro-QoL) measurement system among neurorehabilitation populations.

Data Sources: The Consensus-based Standards for the selection of health Measurement Instruments (COSMIN) guided this systematic review in which we searched nine electronic databases and registries, and hand-searched reference lists of included articles.

Study Selection: Two independent reviewers screened selected articles and extracted data from 28 included studies.

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Response.

Chest

September 2024

Cardiovascular Medicine Division, Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Center for Outcomes Research and Evaluation (CORE), Yale University School of Medicine. New Haven, CT; Cardiovascular Research Foundation, New York, NY.

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Objective: To estimate the extent to which comorbidity, polypharmacy, and anticholinergic/sedative burden interrelate to influence cognitive ability, perceived cognitive deficits and physical frailty in people living with HIV.

Design: Cross-sectional Structural Equation Modeling (SEM) of data from 824 older people living with HIV in Canada, participating in the Positive Brain Health Now study.

Method: SEM was used to link observed variables, including comorbidity, polypharmacy, anticholinergic and sedative burden, to cognitive ability and two latent constructs - physical frailty and perceived cognitive deficits (PCD).

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This study generated evidence to guide anticoagulation in patients with VTE after vaccination for COVID-19. We provided data on the low recurrence rate after cessation of anticoagulant therapy and the findings for this study offer timely insights into the management of a potentially vaccine-related adverse event.

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Trustworthy and ethical AI-enabled cardiovascular care: a rapid review.

BMC Med Inform Decis Mak

September 2024

Section of General Internal Medicine, Department of Internal Medicine, Yale School of Medicine, New Haven, CT, USA.

Article Synopsis
  • Artificial intelligence (AI) is being increasingly integrated into cardiovascular care for various purposes like prevention and treatment, but faces ethical and trust issues from both patients and healthcare providers.
  • A comprehensive literature review was conducted to identify these ethical concerns and trust barriers, revealing that issues such as privacy, healthcare inequity, and accountability are significant obstacles to AI adoption.
  • Key findings show that major trust barriers stem from fears about data security, potential harm to patients, and the perceived lack of transparency and human touch in AI-driven healthcare.
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Article Synopsis
  • * A machine learning model, called ARISE, was developed to improve screening for elevated Lp(a) levels using data from the UK Biobank and validated in three other large studies.
  • * ARISE significantly reduces the number of tests needed to identify someone with high Lp(a), making it easier to utilize common clinical data and potentially implement in electronic health records for better screening outcomes.
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Article Synopsis
  • Researchers at McGill University created a small device called Heel2Toe™ that makes a sound to help people with Parkinson's improve their walking.
  • In a study with 27 participants, those using the Heel2Toe™ sensor showed better walking results compared to those using a workbook.
  • Most people using Heel2Toe™ reported being happy with the device, suggesting it could be a helpful tool for improving gait in Parkinson's patients.
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The association between prolonged SARS-CoV-2 symptoms and work outcomes.

PLoS One

July 2024

Division of Infectious Diseases, Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois, United States of America.

While the early effects of the COVID-19 pandemic on the United States labor market are well-established, less is known about the long-term impact of SARS-CoV-2 infection and Long COVID on employment. To address this gap, we analyzed self-reported data from a prospective, national cohort study to estimate the effects of SARS-CoV-2 symptoms at three months post-infection on missed workdays and return to work. The analysis included 2,939 adults in the Innovative Support for Patients with SARS-CoV-2 Infections Registry (INSPIRE) study who tested positive for their initial SARS-CoV-2 infection at the time of enrollment, were employed before the pandemic, and completed a baseline and three-month electronic survey.

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Introduction: Through interviews with 148 older persons from four countries and in four languages, the content for a 17-item measure of active living was developed. The purpose of this paper is to present further evidence of the extent to which this new measure, Older Persons Active Living (OPAL), is "fit-for-purpose" for measuring the extent of active living at one point in time.

Methods: A cross-sectional study was carried out on a population aged 65 + and living independently, drawn from a participant panel, HostedinCanada, sampling people from Canada, United States, United Kingdom, and Netherlands.

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Article Synopsis
  • The project aimed to create a measure called Older Persons for Active Living (OPAL) that reflects what matters to older adults, as many do not identify as "patients" and want to remain active.
  • Content was developed through interviews with older people from various countries, resulting in thematic analysis to synthesize their views on active living.
  • The final measure identified 17 important "ways of being" that highlight the active lifestyle preferences of older adults, while emphasizing the need to account for cultural and linguistic differences in the development process.
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Article Synopsis
  • AI is revolutionizing cardiovascular care and research by introducing advanced diagnostic tools, digital biomarkers, and quality evaluation systems.
  • These innovations aim to increase access to cardiovascular screening and monitoring, particularly for underserved populations lacking specialized care.
  • The review discusses the potential for personalized and effective treatments through AI advancements while emphasizing the necessary precautions and strategies to ensure successful implementation in healthcare.
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