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Added:
11 months ago
In this short interview, we are joined by Dr Michelle Kittleson (Cedars-Sinai Heart Institute, US) to discuss the key updates and recommendations from the 2025 ACC Scientific Statement on the Management of Obesity in Adults with Heart Failure.Interview Questions:1. What is the current research landscape for heart failure patients with obesity?2. What are the new recommendations in this scientific…
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e-SPACE HF 2024 – Day One
Start date:
Oct 18, 2024
Broadcast
e-SPACE HF 2024 – Day Two
Start date:
Oct 19, 2024
Broadcast
Added:
1 year ago
ESC Congress — Ms Carys Barton (Imperial College Healthcare NHS Trust, London, UK) joins us on-site to talk about the implementation of heart failure guidelines.Interview Questions:1. What are the biggest challenges in implementing heart failure guidelines?2. How do nurses help implement guidelines, and what strategies do they use?3. What training can help with guideline implementation?4. How can…
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Cancer Screening in HF
Added:
1 year ago
Short Communication
Added:
1 year ago
AHA Conference 2024 - Discover the findings from a new study on the impact of diastolic dysfunction on the efficacy of empagliflozin in heart failure in the EMPEROR-Preserved trial.Prof Andrew Coats (Heart Research Institute, New South Wales, AU) joins us onsite at AHA Conference to discuss findings from a new analysis of diastolic dysfunction in the EMPEROR-Preserved trial (NCT03057951).EMPEROR…
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MY-MDHFC Study
Added:
3 months ago
Original Research
Added:
3 months ago
Added:
3 months ago
Source:
Arrhythmia Academy
Artificial intelligence applied to electrocardiograms (ECG-AI) may offer a scalable way to identify individuals at high risk of developing heart failure (HF), potentially improving on current clinical risk estimators, according to a new pooled cohort analysis from the HeartShare/Accelerating Medicines Partnership (AMP) Heart Failure program.¹The study aimed to assess whether ECG-AI models…
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Added:
2 months ago
Source:
CFR Journal
Consumer wearable devices may offer a scalable method for the daily monitoring of heart failure (HF) symptoms and predicting exacerbations. A new study has detailed how a deep learning model using Apple Watch data can estimate cardiopulmonary fitness and provide early risk discrimination for unplanned healthcare events in patients with HF.¹MethodologyThe Ted Rogers Understanding Exacerbations of…
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