Sneha Annie Sebastian MD , Edzel Lorraine Co MD, DMD , Arun Mahtani MD , Inderbir Padda MD, MPH , Mahvish Anam MD , Swapna Susan Mathew MD , Ayesha Shahzadi MD , Maha Niazi MD , Shubhadarshini Pawar MD , Gurpreet Johal MD, FACC, FASN, FRCPC
{"title":"Heart Failure: Recent Advances and Breakthroughs","authors":"Sneha Annie Sebastian MD , Edzel Lorraine Co MD, DMD , Arun Mahtani MD , Inderbir Padda MD, MPH , Mahvish Anam MD , Swapna Susan Mathew MD , Ayesha Shahzadi MD , Maha Niazi MD , Shubhadarshini Pawar MD , Gurpreet Johal MD, FACC, FASN, FRCPC","doi":"10.1016/j.disamonth.2023.101634","DOIUrl":null,"url":null,"abstract":"<div><p><span>Heart failure (HF) is a common clinical condition encountered in various healthcare settings with a vast socioeconomic impact. Recent advancements in pharmacotherapy have led to the evolution of novel therapeutic agents with a decrease in hospitalization and mortality rates in HF with reduced left ventricular ejection fraction (HFrEF). Lately, the introduction of artificial intelligence (AI) to construct decision-making models for the early detection of HF has played a vital role in optimizing cardiovascular disease outcomes. In this review, we examine the newer therapies and evidence behind goal-directed medical therapy (GDMT) for managing HF. We also explore the application of AI and machine learning (ML) in HF, including early diagnosis and </span>risk stratification<span> for HFrEF.</span></p></div>","PeriodicalId":51017,"journal":{"name":"Dm Disease-A-Month","volume":"70 2","pages":"Article 101634"},"PeriodicalIF":3.8000,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Dm Disease-A-Month","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0011502923001141","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
Abstract
Heart failure (HF) is a common clinical condition encountered in various healthcare settings with a vast socioeconomic impact. Recent advancements in pharmacotherapy have led to the evolution of novel therapeutic agents with a decrease in hospitalization and mortality rates in HF with reduced left ventricular ejection fraction (HFrEF). Lately, the introduction of artificial intelligence (AI) to construct decision-making models for the early detection of HF has played a vital role in optimizing cardiovascular disease outcomes. In this review, we examine the newer therapies and evidence behind goal-directed medical therapy (GDMT) for managing HF. We also explore the application of AI and machine learning (ML) in HF, including early diagnosis and risk stratification for HFrEF.
期刊介绍：
Designed for primary care physicians, each issue of Disease-a-Month presents an in-depth review of a single topic. In this way, the publication can cover all aspects of the topic - pathophysiology, clinical features of the disease or condition, diagnostic techniques, therapeutic approaches, and prognosis.
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