Journal of the American Society of Echocardiography最新文献

{"title":"Designing a Tailored Career Path: A Guide to Creating Flexible Career Ladders","authors":"","doi":"10.1016/j.echo.2025.02.007","DOIUrl":"10.1016/j.echo.2025.02.007","url":null,"abstract":"","PeriodicalId":50011,"journal":{"name":"Journal of the American Society of Echocardiography","volume":"38 4","pages":"Pages A18-A22"},"PeriodicalIF":5.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143746707","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Normal Fetal Ventricular Strain Pilot Study","authors":"Carol McFarland MD, Cathleen Pruitt MD, Mary T. Donofrio MD, Lindsay R. Freud MD, Leo Lopez MD, L. LuAnn Minich MD, Anita J. Moon-Grady MD, Zhining Ou MS, Rajesh Punn MD, Theresa A. Tacy MD, Oluwatosin Fatusin MD, Nelangi Pinto MD, the Fetal Heart Society Research Collaborative","doi":"10.1016/j.echo.2024.10.020","DOIUrl":"10.1016/j.echo.2024.10.020","url":null,"abstract":"","PeriodicalId":50011,"journal":{"name":"Journal of the American Society of Echocardiography","volume":"38 4","pages":"Pages 361-363"},"PeriodicalIF":5.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142631312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Acute Maternal Hyperoxygenation to Predict Hypoxia and Need for Emergency Intervention in Fetuses With Transposition of the Great Arteries: A Pilot Study","authors":"Trisha V. Vigneswaran MBBS, BSc(Hons), MD(res) ,&nbsp;Chris Oakley MBBS ,&nbsp;Hannah R. Bellsham-Revell MBBS, MD(res) ,&nbsp;Matthew Jones MBBS ,&nbsp;Vita Zidere DM, MD ,&nbsp;Reza Razavi MBBS, MD ,&nbsp;John M. Simpson MD","doi":"10.1016/j.echo.2024.12.011","DOIUrl":"10.1016/j.echo.2024.12.011","url":null,"abstract":"<div><h3>Background</h3><div>Newborns with transposition of the great arteries (TGA) are at risk of severe hypoxia from inadequate atrial mixing, closure of the arterial duct, and/or persistent pulmonary hypertension of the newborn (PPHN). Acute maternal hyperoxygenation (AMH) might assist in identifying at-risk fetuses. We report pulmonary vasoreactivity to AMH in TGA fetuses and its relationship to early postnatal hypoxia and requirement for emergency balloon atrial septostomy (e-BAS).</div></div><div><h3>Methods</h3><div>Standard fetal echocardiographic (FE) assessment of the foramen ovale (FO): to total septal length and morphology of flap valve of the FO were used to predict the need for e-BAS. Following prospective recruitment, additional assessments were performed in fetuses with TGA at baseline and repeated after 10 minutes of 10 L/min of 100% oxygen delivered via non-rebreather mask to the pregnant mother. Analysis included measurement of atrial septal excursion, branch pulmonary artery pulsatility index (PA PI), middle cerebral artery (MCA) PI, and cardiac output. Delivery and newborn status were reviewed. Hypoxia was defined as preductal oxygen saturations &lt;75% and e-BAS when undertaken within 2 hours of birth. Area under receiver operating characteristics curves were calculated.</div></div><div><h3>Results</h3><div>Thirty cases underwent FE at 34.6 weeks’ gestation (interquartile range, 34.6-35.6). All 7 predicted to require e-BAS based on standard FE were correctly identified prenatally. Three of 30 were hypoxic without FO restriction and treated with nitric oxide (PPHN). Change in PA PI ≤ 15% was associated with PPHN (<em>P</em> = .001) but not with e-BAS. The MCA PI response to AMH varied according to newborn condition, a mean reduction occurred in the non-hypoxic newborns (−7.8 ± 18.3, <em>P</em> = .05). Increase in MCA PI <em>Z</em> score (area under receiver operating characteristics curves; 0.837; 95% CI, 0.663-1.00, <em>P</em> = .01), reduction in right ventricular cardiac output (0.811; 95% CI, 0.623-0.998, <em>P</em> = .04), and reduction in combined cardiac output (0.851; 95% CI, 0.699-1.0, <em>P</em> = .01) were moderately associated with e-BAS. Changes in atrial septal excursion and FO flow direction with AMH did not correlate with newborn condition.</div></div><div><h3>Conclusions</h3><div>A PA PI change ≤15% to AMH was associated with postnatal hypoxia due to PPHN. Increase in right and combined cardiac output and reduced MCA resistance with AMH are seen in those who do not require e-BAS.</div></div>","PeriodicalId":50011,"journal":{"name":"Journal of the American Society of Echocardiography","volume":"38 4","pages":"Pages 331-339"},"PeriodicalIF":5.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142957967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extending the Mitral Annular Disjunction Phenotype: Anomalous Attachment of the Posterior Mitral Annulus to the Crest of the Left Ventricle","authors":"Jeffrey J. Silbiger MD,&nbsp;Raveen Bazaz MD","doi":"10.1016/j.echo.2025.01.014","DOIUrl":"10.1016/j.echo.2025.01.014","url":null,"abstract":"","PeriodicalId":50011,"journal":{"name":"Journal of the American Society of Echocardiography","volume":"38 4","pages":"Pages 364-365"},"PeriodicalIF":5.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143257256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Muscling Out of Musculoskeletal Injury in Cardiovascular Ultrasound","authors":"Allyson Boyle MHA, ACS, RDCS, FASE ,&nbsp;Ashlee Davis ACS, RDCS, RCCS, FASE","doi":"10.1016/j.echo.2025.02.015","DOIUrl":"10.1016/j.echo.2025.02.015","url":null,"abstract":"","PeriodicalId":50011,"journal":{"name":"Journal of the American Society of Echocardiography","volume":"38 4","pages":"Pages A15-A17"},"PeriodicalIF":5.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143746706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Information for Readers","authors":"","doi":"10.1016/S0894-7317(25)00129-4","DOIUrl":"10.1016/S0894-7317(25)00129-4","url":null,"abstract":"","PeriodicalId":50011,"journal":{"name":"Journal of the American Society of Echocardiography","volume":"38 4","pages":"Pages A11-A12"},"PeriodicalIF":5.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748685","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning Identifies Clinically Distinct Phenotypes in Patients With Aortic Regurgitation","authors":"Brototo Deb MD, MIDS ,&nbsp;Christopher G. Scott MS ,&nbsp;Hector I. Michelena MD, PhD ,&nbsp;Sorin V. Pislaru MD, PhD ,&nbsp;Vuyisile T. Nkomo MD, MPH ,&nbsp;Garvan C. Kane MD, PhD ,&nbsp;Juan A. Crestanello MD ,&nbsp;Patricia A. Pellikka MD ,&nbsp;Vidhu Anand MD","doi":"10.1016/j.echo.2024.10.019","DOIUrl":"10.1016/j.echo.2024.10.019","url":null,"abstract":"<div><h3>Background</h3><div>Aortic regurgitation (AR) is a prevalent valve disease with a long latent period before symptoms appear. Recent data has suggested the role of novel markers of myocardial overload in assessing onset of decompensation.</div></div><div><h3>Methods</h3><div>The aim of this study was to evaluate the role of unsupervised cluster analyses in identifying different clinical clusters, including clinical status, and a large number of echocardiographic variables including left ventricular volumes, and their associations with mortality. Patients with moderate to severe or greater chronic AR identified using echocardiography at the Mayo Clinic in Rochester, Minnesota, were retrospectively analyzed. The primary outcome was all-cause mortality censored at aortic valve surgery. Uniform manifold approximation and projection with the <em>k</em>-means algorithm was used to cluster patients using clinical and echocardiographic variables at the time of presentation. Missing data were imputed using the multiple imputation by chained equations method. A supervised approach trained on the training set was used to find cluster membership in a hold-out validation set. Log-rank tests were used to assess differences in mortality rates among the clusters in both the training and validation sets.</div></div><div><h3>Results</h3><div>Three distinct clusters were identified among 1,100 patients (log-rank <em>P</em> for survival &lt; .001). Cluster 1 (<em>n</em> = 337), which included younger males with severe AR but fewer symptoms, showed the best survival at 75.6% (95% CI, 69.5%-82.3%). Cluster 2 (<em>n</em> = 235), including older patients and more females with elevated filling pressures, showed intermediate survival of 64.2% (95% CI, 56.8%-72.5%). Cluster 3 (<em>n</em> = 253), characterized by severe symptomatic AR, demonstrated the lowest survival of 45.3% (95% CI, 34.4%-59.8%) at 5 years. Similar clusters were identified in the internal validation cohort.</div></div><div><h3>Conclusions</h3><div>Distinct clusters with variable echocardiographic features and mortality differences exist within patients with chronic moderate to severe or greater AR. Recognizing these clusters can refine individual risk stratification and clinical decision-making after verification in future prospective studies.</div></div>","PeriodicalId":50011,"journal":{"name":"Journal of the American Society of Echocardiography","volume":"38 4","pages":"Pages 300-309"},"PeriodicalIF":5.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142683162","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utility of an Echocardiographic Machine Learning Model to Predict Outcomes in Intensive Cardiac Care Unit Patients","authors":"Samy Aghezzaf MD ,&nbsp;Augustin Coisne MD, PhD ,&nbsp;Kenza Hamzi MSc ,&nbsp;Solenn Toupin PhD ,&nbsp;Claire Bouleti MD, PhD ,&nbsp;Charles Fauvel MD ,&nbsp;Jean-Baptiste Brette MD ,&nbsp;David Montaigne MD, PhD ,&nbsp;Reza Rossanaly Vasram MD ,&nbsp;Antonin Trimaille MD ,&nbsp;Gilles Lemesle MD, PhD ,&nbsp;Guillaume Schurtz MD ,&nbsp;Edouard Gerbaud MD, PhD ,&nbsp;Clément Delmas MD, PhD ,&nbsp;Marc Bedossa MD ,&nbsp;Jean-Claude Dib MD ,&nbsp;Vincent Roule MD, PhD ,&nbsp;Etienne Puymirat MD, PhD ,&nbsp;Martine Gilard MD, PhD ,&nbsp;Marouane Boukhris MD ,&nbsp;Theo Pezel MD, PhD","doi":"10.1016/j.echo.2024.11.014","DOIUrl":"10.1016/j.echo.2024.11.014","url":null,"abstract":"<div><h3>Introduction</h3><div>The risk stratification at admission to the intensive cardiac care unit (ICCU) is crucial and remains challenging.</div></div><div><h3>Objectives</h3><div>We aimed to investigate the accuracy of a machine learning (ML)-model based on initial transthoracic echocardiography (TTE) to predict in-hospital major adverse events (MAEs) in a broad spectrum of patients admitted to ICCU.</div></div><div><h3>Methods</h3><div>All consecutive patients hospitalized in ICCUs with a complete TTE performed within the first 24 hours of admission were included in this prospective multicenter study (39 centers). Sixteen TTE parameters were evaluated. The ML model involved automated feature selection by random survival forest and model building with an extreme gradient boosting (XGBoost) algorithm. The primary outcome was in-hospital MAEs defined as all-cause death, resuscitated cardiac arrest, or cardiogenic shock.</div></div><div><h3>Results</h3><div>Of 1,499 consecutive patients (63 ± 15 years, 70% male), MAEs occurred in 67 patients (4.5%). The 5 TTE parameters selected in the model were left ventricular outflow tract velocity-time integral, E/e’ ratio, systolic pulmonary artery pressure, tricuspid annular plane systolic excursion, and left ventricular ejection fraction. Using the XGBoost, the ML model exhibited a higher area under the receiver operating curve compared with any existing scores (ML model, 0.83 vs logistic regression, 0.76, ACUTE-HF score:,0.66; thrombolysis in myocardial infarction score, 0.60; Global Registry of Acute Coronary Events score, 0.58, all <em>P</em> &lt; .001). The ML model had an incremental prognostic value for predicting MAE over a traditional model including clinical and biological data (<em>C</em> index 0.80 vs 0.73, <em>P</em> = .012; chi-square 59.7 vs 32.4; <em>P</em> &lt; .001).</div></div><div><h3>Conclusion</h3><div>The ML model based on initial TTE exhibited a higher prognostic value to predict in-hospital MAEs compared with existing scores or clinical and biological data in the ICCU.</div></div>","PeriodicalId":50011,"journal":{"name":"Journal of the American Society of Echocardiography","volume":"38 4","pages":"Pages 320-330"},"PeriodicalIF":5.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142839656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Limited Concordance of Left Ventricular Ejection Fraction and Chamber Dimensions With Automated Assessments in Hypertrophic Cardiomyopathy: A Substudy From VALOR-HCM","authors":"Gary Parizher MD,&nbsp;Alice Haouzi MD,&nbsp;Wael A. Jaber MD,&nbsp;Anjali Owens MD,&nbsp;Kathy Wolski MPH,&nbsp;Jeffrey B. Geske MD,&nbsp;Sara Saberi MD, MS,&nbsp;Andrew Wang MD,&nbsp;Mark Sherrid MD,&nbsp;Neal K. Lakdawala MD,&nbsp;Albree Tower-Rader MD,&nbsp;David Fermin MD,&nbsp;Srihari S. Naidu MD,&nbsp;Zoran B. Popovic MD, PhD,&nbsp;Nicholas G. Smedira MD, MBA,&nbsp;Hartzell Schaff MD,&nbsp;Ellen McErlean RN, MSN,&nbsp;Christina Sewell RN,&nbsp;Kathy Lampl MD,&nbsp;Amy J. Sehnert MD,&nbsp;Paul C. Cremer MD, MS","doi":"10.1016/j.echo.2024.12.009","DOIUrl":"10.1016/j.echo.2024.12.009","url":null,"abstract":"","PeriodicalId":50011,"journal":{"name":"Journal of the American Society of Echocardiography","volume":"38 4","pages":"Pages 356-358"},"PeriodicalIF":5.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142903994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Blood Pressure and Echocardiographic Interpretation: Guideline Revision Needed","authors":"Christopher Lee MD,&nbsp;Theodore P. Abraham MD,&nbsp;Nelson B. Schiller MD","doi":"10.1016/j.echo.2025.01.003","DOIUrl":"10.1016/j.echo.2025.01.003","url":null,"abstract":"","PeriodicalId":50011,"journal":{"name":"Journal of the American Society of Echocardiography","volume":"38 4","pages":"Page 364"},"PeriodicalIF":5.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142973025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}