Beatriz Castillo Rodriguez MD , Eric A. Secemsky MD , Rajesh V. Swaminathan MD , Dmitriy N. Feldman MD , Markus Schlaich MD , Yuri Battaglia MD, PhD , Edward J. Filippone MD , Chayakrit Krittanawong MD
{"title":"The Reply","authors":"Beatriz Castillo Rodriguez MD , Eric A. Secemsky MD , Rajesh V. Swaminathan MD , Dmitriy N. Feldman MD , Markus Schlaich MD , Yuri Battaglia MD, PhD , Edward J. Filippone MD , Chayakrit Krittanawong MD","doi":"10.1016/j.amjmed.2024.07.019","DOIUrl":"10.1016/j.amjmed.2024.07.019","url":null,"abstract":"","PeriodicalId":50807,"journal":{"name":"American Journal of Medicine","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142512429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Amylase in Lung Cancer: Not All That Glitters…","authors":"Lars C. Huber MD, Mattia Arrigo MD","doi":"10.1016/j.amjmed.2024.07.011","DOIUrl":"10.1016/j.amjmed.2024.07.011","url":null,"abstract":"","PeriodicalId":50807,"journal":{"name":"American Journal of Medicine","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142512420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Solomon Liao, Alpesh N Amin, Steven Barczi, Christine Barron, Laura E Degnon, Jennifer G Duncan, Brian Kwan, Vera Luther, Mary E Moffatt, Angela Myers, Paul O'Rourke, Iliana D Vera, Aimee K Zaas, John Solomonides
{"title":"Salary Equity among Subspecialty Fellows: A Call to Action.","authors":"Solomon Liao, Alpesh N Amin, Steven Barczi, Christine Barron, Laura E Degnon, Jennifer G Duncan, Brian Kwan, Vera Luther, Mary E Moffatt, Angela Myers, Paul O'Rourke, Iliana D Vera, Aimee K Zaas, John Solomonides","doi":"10.1016/j.amjmed.2024.10.017","DOIUrl":"https://doi.org/10.1016/j.amjmed.2024.10.017","url":null,"abstract":"","PeriodicalId":50807,"journal":{"name":"American Journal of Medicine","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142512419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Environmental Neurotoxins and a Neurodegenerative Outbreak: Diagnosis Requires Specific Sampling Knowledge.","authors":"Arnold R Eiser","doi":"10.1016/j.amjmed.2024.08.033","DOIUrl":"10.1016/j.amjmed.2024.08.033","url":null,"abstract":"","PeriodicalId":50807,"journal":{"name":"American Journal of Medicine","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142479973","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ran Abuhasira, Nitzan Burrack, Adi Turjeman, Yonatan Shneor Patt, Leonard Leibovici, Alon Grossman
{"title":"Comparative Analysis of First-Line Antihypertensive Treatment Classes.","authors":"Ran Abuhasira, Nitzan Burrack, Adi Turjeman, Yonatan Shneor Patt, Leonard Leibovici, Alon Grossman","doi":"10.1016/j.amjmed.2024.10.016","DOIUrl":"https://doi.org/10.1016/j.amjmed.2024.10.016","url":null,"abstract":"<p><strong>Background: </strong>The best first-line monotherapy for hypertension remains uncertain, as current guidelines suggest that thiazides, angiotensin-converting enzyme inhibitors (ACEi), angiotensin receptor blockers (ARB), and calcium channel blockers (CCB) are appropriate in the absence of specific comorbidities. We aimed to compare the outcomes of first-line antihypertensive classes in a real-life setting with a long follow-up period.</p><p><strong>Methods: </strong>This nationwide retrospective new-user cohort study included patients insured by the largest health maintenance organization in Israel. We included patients with a new diagnosis of hypertension between 2008 and 2021 who initiated treatment with a single first-line drug for hypertension. Outcomes were assessed with and without propensity score matching for confounding factors. The primary composite outcome was the first occurrence of myocardial infarction (MI), acute coronary syndrome (ACS), stroke, or heart failure (HF).</p><p><strong>Results: </strong>A total of 97,639 patients initiated antihypertensive treatment with a single drug as first-line therapy. The most commonly prescribed class was ACEi/ARB (66,717, 68.3%), followed by CCBs (15,922, 16.3%), beta-blockers (BBs, 12,869, 13.2%), and thiazides (2,131, 2.2%). For the primary outcome, the hazard ratios (HRs) for BBs, CCBs, and ACEi/ARBs were 1.44 (95% CI 1.25 - 1.66), 1.10 (95% CI 0.96 - 1.27), and 1.13 (95% CI 0.99 - 1.29), respectively, when compared to thiazides.</p><p><strong>Conclusion: </strong>When initiating pharmacotherapy for hypertension with a single drug, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, and calcium channel blockers were associated with similar risk of MI, ACS, stroke, or HF when compared to thiazides, while beta-blockers were associated with increased risk.</p>","PeriodicalId":50807,"journal":{"name":"American Journal of Medicine","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142479958","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Veins Tell the Tale: Visible Clues of Budd-Chiari Syndrome.","authors":"Yasuhiro Kano","doi":"10.1016/j.amjmed.2024.10.004","DOIUrl":"10.1016/j.amjmed.2024.10.004","url":null,"abstract":"","PeriodicalId":50807,"journal":{"name":"American Journal of Medicine","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142479980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mehmet Ulvi Saygi Ayvaci, Varghese S Jacobi, Young Ryu, Saikrishna Pannaga Srikar Gundreddy, Bekir Tanriover
{"title":"Clinically Guided Adaptive Machine Learning Update Strategies for Predicting Severe COVID-19 Outcomes.","authors":"Mehmet Ulvi Saygi Ayvaci, Varghese S Jacobi, Young Ryu, Saikrishna Pannaga Srikar Gundreddy, Bekir Tanriover","doi":"10.1016/j.amjmed.2024.10.011","DOIUrl":"https://doi.org/10.1016/j.amjmed.2024.10.011","url":null,"abstract":"<p><strong>Background: </strong>Machine learning algorithms are essential for predicting severe outcomes during public health crises like COVID-19. However, the dynamic nature of diseases requires continual evaluation and updating of these algorithms. This study aims to compare three update strategies for predicting severe COVID-19 outcomes post-diagnosis: 'naive' (a single initial model), 'frequent' (periodic retraining), and 'context-driven' (retraining informed by clinical insights). The goal is to determine the most effective timing and approach for adapting algorithms to evolving disease dynamics and emerging data.</p><p><strong>Methods: </strong>A dataset of 1.11 million COVID-19 patients from diverse U.S. regions was used to develop and validate an XGBoost algorithm for predicting severe outcomes upon diagnosis. Data included patient demographics, vital signs, comorbidities, and immunity-related factors (prior infection and vaccination status) from January 2007 to November 2021. The study analyzed the performance of the three update strategies from March 2020 to November 2021.</p><p><strong>Results: </strong>Predictive features changed over the pandemic, with comorbidities and vitals being significant initially, and geography, demographics, and immunity-related variables gaining importance later. The 'naive' strategy had an average AUC of 0.77, the 'frequent' strategy-maintained stability with an average AUC of 0.81, and the 'context-driven' strategy averaged an AUC of 0.80, outperforming the 'naive' strategy and aligning closely with the 'frequent' strategy.</p><p><strong>Conclusion: </strong>A context-driven approach, guided by clinical insights, can enhance predictive performance and offer cost-effective solutions for dynamic public health challenges. These findings have significant implications for efficiently managing healthcare resources during evolving disease outbreaks.</p>","PeriodicalId":50807,"journal":{"name":"American Journal of Medicine","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142479957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Phillip H Lam, Kevin Liu, Amiya A Ahmed, Javed Butler, Paul A Heidenreich, Markus S Anker, Charles Faselis, Prakash Deedwania, Wilbert S Aronow, Ioannis Kanonidis, Ravi Masson, Gauravpal S Gill, Charity J Morgan, Cherinne Arundel, Richard M Allman, Wen-Chih Wu, Gregg C Fonarow, Ali Ahmed
{"title":"Digoxin Discontinuation in Patients with HFrEF on Beta-Blockers: Implication for Future \"Knock-Out Trials\" in Heart Failure.","authors":"Phillip H Lam, Kevin Liu, Amiya A Ahmed, Javed Butler, Paul A Heidenreich, Markus S Anker, Charles Faselis, Prakash Deedwania, Wilbert S Aronow, Ioannis Kanonidis, Ravi Masson, Gauravpal S Gill, Charity J Morgan, Cherinne Arundel, Richard M Allman, Wen-Chih Wu, Gregg C Fonarow, Ali Ahmed","doi":"10.1016/j.amjmed.2024.10.015","DOIUrl":"https://doi.org/10.1016/j.amjmed.2024.10.015","url":null,"abstract":"<p><strong>Background: </strong>National heart failure guidelines recommend quadruple therapy with renin-angiotensin system inhibitors, beta-blockers, mineralocorticoid receptor antagonists, and sodium-glucose cotransporter 2 inhibitors for patients with heart failure with reduced ejection fraction (HFrEF), most of whom also receive loop diuretics. However, the guidelines are less clear about the safe approaches to discontinuing older drugs whose decreasing or residual benefit is less well understood. The objective of this study was to examine whether digoxin can be safely discontinued in patients with HFrEF receiving beta-blockers.</p><p><strong>Methods: </strong>In OPTIMIZE-HF, of 2,477 patients with HFrEF (EF ≤45%) receiving beta-blockers and digoxin, digoxin was discontinued in 450 patients. We assembled a propensity score-matched cohort of 433 pairs of patients in which digoxin continuation vs. discontinuation groups were balanced on 51 baseline characteristics. Using the same approach, from 992 patients not on beta-blockers, we assembled a matched cohort of 198 pairs of patients also balanced on 51 baseline characteristics. Hazard ratios (HRs) and 95% CIs for one-year outcomes were estimated.</p><p><strong>Results: </strong>Among patients receiving beta-blockers, digoxin discontinuation had no association with the combined endpoint of heart failure readmission or death (HR, 1.01; 95% CI, 0.85-1.19), heart failure readmission (HR, 1.03; 95% CI, 0.85-1.25) or death (HR, 0.91; 95% CI, 0.72-1.14). Respective HRs (95% CIs) among patients not receiving beta-blockers were 1.60 (1.25-2.04), 1.62 (1.18-2.22) and 1.43 (1.08-1.89).</p><p><strong>Conclusions: </strong>Digoxin can be discontinued without increasing the risk of adverse outcomes in patients with HFrEF receiving beta-blockers. Future studies need to examine the residual benefit of older heart failure drugs to ensure their safe discontinuation in patients with HFrEF receiving newer guideline-directed medical therapy.</p>","PeriodicalId":50807,"journal":{"name":"American Journal of Medicine","volume":null,"pages":null},"PeriodicalIF":2.5,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142479970","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}