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{"title":"Prediction of atrial fibrillation after a stroke event: A systematic review with meta-analysis","authors":"Anna Helbitz MSc ,&nbsp;Mohammad Haris MRes ,&nbsp;Tanina Younsi MBBS ,&nbsp;Elizabeth Romer MBChB ,&nbsp;William Ginks BSc ,&nbsp;Keerthenan Raveendra MPhil ,&nbsp;Chris Hayward PhD ,&nbsp;Farag Shuweihdi PhD ,&nbsp;Harriet Larvin PhD ,&nbsp;Alan Cameron PhD ,&nbsp;Jianhua Wu PhD ,&nbsp;Brian Buck MD ,&nbsp;Gregory Y.H. Lip MD ,&nbsp;Ramesh Nadarajah PhD ,&nbsp;Chris P. Gale PhD","doi":"10.1016/j.hrthm.2025.01.026","DOIUrl":"10.1016/j.hrthm.2025.01.026","url":null,"abstract":"<div><h3>Background</h3><div>Detecting atrial fibrillation (AF) after stroke is a key component of secondary prevention, but indiscriminate prolonged cardiac monitoring is costly and burdensome. Multivariable prediction models could be used to inform selection of patients.</div></div><div><h3>Objective</h3><div>This study aimed to determine the performance of available models for predicting AF after a stroke.</div></div><div><h3>Methods</h3><div>We searched for studies of multivariable models that were derived, validated, or augmented for prediction of AF in patients with a stroke, using MEDLINE and Embase from inception through September 20, 2024. Discrimination measures for tools with C statistic data from ≥3 cohorts were pooled by bayesian meta-analysis, with heterogeneity assessed through a 95% prediction interval. The risk of bias was assessed with the Prediction model Risk Of Bias Assessment tool (PROBAST).</div></div><div><h3>Results</h3><div>We included 75 studies with 58 prediction models; 66% had a high risk of bias. Fifteen multivariable models were eligible for meta-analysis. Three models showed excellent discrimination: SAFE (C statistic, 0.856; 95% confidence interval [CI], 0.796–0.916), SURF (0.815; 95% CI, 0.728–0.893), and iPAB (0.888; 95% CI, 0.824–0.957). Excluding high-bias studies, only SAFE showed excellent discrimination (0.856; 95% CI 0.800–0.915). No model showed excellent discrimination when limited to external validation or studies with ≥100 AF events. No clinical impact studies were found.</div></div><div><h3>Conclusion</h3><div>Three of the 58 identified multivariable prediction models for AF after stroke demonstrated excellent statistical performance on meta-analysis. However, prospective validation is required to understand the effectiveness of these models in clinical practice before they can be recommended for inclusion in clinical guidelines.</div></div>","PeriodicalId":12886,"journal":{"name":"Heart rhythm","volume":"22 7","pages":"Pages 1637-1645"},"PeriodicalIF":5.6,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143046450","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":"The effect of capsaicin-phenylephrine-caffeine formulation on tilt-induced syncope in patients with a history of vasovagal syncope or near-syncope","authors":"Mohamed H. Hamdan MD, MBA, FACC, FHRS ,&nbsp;Michele Brignole MD, FESC ,&nbsp;Pierre Michelet MD, PhD ,&nbsp;Jean Claude Deharo MD, FESC ,&nbsp;Régis Guieu MD, PhD","doi":"10.1016/j.hrthm.2025.01.017","DOIUrl":"10.1016/j.hrthm.2025.01.017","url":null,"abstract":"","PeriodicalId":12886,"journal":{"name":"Heart rhythm","volume":"22 7","pages":"Pages e254-e256"},"PeriodicalIF":5.6,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143004453","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":"Electrical dyssynchrony mapping and optimization of nonresponders in patients programmed with the adaptive cardiac resynchronization therapy algorithm","authors":"Alan J. Bank MD ,&nbsp;Kevin V. Burns PhD ,&nbsp;Christopher D. Brown BA ,&nbsp;Evan Walser-Kuntz MS ,&nbsp;Madeline A. Czeck PhD ,&nbsp;Robert G. Hauser MD ,&nbsp;Jay D. Sengupta MD","doi":"10.1016/j.hrthm.2024.12.012","DOIUrl":"10.1016/j.hrthm.2024.12.012","url":null,"abstract":"<div><h3>Background</h3><div>The adaptive cardiac resynchronization therapy (CRT) (aCRT) algorithm provides an important clinical benefit. However, a significant number of patients are nonresponders.</div></div><div><h3>Objectives</h3><div>The goals of this study were to quantify electrical synchrony in patients programmed with aCRT and to assess the echocardiographic effects of optimization in CRT nonresponders and incomplete responders.</div></div><div><h3>Methods</h3><div>We studied 125 patients programmed with aCRT and measured electrical synchrony at multiple device settings using novel electrical dyssynchrony mapping (EDM) technology. Electrical synchrony was quantified as cardiac resynchronization index (CRI), a measure that analyzes areas between multiple pairs of anterior and posterior electrograms and calculates synchrony normalized to native rhythm.</div></div><div><h3>Results</h3><div>CRI improved from baseline aCRT settings to optimal settings on the basis of EDM (56%±29% vs 92%±12%; <em>P</em>&lt;.001). Patients programmed with left ventricle (LV)–only aCRT (group 1, n=68 [54%]) had a higher CRI (62%±25% vs 48%±31%; <em>P</em>=.014) than did patients programmed with biventricular aCRT (group 2, n=57 [46%]). In group 1 and group 2, optimal CRI during sequential biventricular (92%±13% and 93%±9%, respectively) and LV-only (92%±6% and 91%±7%, respectively) pacing was significantly (<em>P</em>&lt;.001) higher than CRI at baseline aCRT setting. In a subset of 53 nonresponders optimized using EDM, there were significant improvements in CRI (37%±25%; <em>P</em>&lt;.0001), LV ejection fraction (6.2%±6.6%; <em>P</em>&lt;.0001), end-diastolic volume (9.5±28.2 mL; <em>P</em>=.015), end-systolic volume (13.4±24.9 mL; <em>P</em>&lt;.001), and transverse (1.5%±4.4%; <em>P</em>=.014), longitudinal (1.0%±2.5%; <em>P</em>=.003), and circumferential (2.6%±8.5%; <em>P</em>=.047) strain.</div></div><div><h3>Conclusion</h3><div>Electrical synchrony improves 56% with CRT using aCRT programming and 92% with EDM optimization. Optimization of aCRT-programmed nonresponders results in significant improvements in LV size and systolic function, offering the possibility of converting CRT nonresponders into responders.</div></div>","PeriodicalId":12886,"journal":{"name":"Heart rhythm","volume":"22 7","pages":"Pages 1746-1755"},"PeriodicalIF":5.6,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142828235","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":"ACT targets during atrial fibrillation ablation","authors":"Thomas A. Boyle MD,&nbsp;Adrian M. Petzl MD,&nbsp;David S. Frankel MD","doi":"10.1016/j.hrthm.2024.12.023","DOIUrl":"10.1016/j.hrthm.2024.12.023","url":null,"abstract":"","PeriodicalId":12886,"journal":{"name":"Heart rhythm","volume":"22 7","pages":"Pages e259-e260"},"PeriodicalIF":5.6,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142871841","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":"Imaging findings associated with costoclavicular intervention during lead extraction","authors":"Ethan S. Wagner BS ,&nbsp;Jeffrey Gaca MD ,&nbsp;Donald D. Hegland MD ,&nbsp;Lynne Koweek MD ,&nbsp;Robert K. Lewis MD, PhD ,&nbsp;Sean D. Pokorney MD ,&nbsp;Adam Williams MD ,&nbsp;Jonathan P. Piccini MD, MHS, FHRS","doi":"10.1016/j.hrthm.2024.10.058","DOIUrl":"10.1016/j.hrthm.2024.10.058","url":null,"abstract":"<div><h3>Background</h3><div>Binding sites in the costoclavicular space are commonly encountered during transvenous lead extraction. Severe adhesions may warrant use of more aggressive rotational cutting tools or surgical intervention. It is not known whether preprocedural multidetector computed tomography (MDCT) can provide information about the likelihood that a patient will require costoclavicular intervention.</div></div><div><h3>Objective</h3><div>The purpose of this study was to determine whether there are preprocedural MDCT findings associated with need for intervention in the costoclavicular space during lead extraction.</div></div><div><h3>Methods</h3><div>Patients who underwent lead extraction and required use of stiffer rotational cutting tools (TightRail Sub-C) or surgical intervention in the costoclavicular space as well as age- and sex-matched controls who did not require intervention were included. Preprocedural MDCT was evaluated for patterns of lead tethering to bone and adjacent calcification.</div></div><div><h3>Results</h3><div>Overall, 56 patients were included (n = 20 Sub-C only, n = 8 surgical intervention, and n = 28 matched controls). The mean patient age of interventional cases was 65.0 ± 14.7 years, 18% were female, and the mean lead age was 12.3 ± 6.2 years. Four major patterns were identified on imaging: lead surrounded 360° by fat (intervention rate, 5/24 patients); lead tethered to bone by &lt;180° (11/19); no tethering of lead but with associated calcifications (3/4); and lead tethered to bone by &gt;180° (9/9). Tethering of at least 1 lead to bone by &gt;180° was associated with a 100% rate of costoclavicular intervention and the highest rate of surgical intervention (56%). Absence of any degree of bone tethering was associated with a 0% rate of surgical intervention.</div></div><div><h3>Conclusion</h3><div>Computed tomography captures details of costoclavicular binding that appear to correlate with the need for adjunctive extraction techniques, including surgical intervention. Computed tomography may be useful in preprocedural planning for adhesions in the costoclavicular space.</div></div>","PeriodicalId":12886,"journal":{"name":"Heart rhythm","volume":"22 7","pages":"Pages 1800-1809"},"PeriodicalIF":5.6,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142681028","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":"Enhanced detection of atrial fibrillation in single-lead electrocardiograms using a Cloud-based artificial intelligence platform","authors":"François De Guio PhD ,&nbsp;Michiel Rienstra MD, PhD ,&nbsp;José María Lillo-Castellano PhD ,&nbsp;Raquel Toribio-Fernández PhD ,&nbsp;Carlos Lizcano MS ,&nbsp;Daniel Corrochano-Diego MD ,&nbsp;David Jimenez-Virumbrales MD ,&nbsp;Manuel Marina-Breysse MD, MS","doi":"10.1016/j.hrthm.2024.12.048","DOIUrl":"10.1016/j.hrthm.2024.12.048","url":null,"abstract":"<div><h3>Background</h3><div>Although smartphone-based devices have been developed to record 1-lead electrocardiogram (ECG), existing solutions for automatic detection of atrial fibrillation (AF) often has poor positive predictive value.</div></div><div><h3>Objective</h3><div>This study aimed to validate a Cloud-based deep-learning platform for automatic AF detection in a large cohort of patients using 1-lead ECG records.</div></div><div><h3>Methods</h3><div>We analyzed 8528 patients with 30-second ECG records from a single-lead handheld ECG device. Ground truth for AF presence was established through a benchmark algorithm and expert manual labeling. The Willem Artificial Intelligence (AI) platform, not trained on these ECGs, was used for automatic arrhythmia detection, including AF. A rules-based algorithm was also used for comparison. An expert cardiology committee reviewed false positives and negatives, and performance metrics were computed.</div></div><div><h3>Results</h3><div>The AI platform achieved an accuracy of 96.1% (initial labels) and 96.4% (expert review), with sensitivities of 83.3% and 84.2%, and specificities of 97.3% and 97.6%, respectively. The positive predictive value was 75.2% and 78.0%, and the negative predictive value was 98.4%. Performance of the AI platform largely exceeded the performance of the rules-based algorithm for all metrics. The AI also detected other arrhythmias, such as premature ventricular complexes, premature atrial complexes along with 1-degree atrioventricular blocks.</div></div><div><h3>Conclusion</h3><div>The result of this external validation indicates that the AI platform can match cardiologist-level accuracy in AF detection from 1-lead ECGs. Such tools are promising for AF screening and have the potential to improve accuracy in noncardiology expert health care professional interpretation and trigger further tests for effective patient management.</div></div>","PeriodicalId":12886,"journal":{"name":"Heart rhythm","volume":"22 7","pages":"Pages 1667-1674"},"PeriodicalIF":5.6,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142970427","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":"Biomarkers and prediction models: Envisioning the future of atrial fibrillation detection after stroke","authors":"Giulio Francesco Romiti MD, PhD ,&nbsp;Valeria Trapani MD ,&nbsp;Marco Proietti MD, PhD","doi":"10.1016/j.hrthm.2025.02.051","DOIUrl":"10.1016/j.hrthm.2025.02.051","url":null,"abstract":"","PeriodicalId":12886,"journal":{"name":"Heart rhythm","volume":"22 7","pages":"Pages 1646-1647"},"PeriodicalIF":5.6,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143585242","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":"Tailoring non-invasive respiratory supports in acute hypoxemic respiratory failure: A practical approach for clinicians","authors":"Maria Laura Vega Pittao ,&nbsp;Stefano Nava ,&nbsp;Nicholas S Hill ,&nbsp;Lara Pisani","doi":"10.1016/j.ejim.2025.04.018","DOIUrl":"10.1016/j.ejim.2025.04.018","url":null,"abstract":"<div><div>The use of non-invasive respiratory support (NIRS) for acute respiratory failure (ARF), particularly hypoxemic respiratory failure, has advanced in recent years, especially during the COVID-19 pandemic. NIRS modalities like high-flow nasal cannula (HFNC), continuous positive airway pressure (CPAP), and non-invasive ventilation (NIV) have shown efficacy, though evidence is inconsistent, especially for \"de novo\" acute hypoxemic respiratory failure (AHRF). This review outlines the physiological rationale for NIRS and offers practical guidance on tailoring treatment to individual patients. Successful AHRF management with NIRS requires a personalized approach, guided by clinical expertise. Further research is needed to refine patient selection and optimize NIRS application.</div></div>","PeriodicalId":50485,"journal":{"name":"European Journal of Internal Medicine","volume":"137 ","pages":"Pages 21-32"},"PeriodicalIF":5.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144023067","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":"Omalizumab-associated purpura fulminans","authors":"Lan Li ,&nbsp;Jie Chen ,&nbsp;Kun Yang","doi":"10.1016/j.ejim.2025.04.021","DOIUrl":"10.1016/j.ejim.2025.04.021","url":null,"abstract":"","PeriodicalId":50485,"journal":{"name":"European Journal of Internal Medicine","volume":"137 ","pages":"Pages 121-122"},"PeriodicalIF":5.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144037694","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":"A protrusion of the left abdominal wall","authors":"Li Chai,&nbsp;Ze-Hu Liu","doi":"10.1016/j.ejim.2025.04.019","DOIUrl":"10.1016/j.ejim.2025.04.019","url":null,"abstract":"","PeriodicalId":50485,"journal":{"name":"European Journal of Internal Medicine","volume":"137 ","pages":"Pages 119-120"},"PeriodicalIF":5.9,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144049053","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}