European heart journal. Digital health最新文献

{"title":"Validation of a novel numerical model to predict regionalized blood flow in the coronary arteries.","authors":"Daniel J Taylor,&nbsp;Jeroen Feher,&nbsp;Krzysztof Czechowicz,&nbsp;Ian Halliday,&nbsp;D R Hose,&nbsp;Rebecca Gosling,&nbsp;Louise Aubiniere-Robb,&nbsp;Marcel Van't Veer,&nbsp;Danielle C J Keulards,&nbsp;Pim Tonino,&nbsp;Michel Rochette,&nbsp;Julian P Gunn,&nbsp;Paul D Morris","doi":"10.1093/ehjdh/ztac077","DOIUrl":"https://doi.org/10.1093/ehjdh/ztac077","url":null,"abstract":"<p><strong>Aims: </strong>Ischaemic heart disease results from insufficient coronary blood flow. Direct measurement of absolute flow (mL/min) is feasible, but has not entered routine clinical practice in most catheterization laboratories. Interventional cardiologists, therefore, rely on surrogate markers of flow. Recently, we described a computational fluid dynamics (CFD) method for predicting flow that differentiates inlet, side branch, and outlet flows during angiography. In the current study, we evaluate a new method that regionalizes flow along the length of the artery.</p><p><strong>Methods and results: </strong>Three-dimensional coronary anatomy was reconstructed from angiograms from 20 patients with chronic coronary syndrome. All flows were computed using CFD by applying the pressure gradient to the reconstructed geometry. Side branch flow was modelled as a porous wall boundary. Side branch flow magnitude was based on morphometric scaling laws with two models: a homogeneous model with flow loss along the entire arterial length; and a regionalized model with flow proportional to local taper. Flow results were validated against invasive measurements of flow by continuous infusion thermodilution (Coroventis™, Abbott). Both methods quantified flow relative to the invasive measures: homogeneous (<i>r</i> 0.47, <i>P</i> 0.006; zero bias; 95% CI -168 to +168 mL/min); regionalized method (<i>r</i> 0.43, <i>P</i> 0.013; zero bias; 95% CI -175 to +175 mL/min).</p><p><strong>Conclusion: </strong>During angiography and pressure wire assessment, coronary flow can now be regionalized and differentiated at the inlet, outlet, and side branches. The effect of epicardial disease on agreement suggests the model may be best targeted at cases with a stenosis close to side branches.</p>","PeriodicalId":72965,"journal":{"name":"European heart journal. Digital health","volume":"4 2","pages":"81-89"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10039427/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9552636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Determining the cause of cardiac arrest: artificial intelligence at the bedside.","authors":"Samantha K Engrav,&nbsp;Jeffrey B Geske,&nbsp;Konstantinos C Siontis","doi":"10.1093/ehjdh/ztad002","DOIUrl":"https://doi.org/10.1093/ehjdh/ztad002","url":null,"abstract":",","PeriodicalId":72965,"journal":{"name":"European heart journal. Digital health","volume":"4 2","pages":"136-137"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/ca/ee/ztad002.PMC10039424.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9567930","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automated categorization of virtual reality studies in cardiology based on the device usage: a bibliometric analysis (2010-2022).","authors":"Akinori Higaki,&nbsp;Yuta Watanabe,&nbsp;Yusuke Akazawa,&nbsp;Toru Miyoshi,&nbsp;Hiroshi Kawakami,&nbsp;Fumiyasu Seike,&nbsp;Haruhiko Higashi,&nbsp;Takayuki Nagai,&nbsp;Kazuhisa Nishimura,&nbsp;Katsuji Inoue,&nbsp;Shuntaro Ikeda,&nbsp;Osamu Yamaguchi","doi":"10.1093/ehjdh/ztad008","DOIUrl":"https://doi.org/10.1093/ehjdh/ztad008","url":null,"abstract":"<p><strong>Aims: </strong>Currently, virtual reality (VR) constitutes a vital aspect of digital health, necessitating an overview of study trends. We classified type A studies as those in which health care providers utilized VR devices and type B studies as those in which patients employed the devices. This study aimed to analyse the characteristics of each type of studies using natural language processing (NLP) methods.</p><p><strong>Methods and results: </strong>Literature related to VR in cardiovascular research was searched in PubMed between 2010 and 2022. The characteristics of studies were analysed based on their classification as type A or type B. Abstracts of the studies were used as corpus for text mining. A binary logistic regression model was trained to automatically categorize the abstracts into the two study types. Classification performance was evaluated by accuracy, precision, recall, F-1 score, and c-statistics of the receiver operator curve (ROC) analysis. In total, 171 articles met the inclusion criteria, where 120 (70.2%) were type A studies and 51 (29.8%) were type B studies. Type A studies had a higher proportion of case reports than type B studies (18.3% vs. 3.9%, <i>P</i> = 0.01). As for abstract classification, the binary logistic regression model yielded 88% accuracy and an area under the ROC of 0.98. The words 'training', '3d', and 'simulation' were the most powerful determinants of type A studies, while the words 'patients', 'anxiety', and 'rehabilitation' were more indicative for type B studies.</p><p><strong>Conclusions: </strong>NLP methods revealed the characteristics of the two types of VR-related research in cardiology.</p>","PeriodicalId":72965,"journal":{"name":"European heart journal. Digital health","volume":"4 2","pages":"119-124"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/84/62/ztad008.PMC10039423.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9198159","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Virtual healthcare solutions for cardiac rehabilitation: a literature review.","authors":"Keni C S Lee,&nbsp;Boris Breznen,&nbsp;Anastasia Ukhova,&nbsp;Friedrich Koehler,&nbsp;Seth S Martin","doi":"10.1093/ehjdh/ztad005","DOIUrl":"https://doi.org/10.1093/ehjdh/ztad005","url":null,"abstract":"<p><p>Graphical AbstractAdherence to cardiac rehabilitation following a primary event has been demonstrated to improve quality of life, increase functional capacity, and decrease hospitalizations and mortality. Mobile technologies offer an opportunity to improve both the quality and utilization of cardiac rehabilitation, and recent clinical studies investigated this technology. This literature review summarizes the current use of mobile health, wearable activity monitors (WAMs), and other multi-component technologies deployed to support home-based virtual cardiac rehabilitation. The methodology was adapted from the <i>Cochrane Handbook for Systematic Reviews of Interventions</i>. We identified 2094 records, of which 113 were eligible for qualitative analysis. Different virtual cardiac rehabilitation solutions were implemented in the studies: (i) multi-component interventions in 48 studies (42.5%), (ii) WAMs in 27 studies (23.9%), (iii) web-based communications solutions, and (iv) mobile apps, both in 19 studies (16.4%). Functional capacity was the most frequently reported primary outcome (<i>k</i> = 37, 32.7%), followed by user adherence/compliance (<i>k</i> = 35, 31.0%), physical activity (<i>k</i> = 27, 23.9%), and quality of life (<i>k</i> = 14, 12.4%). Studies provided a mixed assessment of the efficacy of virtual cardiac rehabilitation in attaining either significant improvements over baseline or significant improvements in outcomes compared with conventional rehabilitation. Efficacy outcomes with virtual cardiac rehabilitation sometimes improve on the centre-based outcomes; however, superior clinical efficacy may not necessarily be the only outcome of interest. The promise of virtual cardiac rehabilitation includes the potential for increased user adherence and longer-term patient engagement. If these outcomes can be improved, that would be a significant justification for using this technology.</p>","PeriodicalId":72965,"journal":{"name":"European heart journal. Digital health","volume":"4 2","pages":"99-111"},"PeriodicalIF":0.0,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/39/df/ztad005.PMC10039430.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9567933","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A prospective, randomized, controlled, multicentre trial for secondary prevention in patients with chronic coronary syndrome using a smartphone application for digital therapy: the CHANGE study protocol.","authors":"Philip Düsing, Irina Eckardt, Stephan H Schirmer, Jan-Malte Sinning, Nikos Werner, Florian Bönner, Alexander Krogmann, Sebastian Schäfer, Alexander Sedaghat, Cornelius Müller, Georg Nickenig, Andreas Zietzer","doi":"10.1093/ehjdh/ztad012","DOIUrl":"10.1093/ehjdh/ztad012","url":null,"abstract":"<p><strong>Aims: </strong>Coronary artery disease (CAD) remains the leading cause of death worldwide. 'Stable' CAD is a chronic progressive condition, which recent European guidelines recommend referring to as 'chronic coronary syndrome' (CCS). Despite therapeutic advances, morbidity and mortality among patients with CCS remain high. Optimal secondary prevention in patients with CCS includes optimization of modifiable risk factors with behavioural changes and pharmacological therapy. The CHANGE study aims to provide evidence for optimization of secondary prevention in CCS patients by using a smartphone application (app).</p><p><strong>Methods and results: </strong>The CHANGE study is designed as a prospective, randomized, controlled trial with a 1:1 allocation ratio, which is currently performed in nine centres in Germany in a parallel group design. 210 patients with CCS will be randomly allocated either to the control group (standard-of-care) or to the intervention group, who will be provided the VantisTherapy* app in addition to standard-of-care to incorporate secondary prevention into their daily life. The study will be performed in an open design. Outcomes will be assessed using objective data from three in-person visits (0, 12, and 24 weeks). Primary outcomes will involve adherence to secondary prevention recommendations and quality of life (QoL). The recruitment process started in July 2022.</p><p><strong>Conclusion: </strong>The CHANGE study will investigate whether a smartphone-guided secondary prevention app, combined with a monitor function compared with standard-of-care, has beneficial effects on overall adherence to secondary prevention guidelines and QoL in patients with CCS.</p><p><strong>Trial registration: </strong>The study is listed at the German study registry (DRKS) under the registered number DRKS00028081.</p>","PeriodicalId":72965,"journal":{"name":"European heart journal. Digital health","volume":"4 3","pages":"207-215"},"PeriodicalIF":3.9,"publicationDate":"2023-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/df/f5/ztad012.PMC10232292.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9568844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinician-to-clinician electronic consultation in cardiology is also a digital health technology for cardiovascular care.","authors":"José R González-Juanatey, Sergio Cinza Sanjurjo","doi":"10.1093/ehjdh/ztad011","DOIUrl":"10.1093/ehjdh/ztad011","url":null,"abstract":"","PeriodicalId":72965,"journal":{"name":"European heart journal. Digital health","volume":"4 2","pages":"69-70"},"PeriodicalIF":3.9,"publicationDate":"2023-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/26/31/ztad011.PMC10039421.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9567932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The association of electronic health literacy with behavioural and psychological coronary artery disease risk factors in patients after percutaneous coronary intervention: a 12-month follow-up study.","authors":"Gunhild Brørs, Håvard Dalen, Heather Allore, Christi Deaton, Bengt Fridlund, Cameron D Norman, Pernille Palm, Tore Wentzel-Larsen, Tone M Norekvål","doi":"10.1093/ehjdh/ztad010","DOIUrl":"10.1093/ehjdh/ztad010","url":null,"abstract":"<p><strong>Aims: </strong>Fundamental roadblocks, such as non-use and low electronic health (eHealth) literacy, prevent the implementation of eHealth resources. The aims were to study internet usage for health information and eHealth literacy in patients after percutaneous coronary intervention (PCI). Further, we aimed to evaluate temporal changes and determine whether the use of the internet to find health information and eHealth literacy were associated with coronary artery disease (CAD) risk factors at the index admission and 12-month follow-up of the same population.</p><p><strong>Methods and results: </strong>This prospective longitudinal study recruited 2924 adult patients with internet access treated by PCI in two Nordic countries. Assessments were made at baseline and 12-month follow-up, including a <i>de novo</i> question <i>Have you used the internet to find information about health?</i>, the eHealth literacy scale, and assessment of clinical, behavioural, and psychological CAD risk factors. Regression analyses were used. Patients' use of the internet for health information and their eHealth literacy were moderate at baseline but significantly lower at 12-month follow-up. Non-users of the internet for health information were more often smokers and had a lower burden of anxiety symptoms. Lower eHealth literacy was associated with a higher burden of depression symptoms at baseline and lower physical activity and being a smoker at baseline and at 12-month follow-up.</p><p><strong>Conclusion: </strong>Non-use of the internet and lower eHealth literacy need to be considered when implementing eHealth resources, as they are associated with behavioural and psychological CAD risk factors. eHealth should therefore be designed and implemented with high-risk CAD patients in mind.</p><p><strong>Clinical trial registration: </strong>ClinicalTrials.gov NCT03810612 https://clinicaltrials.gov/ct2/show/NCT03810612.</p>","PeriodicalId":72965,"journal":{"name":"European heart journal. Digital health","volume":"4 2","pages":"125-135"},"PeriodicalIF":3.9,"publicationDate":"2023-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/a8/75/ztad010.PMC10039428.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9552635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Premature atrial and ventricular contractions detected on wearable-format electrocardiograms and prediction of cardiovascular events.","authors":"Michele Orini, Stefan van Duijvenboden, William J Young, Julia Ramírez, Aled R Jones, Andrew Tinker, Patricia B Munroe, Pier D Lambiase","doi":"10.1093/ehjdh/ztad007","DOIUrl":"10.1093/ehjdh/ztad007","url":null,"abstract":"<p><strong>Aims: </strong>Wearable devices are transforming the electrocardiogram (ECG) into a ubiquitous medical test. This study assesses the association between premature ventricular and atrial contractions (PVCs and PACs) detected on wearable-format ECGs (15 s single lead) and cardiovascular outcomes in individuals without cardiovascular disease (CVD).</p><p><strong>Methods and results: </strong>Premature atrial contractions and PVCs were identified in 15 s single-lead ECGs from <i>N</i> = 54 016 UK Biobank participants (median age, interquartile range, age 58, 50-63 years, 54% female). Cox regression models adjusted for traditional risk factors were used to determine associations with atrial fibrillation (AF), heart failure (HF), myocardial infarction (MI), stroke, life-threatening ventricular arrhythmias (LTVAs), and mortality over a period of 11.5 (11.4-11.7) years. The strongest associations were found between PVCs (prevalence 2.2%) and HF (hazard ratio, HR, 95% confidence interval = 2.09, 1.58-2.78) and between PACs (prevalence 1.9%) and AF (HR = 2.52, 2.11-3.01), with shorter prematurity further increasing risk. Premature ventricular contractions and PACs were also associated with LTVA (<i>P</i> < 0.05). Associations with MI, stroke, and mortality were significant only in unadjusted models. In a separate UK Biobank sub-study sample [UKB-2, <i>N</i> = 29,324, age 64, 58-60 years, 54% female, follow-up 3.5 (2.6-4.8) years] used for independent validation, after adjusting for risk factors, PACs were associated with AF (HR = 1.80, 1.12-2.89) and PVCs with HF (HR = 2.32, 1.28-4.22).</p><p><strong>Conclusion: </strong>In middle-aged individuals without CVD, premature contractions identified in 15 s single-lead ECGs are strongly associated with an increased risk of AF and HF. These data warrant further investigation to assess the role of wearable ECGs for early cardiovascular risk stratification.</p>","PeriodicalId":72965,"journal":{"name":"European heart journal. Digital health","volume":"4 2","pages":"112-118"},"PeriodicalIF":0.0,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10039429/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9567928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A clinician-to-clinician universal electronic consultation programme at the cardiology department of a Galician healthcare area improves healthcare accessibility and outcomes in elderly patients.","authors":"Pilar Mazón-Ramos, Sergio Cinza-Sanjurjo, David Garcia-Vega, Manuel Portela-Romero, Juan C Sanmartin-Pena, Daniel Rey-Aldana, Amparo Martinez-Monzonis, Jenifer Espasandín-Domínguez, Francisco Gude-Sampedro, José R González-Juanatey","doi":"10.1093/ehjdh/ztad004","DOIUrl":"10.1093/ehjdh/ztad004","url":null,"abstract":"<p><strong>Aims: </strong>We aimed to assess longer-term results (accessibility, hospital admissions, and mortality) in elderly patients referred to a cardiology department (CD) from primary care using e-consultation in outpatient care.</p><p><strong>Methods and results: </strong>We included 9963 patients >80 years from 1 January 2010 to 31 December 2019. Until 2012, all patients attended an in-person consultation (2010-2012). In 2013, we instituted an e-consult programme (2013-2019) for all primary care referrals to cardiologists that preceded a patient's in-person consultation when considered. We used an interrupted time series (ITS) regression approach to investigate the impact of e-consultation on (i) cardiovascular hospital admissions and mortality. We also analysed (ii) the total number and referral rate (population-adjusted referred rate) in both periods, and (iii) the accessibility was measured as the number of consultations and variation according to the distance from the municipality and reference hospital. During e-consultation, the demand for care increased (12.8 ± 4.3% vs. 25.5 ± 11.1% per 1000 inhabitants, <i>P</i> < 0.001) and referrals from different areas were equalized. After the implementation of e-consultation, we observed that the increase in hospital admissions and mortality were stabilized [incidence rate ratio (iRR): 1.351 (95% CI, 0.787, 2.317), <i>P</i> = 0.874] and [iRR: 1.925 (95% CI: 0.889, 4.168), <i>P</i> = 0.096], respectively. The geographic variabilities in hospital admissions and mortality seen during the in-person consultation were stabilized after e-consultation implementation.</p><p><strong>Conclusions: </strong>Implementation of a clinician-to-clinician e-consultation programme in outpatient care was associated with improved accessibility to cardiology healthcare in elderly patients. After e-consultations were implemented, hospital admissions and mortality were stabilized.</p>","PeriodicalId":72965,"journal":{"name":"European heart journal. Digital health","volume":"4 2","pages":"90-98"},"PeriodicalIF":3.9,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/73/1a/ztad004.PMC10039426.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9567934","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-invasive detection of cardiac allograft rejection among heart transplant recipients using an electrocardiogram based deep learning model.","authors":"Demilade Adedinsewo, Heather D Hardway, Andrea Carolina Morales-Lara, Mikolaj A Wieczorek, Patrick W Johnson, Erika J Douglass, Bryan J Dangott, Raouf E Nakhleh, Tathagat Narula, Parag C Patel, Rohan M Goswami, Melissa A Lyle, Alexander J Heckman, Juan C Leoni-Moreno, D Eric Steidley, Reza Arsanjani, Brian Hardaway, Mohsin Abbas, Atta Behfar, Zachi I Attia, Francisco Lopez-Jimenez, Peter A Noseworthy, Paul Friedman, Rickey E Carter, Mohamad Yamani","doi":"10.1093/ehjdh/ztad001","DOIUrl":"10.1093/ehjdh/ztad001","url":null,"abstract":"<p><strong>Aims: </strong>Current non-invasive screening methods for cardiac allograft rejection have shown limited discrimination and are yet to be broadly integrated into heart transplant care. Given electrocardiogram (ECG) changes have been reported with severe cardiac allograft rejection, this study aimed to develop a deep-learning model, a form of artificial intelligence, to detect allograft rejection using the 12-lead ECG (AI-ECG).</p><p><strong>Methods and results: </strong>Heart transplant recipients were identified across three Mayo Clinic sites between 1998 and 2021. Twelve-lead digital ECG data and endomyocardial biopsy results were extracted from medical records. Allograft rejection was defined as moderate or severe acute cellular rejection (ACR) based on International Society for Heart and Lung Transplantation guidelines. The extracted data (7590 unique ECG-biopsy pairs, belonging to 1427 patients) was partitioned into training (80%), validation (10%), and test sets (10%) such that each patient was included in only one partition. Model performance metrics were based on the test set (<i>n</i> = 140 patients; 758 ECG-biopsy pairs). The AI-ECG detected ACR with an area under the receiver operating curve (AUC) of 0.84 [95% confidence interval (CI): 0.78-0.90] and 95% (19/20; 95% CI: 75-100%) sensitivity. A prospective proof-of-concept screening study (<i>n</i> = 56; 97 ECG-biopsy pairs) showed the AI-ECG detected ACR with AUC = 0.78 (95% CI: 0.61-0.96) and 100% (2/2; 95% CI: 16-100%) sensitivity.</p><p><strong>Conclusion: </strong>An AI-ECG model is effective for detection of moderate-to-severe ACR in heart transplant recipients. Our findings could improve transplant care by providing a rapid, non-invasive, and potentially remote screening option for cardiac allograft function.</p>","PeriodicalId":72965,"journal":{"name":"European heart journal. Digital health","volume":"4 2","pages":"71-80"},"PeriodicalIF":0.0,"publicationDate":"2023-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/35/4b/ztad001.PMC10039431.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9567931","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}