European Journal of Clinical Investigation最新文献

{"title":"The role of artificial intelligence in cardiovascular research: Fear less and live bolder","authors":"Alessandro Scuricini,&nbsp;Davide Ramoni,&nbsp;Luca Liberale,&nbsp;Fabrizio Montecucco,&nbsp;Federico Carbone","doi":"10.1111/eci.14364","DOIUrl":"https://doi.org/10.1111/eci.14364","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Artificial intelligence (AI) has captured the attention of everyone, including cardiovascular (CV) clinicians and scientists. Moving beyond philosophical debates, modern cardiology cannot overlook AI's growing influence but must actively explore its potential applications in clinical practice and research methodology.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods and Results</h3>\u0000 \u0000 <p>AI offers exciting possibilities for advancing CV medicine by uncovering disease heterogeneity, integrating complex multimodal data, and enhancing treatment strategies. In this review, we discuss the innovative applications of AI in cardiac electrophysiology, imaging, angiography, biomarkers, and genomic data, as well as emerging tools like face recognition and speech analysis. Furthermore, we focus on the expanding role of machine learning (ML) in predicting CV risk and outcomes, outlining a roadmap for the implementation of AI in CV care delivery. While the future of AI holds great promise, technical limitations and ethical challenges remain significant barriers to its widespread clinical adoption.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Addressing these issues through the development of high-quality standards and involving key stakeholders will be essential for AI to transform cardiovascular care safely and effectively.</p>\u0000 </section>\u0000 </div>","PeriodicalId":12013,"journal":{"name":"European Journal of Clinical Investigation","volume":"55 S1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/eci.14364","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143786866","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deciphering immune dynamics in atherosclerosis: Inflammatory mediators as biomarkers and therapeutic target","authors":"Paolo Magni,&nbsp;Tijana Mitić,&nbsp;Yvan Devaux,&nbsp;Philippe Pierre,&nbsp;Miron Sopić,&nbsp;Fernando de la Cuesta,&nbsp;Rui Vitorino,&nbsp;EU-AtheroNET COST Action CA21153","doi":"10.1111/eci.70043","DOIUrl":"10.1111/eci.70043","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Atherosclerosis, one of the main causes of cardiovascular disease, is driven by complex interactions between lipid metabolism and immune mechanisms in the vascular system. Regulatory molecules, particularly protein fragments derived from cytokines, chemokines and other immune-related proteins, play a central role in modulating inflammation and immune responses in atherosclerotic plaques.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Recent advances in peptidomics have revealed the dual role of immune system-derived peptides as indicators and effectors of atherosclerotic cardiovascular disease (ASCVD). Certain subsets of immune cells, such as pro-inflammatory monocytes and regulatory T cells, contribute to this peptide-mediated regulation. New findings suggest that these peptides may serve as diagnostic biomarkers and therapeutic targets in atherosclerosis.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>This review highlights the translational relevance of immune-mediated peptides in ASCVD and emphasizes their diagnostic and therapeutic potential. By integrating peptidomics with immunology research, a new framework for understanding and targeting inflammation in atherosclerosis is proposed, opening new avenues for precision medicine in cardiovascular care.</p>\u0000 </section>\u0000 </div>","PeriodicalId":12013,"journal":{"name":"European Journal of Clinical Investigation","volume":"55 6","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143794780","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":"The reach and leading end of modern machine learning-based artificial intelligence in cardiovascular medicine","authors":"Luis Eduardo Juarez-Orozco","doi":"10.1111/eci.70004","DOIUrl":"https://doi.org/10.1111/eci.70004","url":null,"abstract":"","PeriodicalId":12013,"journal":{"name":"European Journal of Clinical Investigation","volume":"55 S1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143786713","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":"Editorial Introduction","authors":"Luis Eduardo Juarez-Orozco,&nbsp;Hendrik Nathoe","doi":"10.1111/eci.70029","DOIUrl":"https://doi.org/10.1111/eci.70029","url":null,"abstract":"","PeriodicalId":12013,"journal":{"name":"European Journal of Clinical Investigation","volume":"55 S1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143786963","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":"Expanding interpretability through complexity reduction in machine learning-based modelling of cardiovascular disease: A myocardial perfusion imaging PET/CT prognostic study","authors":"Eero Lehtonen,&nbsp;Jarmo Teuho,&nbsp;Monire Vatandoust,&nbsp;Juhani Knuuti,&nbsp;Remco J. J. Knol,&nbsp;Friso M. van der Zant,&nbsp;Luis Eduardo Juárez-Orozco,&nbsp;Riku Klén","doi":"10.1111/eci.14391","DOIUrl":"https://doi.org/10.1111/eci.14391","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Machine learning-based analysis can be used in myocardial perfusion imaging data to improve risk stratification and the prediction of major adverse cardiovascular events for patients with suspected or established coronary artery disease. We present a new machine learning approach for the identification of patients who develop major adverse cardiovascular events. The new method is robust against the deleterious effect of outliers in the training set stratification and training process.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>The proposed sum-of-sigmoids model is obtained by averaging the contributions of various input variables in an ensemble of XGBoost models. To illustrate its performance, we have applied it to predict major adverse cardiovascular events from advanced imaging data extracted from rest and adenosine stress ¹³N-ammonia positron emission tomography myocardial perfusion imaging polar maps. There were 1185 individual studies performed, and the event occurrence was tracked over a follow-up period of 2 years.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The sum-of-sigmoids model achieved a prediction accuracy of .83 on the test set, matching the performance of significantly more complex and less interpretable models (whose accuracies were .83–.84).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>The sum-of-sigmoids model is interpretable and simple, while achieving similar prediction accuracy to significantly more complex machine learning models in the considered prediction task. It should be suitable for applications such as automated clinical risk stratification, where clear and explicit justification of the classification procedure is highly pertinent.</p>\u0000 </section>\u0000 </div>","PeriodicalId":12013,"journal":{"name":"European Journal of Clinical Investigation","volume":"55 S1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/eci.14391","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143786711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Automatic reorientation algorithm for myocardial perfusion SPECT using segmentation","authors":"Ezequiel Vijande,&nbsp;Roxana Campisi,&nbsp;Luis Eduardo Juarez-Orozco,&nbsp;Roberto Agüero,&nbsp;Ricardo Geronazzo,&nbsp;Mauro Namías","doi":"10.1111/eci.70016","DOIUrl":"https://doi.org/10.1111/eci.70016","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Cardiac reorientation is a necessary step in processing myocardial perfusion images. This task usually requires manual intervention and thus introduces intra- and inter-operator variability in the processing workflow that may lead to reduced reproducibility of the results.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>A deep learning model was trained to perform segmentation of cardiac structures from SPECT images simulated from a real PET/CT dataset. Labels used for training were automatically generated in a semi-supervised fashion by using TotalSegmentator on CT images. Segmentation results from the trained model were used to calculate cardiac landmarks from which the cardiac axes were defined, and reorientation was performed. Automatic reorientation was compared against the manual reorientation defined by three expert nuclear cardiologists.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The average rotation difference between cardiac axes calculated from predicted segmentations and ground-truth segmentations was <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <msup>\u0000 <mn>5.3</mn>\u0000 <mo>°</mo>\u0000 </msup>\u0000 <mo>±</mo>\u0000 <msup>\u0000 <mn>3.1</mn>\u0000 <mo>°</mo>\u0000 </msup>\u0000 </mrow>\u0000 </semantics></math> on the simulated SPECT test dataset. In real SPECT images, the standard deviation of the angle difference between the automatic method and human experts was lower in all axes and operators compared to the maximum inter-operator standard deviation.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>The proposed deep learning-based algorithm provides an automatic method to perform cardiac reorientation in myocardial perfusion SPECT images with an error range like the variability between operators and with the advantage of using objective anatomical landmarks for the definition of cardiac axes.</p>\u0000 </section>\u0000 </div>","PeriodicalId":12013,"journal":{"name":"European Journal of Clinical Investigation","volume":"55 S1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143786710","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":"Machine learning in cardiovascular risk assessment: Towards a precision medicine approach","authors":"Yifan Wang,&nbsp;Evmorfia Aivalioti,&nbsp;Kimon Stamatelopoulos,&nbsp;Georgios Zervas,&nbsp;Martin Bødtker Mortensen,&nbsp;Marianne Zeller,&nbsp;Luca Liberale,&nbsp;Davide Di Vece,&nbsp;Victor Schweiger,&nbsp;Giovanni G. Camici,&nbsp;Thomas F. Lüscher,&nbsp;Simon Kraler","doi":"10.1111/eci.70017","DOIUrl":"https://doi.org/10.1111/eci.70017","url":null,"abstract":"<p>Cardiovascular diseases remain the leading cause of global morbidity and mortality. Validated risk scores are the basis of guideline-recommended care, but most scores lack the capacity to integrate complex and multidimensional data. Limitations inherent to traditional risk prediction models and the growing burden of residual cardiovascular risk highlight the need for refined strategies that go beyond conventional paradigms. Artificial intelligence and machine learning (ML) provide unique opportunities to refine cardiovascular risk assessment and surveillance through the integration of diverse data types and sources, including clinical, electrocardiographic, imaging and multi-omics derived data. In fact, ML models, such as deep neural networks, can handle high-dimensional data through which phenotyping and cardiovascular risk assessment across diverse patient populations become much more precise, fostering a paradigm shift towards more personalized care. Here, we review the role of ML in advancing cardiovascular risk assessment and discuss its potential to identify novel therapeutic targets and to improve prevention strategies. We also discuss key challenges inherent to ML, such as data quality, standardized reporting, model transparency and validation, and discuss barriers in its clinical translation. We highlight the transformative potential of ML in precision cardiology and advocate for more personalized cardiovascular prevention strategies that go beyond previous notions.</p>","PeriodicalId":12013,"journal":{"name":"European Journal of Clinical Investigation","volume":"55 S1","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143786965","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":"Strengthening the reporting of diet item details in feeding studies measuring the dietary metabolome: The DID-METAB core outcome set statement","authors":"Jessica J. A. Ferguson,&nbsp;Erin D. Clarke,&nbsp;Jordan Stanford,&nbsp;María Gómez-Martín,&nbsp;Tammie Jakstas,&nbsp;Clare E. Collins,&nbsp;DID-METAB Delphi Working Group Authors","doi":"10.1111/eci.70030","DOIUrl":"10.1111/eci.70030","url":null,"abstract":"&lt;p&gt;Nutrition research and diet–disease relationships historically rely on self-reported data assessed via dietary assessment instruments such as 24-h dietary recalls, food records, food frequency questionnaires, etc.,&lt;span&gt;&lt;sup&gt;1&lt;/sup&gt;&lt;/span&gt; which are prone to inherent bias and errors.&lt;span&gt;&lt;sup&gt;1, 2&lt;/sup&gt;&lt;/span&gt; While these methods provide detailed information on what, how much, and when individuals eat, involvement from dietitians or nutritionists can help to minimise errors.&lt;span&gt;&lt;sup&gt;3&lt;/sup&gt;&lt;/span&gt; However, misreporting remains inherent and can lead to misinterpretation of diet–disease relationships.&lt;span&gt;&lt;sup&gt;2&lt;/sup&gt;&lt;/span&gt; Controlled human feeding studies provide known amounts of foods/beverages and aim to mitigate inherent biases associated with self-reported dietary assessment while observing individual responses and enhancing adherence; however, they are also highly resource-intensive. The reliability and accuracy of dietary assessment methods have been shown to be increased by substituting or complementing dietary assessment instruments with objective biomarkers of food intake.&lt;span&gt;&lt;sup&gt;4-8&lt;/sup&gt;&lt;/span&gt; Currently, there are few valid dietary biomarkers routinely applied, for example, 24-h urinary sodium for salt,&lt;span&gt;&lt;sup&gt;9&lt;/sup&gt;&lt;/span&gt; plasma carotenoids for fruit and vegetables,&lt;span&gt;&lt;sup&gt;10&lt;/sup&gt;&lt;/span&gt; proline betaine for citrus fruits&lt;span&gt;&lt;sup&gt;11&lt;/sup&gt;&lt;/span&gt;; however, their application can be limited to a specific nutrient or food/food group.&lt;span&gt;&lt;sup&gt;11&lt;/sup&gt;&lt;/span&gt; Human feeding studies utilising metabolomics as an adjunct objective dietary assessment method are gaining traction.&lt;span&gt;&lt;sup&gt;12-14&lt;/sup&gt;&lt;/span&gt; However, the methodology of dietary feeding interventions can vary in their approach,&lt;span&gt;&lt;sup&gt;15&lt;/sup&gt;&lt;/span&gt; making cross-comparison between studies and synthesising dietary evidence difficult (see Box 1). Beyond the discovery of metabolites identified from biospecimens for qualifying and quantifying dietary intake of specific foods, nutrients and/or dietary patterns, metabolomics may also reflect the impact of diets on endogenous metabolism, accounting for individual variation driven by factors such as genetics and gut microbiome composition. For example, metabolites derived from the gut microbiome&lt;span&gt;&lt;sup&gt;16, 17&lt;/sup&gt;&lt;/span&gt; or produced through microbial conversion,&lt;span&gt;&lt;sup&gt;18, 19&lt;/sup&gt;&lt;/span&gt; contribute to the diverse metabolic responses to dietary interventions.&lt;span&gt;&lt;sup&gt;16&lt;/sup&gt;&lt;/span&gt; Therefore, metabolomics offers promise for future incorporation within precision and personalised nutrition interventions, ultimately advancing the broader field of nutrition research.&lt;span&gt;&lt;sup&gt;16&lt;/sup&gt;&lt;/span&gt;&lt;/p&gt;&lt;p&gt;While metabolomics is being rapidly integrated as a biological assessment technique in nutrition research,&lt;span&gt;&lt;sup&gt;20&lt;/sup&gt;&lt;/span&gt; it is still in its infancy and therefore improved quality of reporting is required to facilitate consistency, reproducibility of findings, and advancement of the field long-term.&lt;/p","PeriodicalId":12013,"journal":{"name":"European Journal of Clinical Investigation","volume":"55 7","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/eci.70030","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143794808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fatigue and itch severity in patients with PBC and PSC: Prospective analysis of two large cohorts","authors":"Beata Kruk,&nbsp;Joanna Raszeja-Wyszomirska,&nbsp;Marcin Krawczyk,&nbsp;Piotr Milkiewicz","doi":"10.1111/eci.70041","DOIUrl":"10.1111/eci.70041","url":null,"abstract":"<p>Primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC) are rare liver diseases that significantly impair quality of life (QoL). In this study, we analysed two large cohorts comprising a total of 1267 patients with PBC and PSC, showing that fatigue is a frequent symptom in both conditions, particularly among females. Fatigue was associated with liver function markers (ALP/GGT in PSC) and with cirrhosis (in PBC). It was also often linked to cholestatic pruritus, further compromising QoL.\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":12013,"journal":{"name":"European Journal of Clinical Investigation","volume":"55 7","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143771733","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":"Pulmonary hypertension and associated heart failure: New insights on emerging signalling pathways","authors":"Rosalinda Madonna,&nbsp;Elisa Montemaggi","doi":"10.1111/eci.70038","DOIUrl":"10.1111/eci.70038","url":null,"abstract":"<p>Pulmonary hypertension associated with left heart disease (PH-LHD) represents the hemodynamic condition at rest resulting from pathologies that affect the left ventricle and/or the left atrium. Among the left heart diseases, heart failure is the most frequent cause of PH. PH-LHD is the most common cause of PH, accounting for 65–80% of diagnoses. Several drugs targeting specific signalling pathways involved in the pulmonary remodelling in PH-LHD, including nitric oxide, MAP kinase and endothelin-1, have been tested in randomized clinical trials (RCTs), with disappointing results in terms of efficacy and safety. Therefore, PH-LHD still remains orphan of specific therapies able to counteract the pre- and post-capillary remodelling of the pulmonary circulation. In this article, we will discuss the pathophysiology and molecular mechanisms of PH-LHD. We will focus on the emerging signalling pathways involved in the pathophysiology of PH-LHD that could suggest novel molecular targets for the treatment of this condition.</p>","PeriodicalId":12013,"journal":{"name":"European Journal of Clinical Investigation","volume":"55 8","pages":""},"PeriodicalIF":4.4,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143735647","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}