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[FG] Boeddinghaus Jasper

Publications

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Koechlin, L. et al. (2025) ‘Impact of Food and Drug Administration Regulations on the Performance of Guideline‐Recommended Pathways With an Approved Point‐of‐Care High‐Sensitivity Cardiac Troponin I Assay’, Journal of the American Heart Association [Preprint]. Available at: https://doi.org/10.1161/jaha.124.039164.

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Papachristou, Androniki et al. (2025) ‘Terminal renal failure as a contributor to high-sensitivity cardiac troponin T elevations: insights from patients undergoing renal transplantation’, Heart, p. Online ahead of print. Available at: https://doi.org/10.1136/heartjnl-2024-324686.

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Haaf, P. et al. (2025) ‘Heatstroke-induced thromboembolic myocardial infarction’, European Heart Journal - Cardiovascular Imaging [Preprint]. Available at: https://doi.org/10.1093/ehjci/jeaf053.

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Chapman, Andrew R et al. (2025) ‘Type 2 myocardial infarction: challenges in diagnosis and treatment’, European Heart Journal, 46(6), pp. 504–517. Available at: https://doi.org/10.1093/eurheartj/ehae803.

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Koechlin, Luca et al. (2025) ‘Diagnostic and Prognostic Performance of High-Sensitivity Cardiac Troponin T vs I’, Journal of the American College of Cardiology, 85(4), pp. 381–385. Available at: https://doi.org/10.1016/j.jacc.2024.10.076.

Jasper Boeddinghaus et al. (2025) ‘Implications of a new clinical classification of acute myocardial infarction’, European Heart Journal Acute Cardiovascular Care [Preprint]. Available at: https://doi.org/10.1093/ehjacc/zuaf002.

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Minder, Judith et al. (2024) ‘Impact of new-onset atrial fibrillation in patients with ST-segment elevation myocardial infarction’, Journal of Interventional Cardiac Electrophysiology [Preprint]. Available at: https://doi.org/10.1007/s10840-024-01941-5.

Stolte, Thorald et al. (2024) ‘The impact of myocardial injury on outcomes in TAVI patients’, Clinical Research in Cardiology [Preprint]. Available at: https://doi.org/10.1007/s00392-024-02585-1.

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Li, Z., Boeddinghaus, J. and Mills, N.L. (2024) ‘Cardiac Troponin I or T for the Diagnosis of Myocardial Infarction and Prediction of Outcomes—Does It Matter?’, Clinical Chemistry, 70(10), pp. 1197–1199. Available at: https://doi.org/10.1093/clinchem/hvae123.

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Koechlin, Luca et al. (2024) ‘Clinical and Analytical Performance of a Novel Point-of-Care High-Sensitivity Cardiac Troponin I Assay’, Journal of the American College of Cardiology, 84(8), pp. 726–740. Available at: https://doi.org/10.1016/j.jacc.2024.05.056.

Than, Martin P et al. (2024) ‘Clinical decision support using machine learning and cardiac troponin for the diagnosis of myocardial infarction’, European Heart Journal: Acute Cardiovascular Care [Preprint]. Available at: https://doi.org/10.1093/ehjacc/zuae085.

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Lopez-Ayala, Pedro et al. (2024) ‘External validation of the myocardial-ischaemic-injury-index machine learning algorithm for the early diagnosis of myocardial infarction: a multicentre cohort study’, The Lancet Digital Health, 6(7), pp. e480–e488. Available at: https://doi.org/10.1016/s2589-7500(24)00088-8.

Lee, Kuan Ken et al. (2024) ‘Clinical decision support using machine learning and natriuretic peptides for the diagnosis of acute heart failure’, European Heart Journal: Acute Cardiovascular Care, 13(6), pp. 515–516. Available at: https://doi.org/10.1093/ehjacc/zuae064.

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Reichl, Jakob Johannes et al. (2024) ‘Prognostic Impact of Left Ventricular Ejection Fraction Improvement after Transcatheter Aortic Valve Replacement’, Journal of Clinical Medicine, 13(13), p. 3639. Available at: https://doi.org/10.3390/jcm13133639.

Li, Ziwen et al. (2024) ‘Uniform or Sex-Specific Cardiac Troponin Thresholds to Rule Out Myocardial Infarction at Presentation’, Journal of the American College of Cardiology, 83(19), pp. 1855–1866. Available at: https://doi.org/10.1016/j.jacc.2024.03.365.

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Boeddinghaus, Jasper et al. (2024) ‘Machine Learning for Myocardial Infarction Compared With Guideline-Recommended Diagnostic Pathways’, Circulation, 149(14), pp. 1090–1101. Available at: https://doi.org/10.1161/CIRCULATIONAHA.123.066917.

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Boeddinghaus, Jasper et al. (2024) ‘Machine Learning for Myocardial Infarction Compared With Guideline-Recommended Diagnostic Pathways’, Circulation, 149(14), pp. 1090–1101. Available at: https://doi.org/10.1161/circulationaha.123.066917.

Jobs, Alexander et al. (2024) ‘GRACE scores or high-sensitivity troponin for timing of coronary angiography in non-ST-elevation acute coronary syndromes’, Clinical Research in Cardiology, 113(4), pp. 533–545. Available at: https://doi.org/10.1007/s00392-023-02258-5.

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Boeddinghaus, Jasper, Chapman, Andrew R. and Henriksen, Peter A. (2024) ‘Acute chest pain in a young man with low cardiovascular risk profile’, Heart, 110(4). Available at: https://doi.org/10.1136/heartjnl-2023-323398.

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Pedro Lopez-Ayala et al. (2024) ‘External validation of the myocardial-ischaemic-injuryindex machine learning algorithm for the early diagnosis of myocardial infarction: a multicentre cohort study’, Lancet Digit Health [Preprint].

Lowry, Matthew T. H. et al. (2023) ‘Troponin in early presenters to rule out myocardial infarction’, European Heart Journal, 44(30), pp. 2846–2858. Available at: https://doi.org/10.1093/eurheartj/ehad376.

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Fernández-Cisnal A et al. (2023) ‘Performance of an artificial intelligence chatbot with web search capability in cardiology-related assistance: a simulation study.’ Available at: https://doi.org/10.1016/j.rec.2023.06.008.

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Rubini Gimenez M et al. (2023) ‘Implementation of the ESC 0 h/1 h high-sensitivity troponin algorithm for decision-making in the emergency department.’, Revista espanola de cardiologia (English ed.), 76(6), pp. 468–472. Available at: https://doi.org/10.1016/j.rec.2023.01.002.

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Doudesis, Dimitrios et al. (2023) ‘Machine learning for diagnosis of myocardial infarction using cardiac troponin concentrations’, Nature Medicine, 29(5), pp. 1201–1210. Available at: https://doi.org/10.1038/s41591-023-02325-4.

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Taggart, Caelan et al. (2023) ‘Improving Risk Stratification for Patients With Type 2 Myocardial Infarction’, Journal of the American College of Cardiology, 81(2), pp. 156–168. Available at: https://doi.org/10.1016/j.jacc.2022.10.025.

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Boeddinghaus J et al. (2021) ‘Diagnostic Performance of the European Society of Cardiology 0/1-h Algorithms in Late Presenters’, 77(9). Available at: https://doi.org/10.1016/j.jacc.2021.01.004.

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Boeddinghaus, Jasper et al. (2020) ‘Early Diagnosis of Myocardial Infarction With Point-of-Care High-Sensitivity Cardiac Troponin I’, Journal of the American College of Cardiology, 75(10), pp. 1111–1124. Available at: https://doi.org/10.1016/j.jacc.2019.12.065.

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Neumann JT et al. (2019) ‘Application of high-sensitivity troponin in suspected myocardial infarction’, New England Journal of Medicine, 380(26), pp. 2529–2540. Available at: https://doi.org/10.1056/NEJMoa1803377.

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Boeddinghaus, Jasper et al. (2019) ‘Clinical Use of a New High-Sensitivity Cardiac Troponin I Assay in Patients with Suspected Myocardial Infarction’, Clinical Chemistry, 65(11), pp. 1426–1436. Available at: https://doi.org/10.1373/clinchem.2019.304725.

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Boeddinghaus J et al. (2019) ‘High-sensitivity cardiac troponin i assay for early diagnosis of acute myocardial infarction’, Clinical Chemistry, 65(7), pp. 893–904. Available at: https://doi.org/10.1373/clinchem.2018.300061.

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Koechlin, Luca et al. (2019) ‘Early Diagnosis of Myocardial Infarction in Patients With a History of Coronary Artery Bypass Grafting’, Journal of the American College of Cardiology, 74(4), pp. 587–589. Available at: https://doi.org/10.1016/j.jacc.2019.05.044.

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Badertscher, Patrick et al. (2018) ‘Direct Comparison of the 0/1h and 0/3h Algorithms for Early Rule-Out of Acute Myocardial Infarction’, Circulation, 137(23), pp. 2536–2538. Available at: https://doi.org/10.1161/circulationaha.118.034260.

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Boeddinghaus, Jasper et al. (2018) ‘Impact of age on the performance of the ESC 0/1h-algorithms for early diagnosis of myocardial infarction’, European heart journal, 39(42), pp. 3780–3794. Available at: https://doi.org/10.1093/eurheartj/ehy514.

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