{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T18:13:12Z","timestamp":1763748792103,"version":"build-2065373602"},"reference-count":29,"publisher":"MDPI AG","issue":"24","license":[{"start":{"date-parts":[[2022,12,18]],"date-time":"2022-12-18T00:00:00Z","timestamp":1671321600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJERPH"],"abstract":"<jats:p>Catheter-induced dissections (CID) of coronary arteries and\/or the aorta are among the most dangerous complications of percutaneous coronary procedures, yet the data on their risk factors are anecdotal. Logistic regression and five more advanced machine learning techniques were applied to determine the most significant predictors of dissection. Model performance comparison and feature importance ranking were evaluated. We identified 124 cases of CID in electronic databases containing 84,223 records of diagnostic and interventional coronary procedures from the years 2000\u20132022. Based on the f1-score, Extreme Gradient Boosting (XGBoost) was found to have the optimal balance between positive predictive value (precision) and sensitivity (recall). As by the XGBoost, the strongest predictors were the use of a guiding catheter (angioplasty), small\/stenotic ostium, radial access, hypertension, acute myocardial infarction, prior angioplasty, female gender, chronic renal failure, atypical coronary origin, and chronic obstructive pulmonary disease. Risk prediction can be bolstered with machine learning algorithms and provide valuable clinical decision support. Based on the proposed model, a profile of \u2018a perfect dissection candidate\u2019 can be defined. In patients with \u2018a clustering\u2019 of dissection predictors, a less aggressive catheter and\/or modification of the access site should be considered.<\/jats:p>","DOI":"10.3390\/ijerph192417002","type":"journal-article","created":{"date-parts":[[2022,12,19]],"date-time":"2022-12-19T05:55:43Z","timestamp":1671429343000},"page":"17002","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Forewarned Is Forearmed: Machine Learning Algorithms for the Prediction of Catheter-Induced Coronary and Aortic Injuries"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0406-7240","authenticated-orcid":false,"given":"Jacek","family":"Klaudel","sequence":"first","affiliation":[{"name":"Department of Invasive Cardiology and Interventional Radiology, St. Adalbert\u2019s Hospital, Copernicus PL, 80-462 Gda\u0144sk, Poland"},{"name":"Department of Cardiology, St. Vincent de Paul Hospital, Pomeranian Hospitals, 81-348 Gdynia, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2422-3666","authenticated-orcid":false,"given":"Barbara","family":"Klaudel","sequence":"additional","affiliation":[{"name":"Department of Decision Systems and Robotics, Faculty of Electronics, Telecommunications and Informatics, Gdansk University of Technology, 80-233 Gda\u0144sk, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1103-2943","authenticated-orcid":false,"given":"Micha\u0142","family":"Glaza","sequence":"additional","affiliation":[{"name":"Department of Cardiology, St. Vincent de Paul Hospital, Pomeranian Hospitals, 81-348 Gdynia, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1724-8892","authenticated-orcid":false,"given":"Wojciech","family":"Trenkner","sequence":"additional","affiliation":[{"name":"Department of Invasive Cardiology and Interventional Radiology, St. Adalbert\u2019s Hospital, Copernicus PL, 80-462 Gda\u0144sk, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3317-1837","authenticated-orcid":false,"given":"Pawe\u0142","family":"Derejko","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Medicover Hospital, 02-972 Warszawa, Poland"},{"name":"Cardiac Arrhythmias Department, National Institute of Cardiology, 04-628 Warszawa, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0367-4014","authenticated-orcid":false,"given":"Marek","family":"Szo\u0142kiewicz","sequence":"additional","affiliation":[{"name":"Department of Cardiology, St. Vincent de Paul Hospital, Pomeranian Hospitals, 81-348 Gdynia, Poland"},{"name":"Department of Cardiology and Interventional Angiology, Kashubian Center for Heart and Vascular Diseases, Pomeranian Hospitals, 84-200 Wejherowo, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,18]]},"reference":[{"key":"ref_1","first-page":"649","article-title":"Iatrogenic Catheter-Induced Ostial Coronary Artery Dissections: Prevalence, Management, and Mortality from a Cohort of 55,968 Patients over 10\u2009Years","volume":"98","author":"Ramasamy","year":"2021","journal-title":"Catheter. 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