{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,12]],"date-time":"2026-08-12T08:37:44Z","timestamp":1786523864330,"version":"build-2736575974"},"reference-count":31,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T00:00:00Z","timestamp":1786406400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Med. Sci.","Medical Sciences"],"abstract":"<jats:p>Background\/Objectives: Pleural effusions are frequently encountered on pre-procedural computed tomography (CT) scans in patients undergoing transcatheter aortic valve implantation (TAVI). While often regarded as a marker of congestion and advanced cardiovascular disease, their clinical and prognostic significance in contemporary TAVI populations remains poorly understood. This study investigated the relationship between AI-derived pleural effusion volume, cardiovascular dysfunction, and long-term mortality after TAVI. Methods: Consecutive patients undergoing transfemoral TAVI between 2016 and 2022 who had available pre-procedural CT imaging were retrospectively included. Pleural effusion volume was quantified using an artificial intelligence-based segmentation workflow and analyzed as categorical, continuous, log-transformed, and threshold-based variables. Associations with clinical and echocardiographic characteristics were evaluated using Spearman correlation analyses. Long-term mortality was assessed using Kaplan\u2013Meier analysis, Cox proportional hazards regression, and restricted cubic spline models. Results: A total of 470 patients were included (median age 82 years, 50.9% male). Pleural effusion was present in 124 patients (26.38%), including 73 (15.53%) with small, 26 (5.53%) with moderate, and 25 (5.32%) with larger effusions. Increasing pleural effusion volume was associated with atrial fibrillation (AF) (rho = 0.189, p &lt; 0.001), higher systolic pulmonary artery pressure (rho = 0.224, p &lt; 0.001), lower tricuspid annular plane systolic excursion (rho = \u22120.236, p &lt; 0.001), impaired right ventricular\u2013pulmonary arterial coupling (rho = \u22120.267, p &lt; 0.001), lower stroke volume index (rho = \u22120.229, p &lt; 0.001), and reduced left ventricular ejection fraction (rho = \u22120.221, p &lt; 0.001). Despite these associations, pleural effusion volume was not associated with long-term mortality in univariable analyses, multivariable Cox regression models, or restricted cubic spline analyses. In the fully adjusted model, log-transformed pleural effusion volume was not independently associated with mortality (HR 1.00, 95% CI 0.93\u20131.08; p = 0.976). Conclusions: AI-derived pleural effusion volume is associated with markers of cardiovascular congestion and adverse hemodynamic remodeling in patients undergoing TAVI. However, pleural effusion burden does not independently predict long-term mortality, suggesting that its value lies primarily in phenotyping cardiovascular disease severity rather than risk stratification.<\/jats:p>","DOI":"10.3390\/medsci14040472","type":"journal-article","created":{"date-parts":[[2026,8,11]],"date-time":"2026-08-11T16:30:32Z","timestamp":1786465832000},"page":"472","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["More than Fluid: AI-Derived Pleural Effusion Volume as a Marker of Cardiovascular Congestion in Transcatheter Aortic Valve Implantation"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1842-0578","authenticated-orcid":false,"given":"Nikolaos","family":"Sch\u00f6rghofer","sequence":"first","affiliation":[{"name":"Department of Radiology, Paracelsus Medical University of Salzburg, 5020 Salzburg, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3443-9943","authenticated-orcid":false,"given":"Nikolaus","family":"Clodi","sequence":"additional","affiliation":[{"name":"Department of Radiology, Paracelsus Medical University of Salzburg, 5020 Salzburg, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gretha","family":"Hecke","sequence":"additional","affiliation":[{"name":"Division of Cardiology, Department of Internal Medicine II, Paracelsus Medical University of Salzburg, M\u00fcllner Hauptstra\u00dfe 48, 5020 Salzburg, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Matthias","family":"Hammerer","sequence":"additional","affiliation":[{"name":"Division of Cardiology, Department of Internal Medicine II, Paracelsus Medical University of Salzburg, M\u00fcllner Hauptstra\u00dfe 48, 5020 Salzburg, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3429-2203","authenticated-orcid":false,"given":"Alexander","family":"Kupferthaler","sequence":"additional","affiliation":[{"name":"Department of Radiology, Paracelsus Medical University of Salzburg, 5020 Salzburg, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bernhard","family":"Scharinger","sequence":"additional","affiliation":[{"name":"Department of Radiology, Paracelsus Medical University of Salzburg, 5020 Salzburg, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Uta C.","family":"Hoppe","sequence":"additional","affiliation":[{"name":"Division of Cardiology, Department of Internal Medicine II, Paracelsus Medical University of Salzburg, M\u00fcllner Hauptstra\u00dfe 48, 5020 Salzburg, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-6571-8296","authenticated-orcid":false,"given":"Klaus","family":"Hergan","sequence":"additional","affiliation":[{"name":"Department of Radiology, Paracelsus Medical University of Salzburg, 5020 Salzburg, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6589-3853","authenticated-orcid":false,"given":"Elke","family":"Boxhammer","sequence":"additional","affiliation":[{"name":"Department of Radiology, Paracelsus Medical University of Salzburg, 5020 Salzburg, Austria"},{"name":"Division of Cardiology, Department of Internal Medicine II, Paracelsus Medical University of Salzburg, M\u00fcllner Hauptstra\u00dfe 48, 5020 Salzburg, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0656-7038","authenticated-orcid":false,"given":"Christoph","family":"Knapitsch","sequence":"additional","affiliation":[{"name":"Department of Radiology, Paracelsus Medical University of Salzburg, 5020 Salzburg, Austria"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1590\/0100-3984.2021.0156","article-title":"Computed tomography angiography in the planning of transcatheter aortic valve replacement: A step-by-step approach","volume":"55","author":"Pontes","year":"2022","journal-title":"Radiol. 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