PEKAŘ, Matej, Otakar JIRAVSKÝ, Jan NOVÁK, Piotr BRANNY, Jakub BALUŠÍK, Daniel DANIŠ, Jan HEČKO, Marek KANTOR, Robert PROSECKÝ, Lubomír BLAHA a Radek NEUWIRTH. Sarcopenia and adipose tissue evaluation by artificial intelligence predicts the overall survival after TAVI. SCIENTIFIC REPORTS. BERLIN: NATURE PORTFOLIO, 2024, roč. 14, č. 1, s. 1-9. ISSN 2045-2322. Dostupné z: https://dx.doi.org/10.1038/s41598-024-59134-z. |
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@article{2394829, author = {Pekař, Matej and Jiravský, Otakar and Novák, Jan and Branny, Piotr and Balušík, Jakub and Daniš, Daniel and Hečko, Jan and Kantor, Marek and Prosecký, Robert and Blaha, Lubomír and Neuwirth, Radek}, article_location = {BERLIN}, article_number = {1}, doi = {http://dx.doi.org/10.1038/s41598-024-59134-z}, keywords = {Sarcopenia; Artifcial intelligence; Visceral adipose tissue; Subcutaneous adipose tissue; Survival; TAVI}, language = {eng}, issn = {2045-2322}, journal = {SCIENTIFIC REPORTS}, title = {Sarcopenia and adipose tissue evaluation by artificial intelligence predicts the overall survival after TAVI}, url = {https://link.springer.com/article/10.1038/s41598-024-59134-z?utm_source=rct_congratemailt&utm_medium=email&utm_campaign=oa_20240417&utm_content=10.1038/s41598-024-59134-z}, volume = {14}, year = {2024} }
TY - JOUR ID - 2394829 AU - Pekař, Matej - Jiravský, Otakar - Novák, Jan - Branny, Piotr - Balušík, Jakub - Daniš, Daniel - Hečko, Jan - Kantor, Marek - Prosecký, Robert - Blaha, Lubomír - Neuwirth, Radek PY - 2024 TI - Sarcopenia and adipose tissue evaluation by artificial intelligence predicts the overall survival after TAVI JF - SCIENTIFIC REPORTS VL - 14 IS - 1 SP - 1-9 EP - 1-9 PB - NATURE PORTFOLIO SN - 20452322 KW - Sarcopenia KW - Artifcial intelligence KW - Visceral adipose tissue KW - Subcutaneous adipose tissue KW - Survival KW - TAVI UR - https://link.springer.com/article/10.1038/s41598-024-59134-z?utm_source=rct_congratemailt&utm_medium=email&utm_campaign=oa_20240417&utm_content=10.1038/s41598-024-59134-z N2 - Sarcopenia is a serious systemic disease that reduces overall survival. TAVI is selectively performed in patients with severe aortic stenosis who are not indicated for open cardiac surgery due to severe polymorbidity. Artificial intelligence-assisted body composition assessment from available CT scans appears to be a simple tool to stratify these patients into low and high risk based on future estimates of all-cause mortality. Within our study, the segmentation of preprocedural CT scans at the level of the lumbar third vertebra in patients undergoing TAVI was performed using a neural network (AutoMATiCA). The obtained parameters (area and density of skeletal muscles and intramuscular, visceral, and subcutaneous adipose tissue) were analyzed using Cox univariate and multivariable models for continuous and categorical variables to assess the relation of selected variables with all-cause mortality. 866 patients were included (median(interquartile range)): age 79.7 (74.9–83.3) years; BMI 28.9 (25.9–32.6) kg/m2. Survival analysis was performed on all automatically obtained parameters of muscle and fat density and area. Skeletal muscle index (SMI in cm2/m2), visceral (VAT in HU) and subcutaneous adipose tissue (SAT in HU) density predicted the all-cause mortality in patients after TAVI expressed as hazard ratio (HR) with 95% confidence interval (CI): SMI HR 0.986, 95% CI (0.975–0.996); VAT 1.015 (1.002–1.028) and SAT 1.014 (1.004–1.023), all p < 0.05. Automatic body composition assessment can estimate higher all-cause mortality risk in patients after TAVI, which may be useful in preoperative clinical reasoning and stratification of patients. ER -
PEKAŘ, Matej, Otakar JIRAVSKÝ, Jan NOVÁK, Piotr BRANNY, Jakub BALUŠÍK, Daniel DANIŠ, Jan HEČKO, Marek KANTOR, Robert PROSECKÝ, Lubomír BLAHA a Radek NEUWIRTH. Sarcopenia and adipose tissue evaluation by artificial intelligence predicts the overall survival after TAVI. \textit{SCIENTIFIC REPORTS}. BERLIN: NATURE PORTFOLIO, 2024, roč.~14, č.~1, s.~1-9. ISSN~2045-2322. Dostupné z: https://dx.doi.org/10.1038/s41598-024-59134-z.
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