Sarcopenia and adipose tissue evaluation by artificial intelligence predicts the overall survival after TAVI

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00159816%3A_____%2F24%3A00080716" target="_blank" >RIV/00159816:_____/24:00080716 - isvavai.cz</a>

Alternative codes found

RIV/00216224:14110/24:00135825 RIV/61989100:27240/24:10257244

Result on the web

<a href="https://www.nature.com/articles/s41598-024-59134-z" target="_blank" >https://www.nature.com/articles/s41598-024-59134-z</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1038/s41598-024-59134-z" target="_blank" >10.1038/s41598-024-59134-z</a>

Result language

angličtina

Original language name

Sarcopenia and adipose tissue evaluation by artificial intelligence predicts the overall survival after TAVI

Original language description

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/m(2). Survival analysis was performed on all automatically obtained parameters of muscle and fat density and area. Skeletal muscle index (SMI in cm(2)/m(2)), 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 &lt; 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.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

30200 - Clinical medicine

Project

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Continuities

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Scientific Reports

ISSN

2045-2322

e-ISSN

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Volume of the periodical

14

Issue of the periodical within the volume

1

Country of publishing house

US - UNITED STATES

Number of pages

9

Pages from-to

8842

UT code for WoS article

001205348700026

EID of the result in the Scopus database

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