ArticleScientific reports2024
Sarcopenia and adipose tissue evaluation by artificial intelligence predicts the overall survival after TAVI.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 11 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- CT-derived adipose tissue characteristics and TAVI all-cause mortality and complications: a systematic review.European journal of medical research · 2025Pooled it
- Prognostic value of sarcopenia in aortic valve replacement: a systematic review and meta-analysis.Frontiers in nutrition · 2025Pooled it
- Impact of preoperative sarcopenia on the mortality risk in patients undergoing transcatheter aortic valve implantation: a systematic review and meta-analysis.Journal of thoracic disease · 2026Article
- Imaging and biomarker-based risk stratification in TAVI: the role of epicardial fat, visceral fat, and adiponectin.European heart journal open · 2026Article
- CT-derived body composition as a predictor of supervised exercise therapy response in intermittent claudication and peripheral arterial disease: COMPOSE-PAD study protocol.Biomolecules & biomedicine · 2026Article
- Post-Operative Atrial Fibrillation: Novel Predictive Value of CT-Derived Adipose Tissue Density in Minimally Invasive Mitral Surgery.Physiological research · 2025Article
- Your CT scans are hiding crucial TAVI survival data: Are you looking?American heart journal plus : cardiology research and practice · 2025Article
- Applications of Artificial Intelligence in Transcatheter Aortic Valve Replacement: A Review of the Literature.Life (Basel, Switzerland) · 2025Review
- AI in Adipose Imaging: Revolutionizing Visceral Adipose Tissue, Ectopic Fat, and Cardiovascular Risk Assessment.Current atherosclerosis reports · 2025Review
- Beyond BMI: An opinion on the clinical value of AI-powered CT body composition analysis.Biomolecules & biomedicine · 2025Review
- Impact of Sarcopenia on Mortality in Patients Undergoing TAVI: A Follow-Up Study.Journal of clinical medicine · 2025Article
Corrections and comments
- Erratum issued
Authors and funding
11 authors.
Funding
Abstract
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
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.