ArticlemedRxiv : the preprint server for health sciences2024
Application of Principal Component Analysis to Heterogenous Fontan Registry Data Identifies Independent Contributing Factors to Decline.
Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
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Abstract
Single ventricle heart disease is a severe and life-threatening illness, and improvements in clinical outcomes of those with Fontan circulation have not yet yielded acceptable survival over the past two decades. Patients are at risk of developing a diverse variety of Fontan-associated comorbidities that ultimately requires heart transplant. Our observational cohort study goal was to determine if principal component analysis (PCA) applied to data collected from a substantial Fontan cohort can predict functional decline (N=140). Heterogeneous data broadly consisting of measures of cardiac and vascular function, exercise (VO
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