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The aim of this study is to develop and validate an improved, comprehensive risk assessment algorithm integrating blood RNA-based biomarkers, clinical, and patient-centered data and to assess the incremental predictive value (discrimination and reclassification) compared to a traditional risk model (change in the c-statistics for prediction of the primary endpoint).
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The ORACLE study is a multicenter, observational, prospective, cross-sectional and longitudinal study integrated by 3 different cohorts for 1) RNA biomarker discovery (60 nested case-control sample), 2) model derivation (516 nested case-control sample) and 3) external validation (new prospective cohort of 558 consecutive patients recruited in 4 hospital centers) according to a TRIPOD Statement type 3 analysis. In total 1134 consecutive patients with a HF hospitalization or urgent HF visit < 30 days before inclusion and followed for 6 months will be studied.
This study include the discovery of novel RNA-based biomarkers using next-generation sequencing technology to define and validate a new biomarker set and clinical and patient-centered risk determinants definition. A new model will be constructed; training and internal validation in the derivation cohort using machine learning methods, and finally an external validation of the new next generation integrative risk assessment model will be performed.
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Raúl Ramos Polo, MD; Josep Comín Colet, MD, PhD
Data sourced from clinicaltrials.gov
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