Clinical trial NCT05679713: Next-generation, Integrative, and Personalized Risk Assessment to Prevent Recurrent Heart Failure Events: the ORACLE Study
Official title: Next-generation, Integrative, and Personalized Risk Assessment to Prevent Recurrent Heart Failure Events: the ORACLE Study
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Heart Failure
Keywords: Machine Learning
Multi-Omics Approaches
Outcomes Research
Patient-Centered Information
Lead sponsor: Hospital Universitari de Bellvitge
Sponsor class: OTHER
First posted: 2023-01-11
Enrollment: 1134
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: OTHER
Time perspective: CROSS_SECTIONAL
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The external validation cohort will be a multicenter, observational, prospective, cross-sectional and longitudinal cohort recruited for the specific purpose of the ORACLE study. The investigators plan to recruit patients with a recent (\<30 days) acute HF event and follow them for 180 days. The study will be conducted in 4 different hospitals (University Hospital Bellvitge, Viladecans General Hospital, Vic General Hospital and Igualada General Hospital) covering a total healthcare area of \> 650.000 inhabitants.

Brief summary: 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).

Detailed description: 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.

Eligibility criteria: Inclusion Criteria:

* Age ≥ 18 years old.
* Patients with a recent (\<30 days) acute decompensation of HF requiring intravenous diuretic therapy (either hospitalized or in ambulatory care) or intensification of oral diuretics (ambulatory care).
* HF diagnosis according to European Society of Cardiology (ESC) criteria.
* Written informed consent
* Patients receiving oral standard medication for chronic HF.

Exclusion Criteria:

* Age\<18 years old.
* Death before hospital discharge.
* The patient is unable or unwilling to give the informed consent to participate.
* Unstable patients with signs of fluid overload or low cardiac output at the moment of enrollment.

Primary outcomes:
measure: To compare the model performance of the comprehensive risk assessment algorithm with a traditional risk model to predict HF related hospitalizations or all-cause death
timeFrame: 6 months
Secondary outcomes:
measure: To compare the model performance of the comprehensive risk assessment algorithm with a traditional risk model to predict the occurrence of HF-related hospitalizations (readmissions) or all-cause death at 30, and 90 days after hospital discharge.
timeFrame: 6 months
measure: To compare the model performance of the comprehensive risk assessment algorithm with a traditional risk model to predict the occurrence of HF-related hospitalizations (readmissions) at 30, 90, and 180 days after hospital discharge.
timeFrame: 6 months
measure: To compare the model performance of the comprehensive risk assessment algorithm with a traditional risk model to predict the occurrence of all-cause death at 30, 90, and 180 days, after hospital discharge.
timeFrame: 6 months
Other outcomes:
measure: Explore the performance (sensibility and specificity) of the developed model according gender, LVEF (preserved or reduced left ventricle ejection fraction), comorbidity burden (Charlson Comorbidity Index) and frailty.
timeFrame: 6 months
Locations:
city: L'Hospitalet de Llobregat
country: Spain
facility: University Hospital Bellvitge
state: Barcelona
Study officials:
References: