Next-generation, Integrative, and Personalized Risk Assessment to Prevent Recurrent Heart Failure Events: the ORACLE Study

NCT05679713 | Unknown DMC

• 1 other identifier: PI21/00264
• Study Type: observational
• Target: 1,134
• Locations: 1 country
• Sites: 1

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).

Conditions

Heart Failure

Keywords

Machine Learning; Multi-Omics Approaches; Outcomes Research; Patient-Centered Information

Outcome Measures

Primary Outcomes (1)

• 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

  To compare in an external validation cohort of patients a recent acute HF event, the performance (discrimination, additive predictive value, and reclassification ability) of a comprehensive risk assessment algorithm with the performance of a traditional risk model to predict the occurrence of the primary composite clinical end-point of HF related hospitalizations (readmissions) or all-cause death at 180 days after hospital discharge or after an urgent HF visit (acute HF event requiring intravenous administration of diuretics without admission).

  6 months

Secondary Outcomes (3)

• 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.

  6 months

• 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.

  6 months

• 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.

  6 months

Other Outcomes (1)

• 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.

  6 months

Interventions

Comprehensive risk assessment algorithm DIAGNOSTIC_TEST

Risk assessment algorithm including clinical and patient-centered information and a novel RNA-based biomarkers using next-generation sequencing technology.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• 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.

You may qualify if:

• 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.

You may not qualify if:

• 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.

Sponsors & Collaborators

• Hospital Universitari de Bellvitge: lead

Study Sites (1)

University Hospital Bellvitge

L'Hospitalet de Llobregat, Barcelona, 08907, Spain

RECRUITING

MeSH Terms

Conditions

Heart Failure

Condition Hierarchy (Ancestors)

Heart Diseases; Cardiovascular Diseases

Central Study Contacts

Josep Comín Colet, MD, PhD

CONTACT

+34 932607078; jcomin@bellvitgehospital.cat

Raúl Ramos Polo, MD

CONTACT

+34 932607078; rramosp@bellvitgehospital.cat

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: CROSS SECTIONAL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Prof. Josep Comín-Colet, MD, PhD

Study Record Dates

• First Submitted: December 12, 2022
• First Posted: January 11, 2023
• Study Start: September 5, 2022
• Primary Completion: September 1, 2024
• Study Completion: December 1, 2024
• Last Updated: January 11, 2023

Record last verified: 2023-01

Data Sharing

• IPD Sharing: Will not share

Locations

ES (1)