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Multimodal Prognostic System for Heart Failure: A Multi-Center Study

Developing a Prognostic Warning System for Heart Failure Based on Multimodal Clinical Data: a Multi-center Retrospective Study

Status
Not yet recruiting
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT06558448
Enrollment
100000
Registered
2024-08-16
Start date
2024-08-31
Completion date
2024-12-31
Last updated
2024-08-16

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Heart Failure

Brief summary

This study is a multicenter retrospective research aimed at developing a heart failure prognosis warning system based on multimodal clinical data to improve the diagnosis and treatment of heart failure. This study aims to address the following main questions: 1. What are the clinical characteristics and current treatment status of heart failure patients? 2. What factors influence the onset of heart failure and the prognosis of patients? 3. How can real-world big data be utilized to construct an accurate heart failure prognosis assessment model? 4. How can this prognosis assessment model help improve the therapeutic effects and quality of life for heart failure patients?

Interventions

None listed

Sponsors

Chongqing Medical University
Lead SponsorOTHER

Study design

Observational model
COHORT
Time perspective
PROSPECTIVE

Eligibility

Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No

Inclusion criteria

Age Requirement: We plan to include adult patients aged 18 and above to ensure the study covers a broad spectrum of the adult heart failure patient population. Diagnostic Criteria: Patients should have a discharge diagnosis of heart failure according to the guidelines for heart failure diagnosis and treatment. Time Frame: The discharge time of patients should be between January 2011 and December 2024 to collect and analyze data from the past several years. Data Integrity: There is a preference for including medical records with high data integrity, but the specific criteria may be adjusted according to the actual situation of the dataset.

Exclusion criteria

Data Missing: Patients with more than 30% missing data in their medical records may be considered for exclusion to ensure the accuracy and reliability of the analysis. Diagnostic Inconsistency: Patients with unclear diagnoses or potential for confusion with other diseases may be excluded to ensure the specificity of the study. Non-standard Treatment: Patients who have not received treatment according to the established treatment protocol may be excluded to reduce the impact of treatment variability on the study results.

Design outcomes

Primary

MeasureTime frameDescription
In-hospital mortality or other adverse outcomes, including readmission, in-hospital infection, respiratory failure, liver failure, and renal failure.Evaluations will be conducted within 30, 60, or 90 days post-admission for heart failure patients to assess the impact of the condition and the effectiveness of treatment.The study focuses on evaluating the risk factors and predictors of in-hospital mortality and various adverse outcomes in heart failure patients, encompassing events such as readmission due to exacerbation of the condition, infections acquired during hospital stay, critical impairments in respiratory, liver, and kidney functions that may complicate the clinical course and impact patient prognosis.

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026