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Risk Stratification Value of Biomarkers in Patients With Myocarditis (FORWARD)

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Xi'an Jiaotong University

Status

Enrolling

Conditions

Myocarditis

Study type

Observational

Funder types

Other

Identifiers

NCT06010199
XJTU1AF2023LSK-169

Details and patient eligibility

About

The aim of this study is to collect clinical data and biological specimens from patients with myocarditis and construct a predictive model for the prognosis of myocarditis.

Full description

The aim of this study is to retrospectively and prospectively collect clinical data and biological specimens from patients with myocarditis who meet the inclusion and exclusion criteria. General molecular biology analysis, genome sequencing, transcriptome sequencing, methylation sequencing, metabolomics analysis, proteomics analysis, genome-wide chromosome conformation capture and other techniques are used to construct a prognosis prediction model for myocarditis.

Enrollment

1,000 estimated patients

Sex

All

Ages

3 to 80 years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • All patients should meet the diagnostic criteria for myocarditis
  • Patients who are regularly followed up at the corresponding cardiovascular center

Exclusion criteria

  • Age <3 years or >80 years
  • Pregnant or lactating women
  • The patient refused to sign the informed consent and refused to participate in the study
  • None of the above is consistent, but the patient cannot sign the informed consent temporarily due to coma and other reasons, and there is no legal representative to sign it instead. Depending on the condition, the patient may not wake up to sign the informed consent

Trial design

1,000 participants in 1 patient group

Myocarditis group
Description:
All enrolled patients are administered antiviral drugs, glucocorticoids, immunoglobulins, and other standard treatments. Additionally, the decision to provide ECMO support therapy is based on the severity of the patient's condition.

Trial contacts and locations

1

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Central trial contact

Yang Yan; Guoliang Li

Data sourced from clinicaltrials.gov

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