Early Evaluation of Exosome Multiomics and Clinical Prognosis in Patients With Sudden Death

NCT ID: NCT06856993

Last Updated: 2025-03-04

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

300 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-12-22

Study Completion Date

2026-12-31

Brief Summary

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Acute coronary syndrome (ACS) is one of the main causes of death. Worldwide, tens of millions of patients are hospitalized for coronary heart disease and ACS every year. ACS may show acute myocardial infarction, unstable angina pectoris, and even induce early arrhythmia, leading to sudden death. Sudden cardiac death (SCD) has a strong correlation with ACS. Data from clinical and autopsy studies and death certificates show that 62-85% of patients with out of hospital SCD have a history of ACS, 10% have other cardiac structural abnormalities, and 5% have no cardiac structural abnormalities. An SCD surveillance study from Ireland concluded that most cases occurred in families, and the successful recovery of SCD was mainly related to ventricular fibrillation with arrhythmia. At present, there are few reports on the clinical and prognosis of ACS in China, and there is no guideline or consensus on the prevention and treatment of ACS patients. Known domestic research results show that the proportion of male, overweight / obese, smokers in young ACS patients is higher than that in the elderly group, while the proportion of patients with hypertension, diabetes and cerebrovascular diseases is less than that of the elderly group. The levels of TC, TG, LDL-C and UA and the proportion of low HDL-C in young ACS patients were higher than those in elderly patients; The diagnosis of STEMI was the highest in the young ACS group, while the diagnosis of unstable angina pectoris was the most common in the elderly ACS group. The clinical manifestations of ACS vary greatly. 3% \~ 5% of patients who exclude ACS only through myocardial markers, clinical blood transfusion and ECG still have myocardial infarction (MI). For the emergency department, early prediction of the risk of SCD in ACS patients and timely and accurate screening of high-risk patients are very important.

Detailed Description

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Conditions

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Sudden Cardiac Death Exosome Multiomics Clinical Prognosis

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Interventions

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standardized medical care of cardiac arrest

The standardized medical care for cardiac arrest includes early cardiopulmonary resuscitation (CPR), defibrillation, advanced cardiac life support (ACLS), post-resuscitation care, and continuous monitoring of the patient's vital functions.

Intervention Type PROCEDURE

Eligibility Criteria

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Inclusion Criteria

* The death event happens suddenly.
* Age ≥ 18 years
* The patient had obvious clinical symptoms 24 hours before treatment
* Life expectancy exceeds 3 days
* Proxy of patients signs the informed consent form
* Comply with ACS diagnostic indicators recommended by ACC / AHA guidelines in 2016

Exclusion Criteria

* Death caused by accident, such as trauma, poisoning, etc.
* Death from accidental or intentional overdose
* Death from asphyxia
* Death is caused by chronic disease or terminal illness
* The patient died naturally
* Has participated in other clinical studies
* Immediate family members give up continuing treatment
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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The Affiliated Nanjing Drum Tower Hospital of Nanjing University Medical School

OTHER

Sponsor Role lead

Responsible Party

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Hao Sun

MD

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Nanjing Drum Tower Hospital

Nanjing, Jiangsu, China

Site Status RECRUITING

Countries

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China

Facility Contacts

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Hao Sun, MD

Role: primary

8613584017821

Other Identifiers

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2021-SR-320

Identifier Type: -

Identifier Source: org_study_id

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