Clinical trial NCT06196307: Early Warning and Classification Model for Acute Non-traumatic Chest Pain
Official title: A Prospective Study of Acute Nontraumatic Chest Pain - Warning and Classification
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Chest Pain
Lead sponsor: Beijing Anzhen Hospital
Sponsor class: OTHER
First posted: 2024-01-09
Enrollment: 188
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: The study population included patients admitted to the chest pain center of the pilot hospital from August 2022 to December 2022 with chest pain (including tingling, burning pain, pressure, tightness, heartburn and similar discomfort) as the main manifestations. Screening of patients with chest pain is intended from the following sources:

1. outpatients with chest pain;
2. outpatients with a history of cardiovascular disease;
3. patients from other departments of the hospital referred to the cardiology outpatient clinic due to acute chest pain.

Brief summary: Acute non-traumatic chest pain is one of the common causes of presentation in emergency patients, but the causes of acute non-traumatic chest pain are complex, the severity of the condition varies greatly, and the specificity of symptoms is not high. Machine learning and intelligent auxiliary models can greatly shorten the time of clinical decision-making, and improve the accuracy of etiological diagnosis in patients with chest pain, reduce the rate of misdiagnosis and missed diagnosis, and provide a clear direction for further treatment.

Detailed description: Prospective observational studies used outpatient and follow-up information to construct an auxiliary early warning model of acute non-traumatic chest pain based on federated learning, and optimized the accuracy of early warning models through retrospective and prospective studies of large cohort data, and established an efficient and stable early warning and classification model for acute non-traumatic chest pain.

Eligibility criteria: Inclusion Criteria:

1. older than 18 years old;
2. provided written informed consent;
3. Outpatient visits in the pilot hospitals from June 2022 to December 2022

Exclusion Criteria:

1. did not provide written informed consent and were unwilling to be followed up;
2. traumatic chest pain;
3. systemic pain caused by malignant tumors or rheumatic diseases involving the chest;
4. transferred patients;
5. sudden death or death during hospital treatment;
6. women who are known to be pregnant or lactating;
7. have participated in other clinical trials within 3 months before enrolling in this trial or are currently participating in other clinical trials The lender;
8. According to the investigator's judgment, the patient was unable to complete the study or comply with the requirements of the study;
9. Patients were lost to follow-up.

Primary outcomes:
measure: Ecg findings of myocardial infarction, inverted T wave or soaring T wave, ST segment elevation, pathological Q wave, etc.
timeFrame: Baseline and week 12
measure: Myocardial injury marker level (cTn/CK-MB/MYO) level
timeFrame: Baseline and week 12
measure: Achieve HEART score levels 7-10 (high-risk patients) ratio.
timeFrame: Baseline and week 12
measure: Incidence of cardiovascular events (CV death, all-cause death, fatal MI, nonfatal stroke).
timeFrame: Week 12
Secondary outcomes:
Other outcomes:
measure: Differences in accuracy in diagnosing acute non-traumatic chest pain using machine learning and intelligence-assisted models and existing scoring systems.
timeFrame: Week 12
Locations:
city: Beijing
country: China
facility: Xiaonan He
state: Chaoyang
Study officials:
References: