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Prediction model for myocardial injury after non-cardiac surgery using machine learning

Prediction model for myocardial injury after non-cardiac surgery using machine learning

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600117606
Enrollment
Unknown
Registered
2026-01-27
Start date
2025-01-02
Completion date
Unknown
Last updated
2026-02-02

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

Conditions

myocardial injury after noncardiac surgery,MINS

Interventions

Case series:N/A

Sponsors

Zhongshan Hospital Affiliated to Fudan University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 100 Years

Inclusion criteria

Inclusion criteria: 1. Patients who were admitted to our hospital for noncardiac surgery and had at least one cTn measurement before or within 30 days after surgery were enrolled; 2. Fasting blood samples were collected within 1 week before and 5 days after surgery.

Exclusion criteria

Exclusion criteria: 1. patients younger than 18 years of age 2. patients without preoperative or postoperative cTn data 3. patients with elevated preoperative cTn levels 4. patients with a clear nonischemic cause of elevated cTn, such as pulmonary embolism, sepsis, cardioversion, or atrial fibrillation

Design outcomes

Primary

MeasureTime frame
Peak cTn within 30 days after surgery;Model evaluation indicators: accuracy, sensitivity, specificity, ROC curve and AUC;—

Countries

China

Contacts

Public ContactWu Qichao

Zhongshan Hospital Affiliated to Fudan University

wu.qichao@zs-hospital.shcn+86 186 2150 7737

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 7, 2026