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Machine Learning-Based Prognostic Prediction Model for Post-PCI Patients with Coronary Heart Disease Complicated by Heart Failure

Machine Learning-Based Prognostic Prediction Model for Post-PCI Patients with Coronary Heart Disease Complicated by Heart Failure

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600126292
Enrollment
Unknown
Registered
2026-06-05
Start date
2026-06-20
Completion date
Unknown
Last updated
2026-06-08

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

Conditions

Coronary atherosclerotic heart disease, Heart failure

Interventions

Modeling group:None
Validation group:None

Sponsors

Meishan City Peoples Hospital
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.Meets the diagnostic criteria for coronary artery disease (CAD): at least 1 major coronary artery with =50% diameter stenosis confirmed by coronary angiography. 2.Meets the diagnostic criteria for heart failure (HF): diagnosed in accordance with the 2022 Chinese Guidelines for the Diagnosis and Treatment of Heart Failure, with preoperative NYHA functional class II–IV. 3.Successfully underwent PCI revascularization, with complete procedural records available. 4.Complete perioperative baseline clinical data, able to complete standardized 1-year postoperative follow-up, and traceable key outcome data. 5.Age >=18 years.

Exclusion criteria

Exclusion criteria: 1.Concomitant congenital heart disease, severe valvular heart disease, hypertrophic cardiomyopathy, restrictive cardiomyopathy, or other structural heart diseases. 2.Concomitant malignant tumors, end-stage liver or renal failure, severe hematological diseases, or other conditions with an expected survival of <1 year. 3.PCI failure, emergency conversion to coronary artery bypass grafting (CABG) during the procedure, or perioperative fatal complications. 4.Loss to follow-up within 1 year postoperatively, or severe missing data on core clinical characteristics and endpoint events. 5.Obvious logical errors in clinical data, or data quality insufficient to meet modeling requirements.

Design outcomes

Primary

MeasureTime frame
All cause death;

Secondary

MeasureTime frame
Heart failure readmission;

Countries

China

Contacts

Public ContactDing Jingwen

Meishan City Peoples Hospital

djw1993174385@163.com+86 28 38025152

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Jun 11, 2026