Development and validation of a model integrating clinical and coronary lesion-based functional assessment for long-term risk prediction in PCI patients
Shao-Yu WU1
Rui ZHANG1
Sheng YUAN1
Zhong-Xing CAI1
Chang-Dong GUAN2
Tong-Qiang ZOU2
Li-Hua XIE2
Ke-Fei DOU3
1.State Key Laboratory of Cardiovascular Disease,Beijing,China;Cardiometabolic Medicine Center,Fu Wai Hospital,National Center for Cardiovascular Diseases,Chinese Academy of Medical Sciences and Peking Union Medical College,Beijing,China2.Catheterization Laboratories,Fu Wai Hospital,National Center for Cardiovascular Diseases,Chinese Academy of Medical Sciences and Peking Union Medical College,Beijing,China3.State Key Laboratory of Cardiovascular Disease,Beijing,China;Cardiometabolic Medicine Center,Fu Wai Hospital,National Center for Cardiovascular Diseases,Chinese Academy of Medical Sciences and Peking Union Medical College,Beijing,China;Department of Cardiology,Fu Wai Hospital,National Center for Cardiovascular Diseases,Chinese Academy of Medical Sciences and Peking Union Medical College,Beijing,China
摘要：OBJECTIVES To establish a scoring system combining the ACEF score and the quantitative blood flow ratio(QFR)to improve the long-term risk prediction of patients undergoing percutaneous coronary intervention(PCI).
METHODS In this population-based cohort study,a total of 46 features,including patient clinical and coronary lesion charac-teristics,were assessed for analysis through machine learning models.The ACEF-QFR scoring system was developed using 1263 consecutive cases of CAD patients after PCI in PANDA III trial database.The newly developed score was then validated on the other remaining 542 patients in the cohort.
RESULTS In both the Random Forest Model and the DeepSurv Model,age,renal function(creatinine),cardiac function(LVEF)and post-PCI coronary physiological index(QFR)were identified and confirmed to be significant predictive factors for 2-year ad-verse cardiac events.The ACEF-QFR score was constructed based on the developmental dataset and computed as age(years)/EF(％)+1(if creatinine≥2.0 mg/dL)+1(if post-PCI QFR≤0.92).The performance of the ACEF-QFR scoring system was prelimin-arily evaluated in the developmental dataset,and then further explored in the validation dataset.The ACEF-QFR score showed superior discrimination(C-statistic = 0.651;95％CI:0.611-0.691,P<0.05 versus post-PCI physiological index and other com-monly used risk scores)and excellent calibration(Hosmer-Lemeshow χ2 = 7.070;P = 0.529)for predicting 2-year patient-oriented composite endpoint(POCE).The good prognostic value of the ACEF-QFR score was further validated by multivariable Cox re-gression and Kaplan-Meier analysis(adjusted HR = 1.89;95％CI:1.18-3.04;log-rank P<0.01)after stratified the patients into high-risk group and low-risk group.
CONCLUSIONS An improved scoring system combining clinical and coronary lesion-based functional variables(ACEF-QFR)was developed,and its ability for prognostic prediction in patients with PCI was further validated to be significantly better than the post-PCI physiological index and other commonly used risk scores.
机标关键词：developmentpredictionclinicalriskmodelassessmentcoronaryfunctional
论文发表日期：2024-01-28
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：20( 44-63 )