A nomogram model for predicting intramyocardial hemorrhage post-PCI based on SYNTAX score and clinical features

Area of Science:

• Cardiology
• Medical Imaging
• Predictive Modeling

Background:

• Intramyocardial hemorrhage (IMH) is a complication following percutaneous coronary intervention (PCI) in patients with acute myocardial infarction (AMI).
• Predicting IMH risk is crucial for optimizing patient management and treatment strategies.

Purpose of the Study:

• To develop and validate a nomogram model for predicting the occurrence of IMH in AMI patients post-PCI.
• To identify key clinical and angiographic predictors of IMH.

Main Methods:

• A retrospective study involving 216 AMI patients who underwent Cardiac Magnetic Resonance (CMR) post-PCI.
• Development of a nomogram using logistic regression analysis based on clinical data and SYNTAX Score (SS).
• Model validation using a separate training and validation set, assessed by Receiver Operating Characteristic (ROC) curve analysis and Area Under the Curve (AUC).

Main Results:

• The nomogram identified high-sensitivity troponin T (HS-TnT) and SYNTAX Score (SS) as independent predictors of IMH.
• The nomogram demonstrated high predictive accuracy with an AUC of 0.893 in the training set and 0.910 in the validation set.
• Calibration and decision curve analysis confirmed the model's consistency and accuracy.

Conclusions:

• A novel nomogram model effectively predicts IMH risk in AMI patients undergoing PCI.
• The model, incorporating HS-TnT and SS, provides valuable guidance for clinical diagnosis and treatment planning.
• This tool supports personalized risk assessment and management strategies for AMI patients post-PCI.