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Published on: October 14, 2016
A New Model for the Prediction of Intramyocardial Hemorrhage in ST-Segment Elevation Myocardial Infarction Patients
Yongxin Yang1,2,3, Zeting Min4, Yong Ye5
1Department of Cardiology, The First College of Clinical Medical Science, China Three Gorges University & Yichang Central People's Hospital, Yichang, China.
Insights
This study developed a nomogram to predict intramyocardial hemorrhage (IMH) in ST-segment elevation myocardial infarction (STEMI) patients after percutaneous coronary intervention (PCI). The model shows excellent predictive value, aiding clinical decision-making for STEMI patients.
Area of Science:
- Cardiology
- Medical Imaging
- Predictive Modeling
Background:
- Intramyocardial hemorrhage (IMH) is a key predictor of adverse events in ST-segment elevation myocardial infarction (STEMI) patients post-percutaneous coronary intervention (PCI).
- Current predictive tools for IMH are limited, necessitating simpler, visual models.
Purpose of the Study:
- To develop and validate a nomogram model for predicting the occurrence of IMH in STEMI patients undergoing PCI.
- To identify key clinical risk factors associated with IMH development.
Main Methods:
- A cohort of STEMI patients undergoing PCI was analyzed, with cardiac magnetic resonance (CMR) imaging performed 2-10 days post-PCI.
- Risk factors were identified using Random Forest and logistic regression analyses.
- A nomogram was constructed and validated using ROC curves, calibration curves, and DCA, with bootstrap resampling for internal validation.
Main Results:
- IMH was observed in 43 patients. Independent risk factors identified were ischemic time, preoperative CK-MB, and preoperative Myo levels; RCA occlusion was a protective factor.
- The nomogram demonstrated excellent discriminative ability (AUC=0.865, validated AUC=0.873) and good calibration and clinical applicability.
- The model effectively predicts IMH risk in STEMI patients post-PCI.
Conclusions:
- The developed nomogram model, based on four clinical variables, offers significant predictive value for IMH occurrence in STEMI patients post-PCI.
- This visual tool provides a practical reference for clinicians to assess and manage IMH risk.
- The model's strong performance suggests its utility in improving patient outcomes.
Background:
Intramyocardial hemorrhage (IMH) after emergency percutaneous coronary intervention (PCI) in ST-segment elevation myocardial infarction (STEMI) patients is a significant predictor of major adverse cardiovascular events. However, current research lacks a simple and visual predictive model for IMH occurrence.
Aims:
Our study aims to construct a Nomogram model to predict IMH occurrence.
Methods:
Patients with STEMI who underwent PCI at Yichang Central People's Hospital from August 2023 to September 2024 and had CMR 2-10 days post-PCI were included. They were divided into IMH and Non-IMH groups. Risk factors for IMH were identified using Random Forest, single-factor, and multifactor Logistic regression analyses. The constructed nomogram prediction model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and clinical decision analysis (DCA) curves. Bootstrap resampling was used for internal validation.
Results:
IMH occurred in 43 patients (Non-IMH:53). Ischemic time, preoperative CK-MB level, and preoperative Myo level were identified as independent risk factors for IMH, while RCA occlusion was a protective factor. A nomogram model based on these four variables was established to predict the risk of IMH occurrence. The model's ROC curve had an area under the curve (AUC) of 0.865, indicating excellent discriminative ability; the calibration curve had a good fit (p = 0.16); the DCA curve showed high clinical applicability. After internal validation, the AUC of the ROC curve was 0.873 (95% CI:0.754-0.921).
Conclusion:
The Nomogram model constructed based on four clinical risk factors has good predictive value and clinical applicability, providing an effective reference for predicting the risk of IMH occurrence in STEMI patients after PCI.
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