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A nomogram predicting 30-day mortality in patients undergoing percutaneous coronary intervention
Jingjing Song1, Yupeng Liu1,2, Wenyao Wang3,4
1State Key Laboratory of Cardiovascular Disease, Department of Cardiology, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Insights
A new nomogram accurately predicts 30-day mortality after percutaneous coronary intervention (PCI). This tool aids in early risk stratification for patients undergoing PCI, improving clinical decision-making.
Area of Science:
- Cardiology
- Medical Informatics
Background:
- Percutaneous coronary intervention (PCI) is a common procedure.
- Early detection of mortality post-PCI is critical for patient management.
- Existing risk models often use outdated data, necessitating updated prediction tools.
Purpose of the Study:
- To develop and validate a nomogram for predicting 30-day mortality after PCI.
- To provide a more accurate and current risk assessment tool for clinicians.
Main Methods:
- A cohort of 10,444 patients undergoing PCI was analyzed.
- Logistic regression with stepwise backward selection identified key predictive features.
- A nomogram was constructed using selected parameters.
Main Results:
- The nomogram incorporated age, male sex, cardiac dysfunction, STEMI, and TIMI 0-2 post-PCI.
- The nomogram demonstrated strong predictive performance with an AUC of 0.881.
- It outperformed a previous risk model (AUC = 0.7).
Conclusions:
- A novel nomogram effectively predicts 30-day mortality in unselected PCI patients.
- This tool can significantly enhance clinical risk stratification.
- The nomogram offers a valuable resource for improving patient outcomes.
Background And Aims:
Early detection of mortality after percutaneous coronary intervention (PCI) is crucial, whereas most risk prediction models are based on outdated cohorts before the year 2000. This study aimed to establish a nomogram predicting 30-day mortality after PCI.
Materials And Methods:
In total, 10,444 patients undergoing PCI in National Center for Cardiovascular Diseases in China were enrolled to establish a nomogram to predict 30-day mortality after PCI. The nomogram was generated by incorporating parameters selected by logistic regression with the stepwise backward method.
Results:
Five features were selected to build the nomogram, including age, male sex, cardiac dysfunction, STEMI, and TIMI 0-2 after PCI. The performance of the nomogram was evaluated, and the area under the curves (AUC) was 0.881 (95% CI: 0.8-0.961). Our nomogram exhibited better performance than a previous risk model (AUC = 0.7, 95% CI: 0.586-0.813) established by Brener et al. The survival curve successfully stratified the patients above and below the median score of 4.
Conclusion:
A novel nomogram for predicting 30-day mortality was established in unselected patients undergoing PCI, which may help risk stratification in clinical practice.
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