IMR Press / RCM / Volume 25 / Issue 5 / DOI: 10.31083/j.rcm2505155
Open Access Original Research
A Visualized Nomogram for Predicting Prognosis in Elderly Patients after Percutaneous Coronary Intervention
Qin Chen1,2,3,†Yuxiang Chen1,2,3,†Ruijin Hong1,2,3,†Jiaxin Zhong1,2,3Lihua Chen1,2,3Yuanming Yan1,2,3Lianglong Chen1,2,3Yukun Luo1,2,3,*
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1 Fujian Key Laboratory of Vascular Aging (Fujian Medical University), Department of Cardiology, Fujian Medical University Union Hospital, 350001 Fuzhou, Fujian, China
2 Fujian Key Laboratory of Vascular Aging (Fujian Medical University), Fujian Institute of Coronary Heart Disease, 350001 Fuzhou, Fujian, China
3 Fujian Key Laboratory of Vascular Aging (Fujian Medical University), Fujian Heart Medical Center, 350001 Fuzhou, Fujian, China
*Correspondence: luoyukun@hotmail.com (Yukun Luo)
These authors contributed equally.
Rev. Cardiovasc. Med. 2024, 25(5), 155; https://doi.org/10.31083/j.rcm2505155
Submitted: 6 September 2023 | Revised: 1 January 2024 | Accepted: 15 January 2024 | Published: 6 May 2024
Copyright: © 2024 The Author(s). Published by IMR Press.
This is an open access article under the CC BY 4.0 license.
Abstract

Background: Revascularized patients still experience adverse cardiovascular events. This is particularly true for elderly patients over the age of 65, as they often have more co-morbid vascular conditions. It is important to develop a tool to assist clinicians in comprehensively assessing these patients’ prognosis. The objective of this study is to create a comprehensive visual nomogram model combining clinical and physiological assessments to predict outcomes in elderly patients undergoing percutaneous coronary intervention (PCI). Methods: This study is a retrospective investigation of patients who underwent PCI between January 2016 and December 2017. A total of 691 patients with 1461 vessels were randomly divided into a training (n = 483) and a validation set (n = 208). A multivariate Cox regression model was employed using the training set to select variables for constructing a nomogram. The performance of the nomogram was assessed through the receiver operating characteristic curve (ROC) and calibration curves to evaluate its discrimination and predictive accuracy. To further assess the clinical usefulness, Kaplan–Meier curve analysis and landmark analysis were conducted. Results: Independent risk factors, including diabetes mellitus (DM), post-PCI quantitative flow ratio (QFR), previous myocardial infarction (MI), and previous PCI, were contained in the nomogram. The nomogram exhibited a good area under the curve (AUC) ranging from 0.742 to 0.789 in the training set, 0.783 to 0.837 in the validation set, and 0.764 to 0.786 in the entire population. Calibration curves demonstrated a well-fitted curve in all three sets. The Kaplan–Meier curves showed clear separation and the patients with higher scores in the nomogram model exhibited a higher incidence of target vessel revascularization (TVR) (7.99% vs. 1.24% for 2-year, p < 0.001 and 13.54% vs. 2.23% for 5-years, p < 0.001, respectively). Conclusions: This study has developed the visually intuitive nomogram to predict the 2-year and 5-year TVR rates for elderly patients who underwent PCI. This tool provides more accurate and comprehensive healthcare guidance for patients and their physicians.

Keywords
nomogram
target vessel revascularization
percutaneous coronary intervention
coronary artery disease
quantitative flow ratio
Funding
2020Y9098/Joint Funds for the Innovation of Science and Technology
2021GGB004/Fujian Provincial Health Technology Project
2022CXB005/Fujian Provincial Health Technology Project
Figures
Fig. 1.
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