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Predictive Value of Gensini Score in the Long-Term Outcomes of Patients With Coronary Artery Disease Who Underwent PCI

OBJECTIVE: Gensini score is an effective tool used to evaluate the severity of coronary artery disease (CAD). Whether the Gensini score has predictive value for the clinical outcomes of patients with CAD after percutaneous coronary intervention (PCI) has not been investigated. METHODS: All patients...

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Detalles Bibliográficos
Autores principales: Wang, Kai-Yang, Zheng, Ying-Ying, Wu, Ting-Ting, Ma, Yi-Tong, Xie, Xiang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8818732/
https://www.ncbi.nlm.nih.gov/pubmed/35141291
http://dx.doi.org/10.3389/fcvm.2021.778615
Descripción
Sumario:OBJECTIVE: Gensini score is an effective tool used to evaluate the severity of coronary artery disease (CAD). Whether the Gensini score has predictive value for the clinical outcomes of patients with CAD after percutaneous coronary intervention (PCI) has not been investigated. METHODS: All patients were from the Clinical Outcomes and Risk Factors of Patients with Coronary Heart Disease after PCI (CORFCHD-PCI), a retrospective cohort study involving 5,672 patients with CAD who underwent PCI, such as 2,110 patients with diabetes and 3,562 patients without diabetes, from January 2008 to December 2017. Patients were divided into three groups according to the tertile of Gensini score: first tertile (Gensini score <11 points), second tertile (Gensini score 11–38 points), and third tertile (Gensini score >38 points). The median follow-up time was 31.0 (interquartile range, IQR: 30.0) months. Compared the differences in clinical outcomes between the groups. Multivariate Cox regression analyses were performed to assess the predictive value of the Gensini score for outcomes over up to 10 years of follow-up. RESULTS: In the population without diabetes, there were significant differences between the three groups in the incidences of all-cause mortality (ACM, p = 0.048), cardiac mortality (CM, p = 0.024), major adverse cardiovascular (CV) events (MACEs, p = 0.006), and major adverse cardiovascular and cerebrovascular events (MACCEs, p = 0.009). In the population with diabetes, there were significant differences between the three groups in the incidences of ACM, CM, MACEs, and MACCEs (all p < 0.001). After multivariate Cox regression analyses, in the population without diabetes, the respective risks of ACM, CM, MACEs, and MACCEs were increased 89.9% [hazard ratio (HR) = 1.899, 95% CI: 1.285–2.807, p = 0.001], 115.1% (HR = 2.151, 95% CI: 1.378–3.356, p = 0.001), 48.1% (HR = 1.481, 95% CI: 1.152–1.904, p = 0.002), and 49.8% (HR = 1.498, 95% CI: 1.176–1.907, p = 0.001) in the third tertile compared with those in the first tertile. In the population with diabetes, the respective risks of ACM, CM, MACEs, and MACCEs were increased 248.5% (HR = 3.485, 95% CI: 1.973–6.154, p < 0.001), 260.4% (HR = 3.604, 95% CI: 1.866–6.963, p < 0.001), 130.2% (HR = 2.302, 95% CI: 1.649–3.215, p < 0.001), and 119.8% (HR = 2.198, 95% CI: 1.600–3.018, p < 0.001) in the third tertile compared with those in the first tertile. CONCLUSION: The present study indicated that the Gensini score is an independent predictor of long-term adverse outcomes in patients with CAD who underwent PCI, and it has more predictive value in the population with diabetes.