Clinical validation study of a novel prognostic risk prediction model (CHIP Score) for interventional therapy in patients with NSTE-ACS-a single-center retrospective cohort study based on 348 patients

一项针对非ST段抬高型急性冠脉综合征(NSTE-ACS)患者介入治疗的新型预后风险预测模型(CHIP评分)的临床验证研究——一项基于348例患者的单中心回顾性队列研究

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Abstract

BACKGROUND: A complex high-risk indicated percutaneous coronary intervention (CHIP) score was recently developed from the British Cardiovascular Intervention Society (BCIS) database to define CHIP cases and their risk of in-hospital major adverse cardiac or cerebrovascular events (MACCE). However, the effectiveness and reliability of this model in predicting the risk of MACCE in CHIP patients after discharge require further validation.This study aims to clinically validate the prognostic value of the CHIP Score in patients with NSTE-ACS undergoing PCI. METHODS: In this study, a total of 348 patients with non-ST-elevation acute coronary syndrome (NSTE-ACS) who underwent percutaneous coronary intervention (PCI) at the People's Hospital of Ningxia Hui Autonomous Region from January 1st to December 31st, 2019, were consecutively enrolled. The patients were stratified into four groups according to CHIP Score: Group A (0), B (1-2), C (3-4), and D (≥ 5). The primary endpoint was major adverse cardiac and cerebrovascular events (MACCE), a composite of cardiovascular mortality, unplanned revascularization, and stroke, over 36 months. Secondary endpoints included individual MACCE components, acute coronary syndrome (ACS) rehospitalization, acute heart failure hospitalization(AHF) hospitalization, and gastrointestinal bleeding. The Kaplan-Meier (KM) survival curve was used to compare the survival differences between groups. The optimal cut-off value for predicting high-risk patients with CHIP was determined through the receiver operating characteristic (ROC) curve. Patients were then divided into a high-risk group and a low-risk group based on the cut-off value. The KM curve was employed to compare the survival differences between the high-risk and low-risk groups. Additionally, the Cox proportional hazards regression model was applied to identify the independent risk factors for MACCE in patients with NSTE-ACS. RESULTS: Elevated CHIP Scores showed a significant association with increased MACCE risk (P < 0.05). Through ROC curve analysis, patients with CHIP score ≥ 3 were classified as the high-risk group. Compared with the low-risk group, the high-risk group had a significantly increased risk of MACCE (HR = 3.298, 95%CI:1.939-5.610, P < 0.05). Hyperlipidemia (HR = 1.817, 95%CI:1.072-3.081, P < 0.05) and coronary chronic total occlusion (CTO) (HR = 1.966, 95%CI:1.063-3.634, P < 0.05) were identified as independent risk factors for an elevated risk of MACCE. CONCLUSION: In this study, the CHIP score demonstrated moderately satisfactory predictive efficacy in forecasting the risk of MACCE among NSTE-ACS patients. Hyperlipidemia and coronary CTO were independent risk factors for MACCE in CHIP patients.

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