Dataset Information

The Prognostic Value of Cardiac Troponin I in Patients with or without Three-Vessel Disease Undergoing Complete Percutaneous Coronary Intervention.

ABSTRACT: Postprocedural cardiac troponin I (cTnI) elevation commonly occurs in patients undergoing percutaneous coronary intervention (PCI); however, its prognostic value remains controversial. This study aimed to investigate the prognostic value of peak postprocedural cTnI in cardiac patients with or without three-vessel disease (TVD) undergoing complete PCI. A total of 1237 consecutive patients (77% males, mean age 58 ± 10 years) with normal baseline cTnI levels were enrolled, 439 patients (77% males, 59 ± 10 years) with TVD, and 798 patients (77% males, 57 ± 10 years) with single- or double-vessel disease (non-TVD). The primary outcome was the occurrence of major adverse cardiovascular events (MACE), defined as a composite of non-fatal MI, non-fatal stroke, unplanned revascularization, re-hospitalization due to heart failure or severe arrhythmias, and all-cause death. During the median follow-up of 5.3 years, a total of 169 patients (13.7%) developed MACE, including 73 (16.6%) in the TVD group and 96 (12.0%) in the non-TVD group (p = 0.024). After adjustment, the multivariate Cox analysis showed that hypertension (HR 1.50; 95% CI: 1.01-2.20; p = 0.042), TVD (HR 1.44; 95% CI: 1.03-2.02; p = 0.033), and cTnI ≥ 70× URL (HR 2.47; 95% CI: 1.28-4.78, p = 0.007) were independently associated with increased MACE during long-term follow-up. Further subgroup analyses showed that cTnI ≥ 70× URL was an independent predictor of MACE in TVD patients (HR 3.32, 95% CI: 1.51-7.34, p = 0.003), but not in non-TVD patients (HR 1.01, 95%CI: 0.24-4.32, p = 0.991). In conclusion, elevation of post-PCI cTnI ≥ 70× URL is independently associated with a high risk of MACE during long-term follow-up in patients with TVD, but not in those with non-TVD.

SUBMITTER: Li ZF

PROVIDER: S-EPMC9267560 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

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The Prognostic Value of Cardiac Troponin I in Patients with or without Three-Vessel Disease Undergoing Complete Percutaneous Coronary Intervention.

Li Zhi-Fan ZF Zhang Shuang S Shi Hui-Wei HW Zhang Wen-Jia WJ Sui Yong-Gang YG Li Jian-Jun JJ Dou Ke-Fei KF Qian Jie J Wu Na-Qiong NQ

Journal of clinical medicine 20220704 13

Postprocedural cardiac troponin I (cTnI) elevation commonly occurs in patients undergoing percutaneous coronary intervention (PCI); however, its prognostic value remains controversial. This study aimed to investigate the prognostic value of peak postprocedural cTnI in cardiac patients with or without three-vessel disease (TVD) undergoing complete PCI. A total of 1237 consecutive patients (77% males, mean age 58 ± 10 years) with normal baseline cTnI levels were enrolled, 439 patients (77% males, ...[more]

PMID: 35807181

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Project description:BackgroundThe triglyceride-glucose (TyG) index has been proposed as a reliable surrogate marker of insulin resistance and an independent predictor of major adverse cardiovascular events (MACEs). Several recent studies have shown the relationship between the TyG index and cardiovascular outcomes; however, the role of the TyG index in chronic coronary syndrome (CCS) progression has not been extensively assessed especially in population after revascularization. This study aimed to investigate the prognostic value of the TyG index in predicting MACEs in CCS patients undergoing percutaneous coronary intervention (PCI).MethodsThe data for the study were taken from the Hospital Information System database in China-Japan Friendship Hospital over the period 2019-2021. Eligible participants were divided into groups according to the TyG index tertiles. The Boruta algorithm was performed for feature selection. Multivariate Cox proportional hazards models and restricted cubic spline (RCS) analysis were applied to examine the dose-response relationship between the TyG index and endpoint, and the results were expressed with hazard ratio (HR) and 95% confidence interval (CI) values. The area under the receiver operating characteristic (ROC) curve (AUC), decision curve analysis (DCA), and clinical impact curve (CIC) were plotted to comprehensively evaluate the predictive accuracy and clinical value of the model. The goodness-of-fit of models was evaluated using the calibration curve and χ2 likelihood ratio test.ResultsAfter applying inclusion and exclusion criteria, 1353 patients with CCS undergoing PCI were enrolled in the study. After adjusting for all confounders, we found that those with the highest TyG index had a 59.5% increased risk of MACEs over the 1-year follow-up (HR 1.595, 95% CI 1.370 ~ 1.855). Using the lowest TyG index tertile as the reference (T1), the fully adjusted HRs (95% CIs) for endpoints was 1.343 (1.054 ~ 1.711) in the middle (T2) and 2.297 (1.842 ~ 2.864) in highest tertile (T3) (P for trend < 0.001). The TyG index had an excellent predictive performance according to the results of AUC 0.810 (0.786, 0.834) and χ2 likelihood ratio test (χ2 = 7.474, P = 0.486). DCA and CIC analysis also suggested a good overall net benefit and clinical impact of the multivariate model. The results in the subgroup analysis were consistent with the main analyses. RCS model demonstrated that the TyG index was nonlinearly associated with the risk of MACEs within one year (P for nonlinear < 0.001).ConclusionThe elevated TyG index is associated with an increased risk of cardiovascular events and predicts future MACEs in patients with CCS undergoing PCI independently of known cardiovascular risk factors, indicating that the TyG index may be a potential marker for risk stratification and prognosis in CCS patients undergoing PCI.

Project description:AimsThe GRACE and CHA2DS2-VASc risk score are developed for risk stratification in patients with acute coronary syndrome and AF, respectively. We aimed to assess the predictive performance of the GRACE score and CHA2DS2-VASc score among patients with atrial fibrillation (AF) undergoing percutaneous coronary intervention (PCI).MethodsConsecutive patients with a diagnosis of AF admitted to our hospital for PCI between January 2016 and December 2018 were included and followed up for at least 1 year. The primary endpoint was a composite of major adverse cardiac events (MACEs) including all-cause mortality, repeat revascularization, myocardial infarction, or ischaemic stroke.ResultsA total of 1452 patients were identified. Cox regression demonstrated that the GRACE (HR 1.014, 95% CI 1.008-1.020, p < 0.001) but not the CHA2DS2-VASc score was associated with the risk of MACEs. Both GRACE and CHA2DS2-VASc scores were predictive of all-cause mortality with HR of 1.028 (95% CI 1.020-1.037, p < 0.001) and 1.334 (95% CI 1.107-1.632, p = 0.003). Receiver operating characteristic analyses showed both scores had similar discrimination capacity for all-cause mortality (C-statistic: 0.708 for GRACE vs. 0.661 for CHA2DS2-VASc, p = 0.299). High GRACE score was also significantly associated with increased risk of ischaemic stroke (HR 1.018, 95% CI 1.005-1.031, p = 0.006) and major bleeding (HR 1.012, 95% CI 1.001-1.024, p = 0.039), whereas high CHA2DS2-VASc score was not.ConclusionsHigh GRACE score but not CHA2DS2-VASc score were both associated with an increased risk of MACEs after PCI in patients with AF. The GRACE and CHA2DS2-VASc scores have similar predictive performance for predicting all-cause mortality.Key messages:In patients with AF undergoing PCI, increasing GRACE but not CHA2DS2-VASc scores was independently associated high risk of MACEs.The GRACE score could also help identify patients at higher risk of stroke and major bleeding.Both GRACE and CHA2DS2-VASc scores showed good ability in the prediction of all-cause mortality.

Dataset Information

The Prognostic Value of Cardiac Troponin I in Patients with or without Three-Vessel Disease Undergoing Complete Percutaneous Coronary Intervention.

Publications

The Prognostic Value of Cardiac Troponin I in Patients with or without Three-Vessel Disease Undergoing Complete Percutaneous Coronary Intervention.

Similar Datasets

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