Association between Cystatin C and Cardiac Function in Acute Myocardial Infarction Patients: A Real-World Analysis

The predictive value of the triglyceride glucose index combined with cystatin C for the prognosis of patients with acute coronary syndrome

Background

Recent studies have shown that the triglyceride glucose index (TyG) and cystatin C (CysC) are closely related to cardiovascular disease, but there is limited research on the prognosis of patients with acute coronary syndrome (ACS) after percutaneous coronary intervention (PCI). The aim of this study was to explore the predictive value of the combination of the TyG index and CysC in predicting major adverse cardiovascular events (MACEs) in ACS patients who underwent PCI.

Methods

This retrospective study included 319 ACS patients who underwent PCI. The clinical endpoint was the occurrence of MACEs, including all-cause mortality, heart failure, non-fatal myocardial infarction, target vessel revascularization, and angina requiring hospitalization. Patients were classified into MACEs (65 cases) and non-MACEs (254 cases) groups. Univariate factor and multivariate analysis were used to identify predictors of MACEs. The receiver operating curve (ROC) of the prediction model of MACEs was determined. Additionally, the net reclassification improvement and integrated discrimination improvement indexes were calculated to further assess the additional predictive value of the risk factors for MACEs. Subgroup and interaction analysis between the TyG index combined with CysC and MACEs were conducted in various subgroups. Patients were stratified according to the optimal cutoff point value of the TyG index and the CysC determined by ROC curve analysis. The Kaplan-Meier analysis method was used to construct a survival curve 1 year after PCI.

Results

During a median follow-up period of 14 months, 65 (20.38%) patients had experienced at least one primary endpoint event. Multivariate logistic regression analysis indicated that the TyG index and CysC were independently associated with an increased risk of MACEs after PCI (OR, 2.513, 95% CI 1.451-4.351, P= 0.001; and OR, 4.741, 95% CI 1.344-16.731, P=0.016, respectively). The addition of the TyG index and CysC to the baseline risk model had the strongest incremental effect for predicting MACEs in terms of the C-statistic from 0.789 (95% CI 0.723-0.855, P<0.001) to 0.799 (95% CI 0.733-0.865, P<0.001). Furthermore, Kaplan-Meier analysis demonstrated that a TyG index greater than 9.325 and a CysC value greater than 1.065 mg/ml were significantly associated with an increased risk of MACEs (log-rank, all P < 0.01).

Conclusion

The TyG index predicts MACEs after PCI in patients with ASC independent of known cardiovascular risk factors. Adjustment of the CysC by the TyG index further improves the predictive ability for MACEs in patients with ACS undergoing PCI. Thus, both of them are expected to become new prognostic indicators for MACEs in patients with ACS after PCI.

Prediction of Outcomes Through Cystatin C and cTnI in Elderly Type 2 Myocardial Infarction Patients

Background

Chronic kidney disease (CKD) and coronary artery disease (CAD) are strongly associated. Cystatin C (Cys C) is a more sensitive marker of early renal insufficiency. This study aimed to evaluate the prognostic implications of combined of Cys C and cardiac troponin I (cTnI) on 90-day outcomes in elderly patients with type 2 myocardial infarction (MI).

Methods

The data of consecutive type 2 MI patients aged 80 years and older who received Cys C and cTnI measurements within 24 h of admission were retrospectively reviewed. The endpoint was a 90-day all-cause and cardiac mortality.

Results

A total of 4326 patients were included. During the 90-day follow-up period, a higher all-cause and cardiac mortality was observed in patients with Cys C ≥ 1.49mg/L than in patients with Cys C < 1.49 mg/L (P <0.001). After the multivariate logistic regression adjustments, the higher CysC and cTnI levels remained independent predictors of the 90-day all-cause mortality and cardiac mortality. Moreover, the Kaplan-Meier all-cause and cardiac mortality event-free survival curves showed that the patients with the presence of elevated levels of both Cys C and cTnI had a significantly increased risk than those with Cys C or cTnI alone.

Conclusion

Elevated Cys C level is an independent risk factor for all-cause and cardiac mortality in the elderly type 2 MI population. The predictive ability of the combined use of Cys C and cTnI in elderly type 2 MI patients is stronger than that of Cys C or cTnI alone.

From Classic to Modern Prognostic Biomarkers in Patients with Acute Myocardial Infarction

Despite all the important advances in its diagnosis and treatment, acute myocardial infarction (AMI) is still one of the most prominent causes of morbidity and mortality worldwide. Early identification of patients at high risk of poor outcomes through the measurement of various biomarker concentrations might contribute to more accurate risk stratification and help to guide more individualized therapeutic strategies, thus improving prognoses. The aim of this article is to provide an overview of the role and applications of cardiac biomarkers in risk stratification and prognostic assessment for patients with myocardial infarction. Although there is no ideal biomarker that can provide prognostic information for risk assessment in patients with AMI, the results obtained in recent years are promising. Several novel biomarkers related to the pathophysiological processes found in patients with myocardial infarction, such as inflammation, neurohormonal activation, myocardial stress, myocardial necrosis, cardiac remodeling and vasoactive processes, have been identified; they may bring additional value for AMI prognosis when included in multi-biomarker strategies. Furthermore, the use of artificial intelligence algorithms for risk stratification and prognostic assessment in these patients may have an extremely important role in improving outcomes.