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

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.