Survival outcomes correlate with the level of cell-free circulating DNA in ST-elevation myocardial infarction

ST段抬高型心肌梗死患者的生存结果与循环中游离DNA的水平相关。

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Abstract

BACKGROUND: Myocardial infarction (MI) can lead to higher cellular damage, making cell-free DNA (cfDNA) a potential biomarker for assessing disease severity. The aim of this study is to evaluate survival predictions using cfDNA measurements and assess its correlation with MI. MATERIALS AND METHODS: A direct fluorescence assay was employed to measure cfDNA content in the blood samples of participants. The inclusion criteria included patients who gave informed consent, suffering from ST-elevation myocardial infraction (STEMI) based on established diagnostic criteria (joint ESC/ACC guidelines), between the age of 18 and 80 years old, and had elevated troponin biomarker levels. The study included 150 patients diagnosed with STEMI and 50 healthy volunteers as controls. Serial monitoring of patients was conducted to track their postdisease status. The rate of change of cfDNA was calculated and daily measurements for 7 days were recorded. RESULTS: Mean levels of cfDNA were found to be 5.93 times higher in patients with STEMI compared to healthy controls, providing clear evidence of a clinical correlation between cfDNA and STEMI. Patients were further categorized based on their survival status within a 90-day period. The study observed a strong predictive relationship between the rate of change of cfDNA during daily measurements and survival outcomes. To assess its predictive capability, a receiver operating characteristics (ROC) curve analysis was performed. The ROC analysis identified an optimal cutoff value of 2.50 for cfDNA, with a sensitivity of 81.5% and specificity of 74.0% in predicting disease outcomes. CONCLUSION: This study demonstrates a robust association between cfDNA and STEMI, indicating that cfDNA levels can be a valuable early prognostic factor for patients. Serial measurements of cfDNA during early disease onset hold promise as an effective approach for predicting survival outcomes in MI patients.

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