The Predictive Role of Cardiac Troponin Elevation Ratio Combined With Heart Function Index Model in the Prognosis of Non-ST-Segment Elevation Myocardial Infarction Patients

心肌肌钙蛋白升高比值联合心脏功能指数模型在非ST段抬高型心肌梗死患者预后中的预测作用

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Abstract

BACKGROUND: Non-ST-segment elevation myocardial infarction (NSTEMI) is a common form of coronary artery disease, and its prognosis is influenced by multiple factors. This study aimed to analyze the predictive role of the combined application of cardiac troponin and cardiac function indices in NSTEMI patients' prognosis. METHODS: NSTEMI patients were screened and included in the study. Cardiac troponin elevation ratio (cardiac troponin I (cTnI)/upper limit of normal (ULN)) was measured upon admission, and cardiac function was assessed. General clinical data, laboratory parameters, Grace score, New York Heart Association (NYHA) functional class, complications, and mortality data were collected. The correlation between mortality in NSTEMI patients and clinical parameters was analyzed, and a nomogram prediction model for NSTEMI patient mortality was established. RESULTS: A total of 252 NSTEMI patients were included. Female gender, elevated high-sensitivity C-reactive protein (H-CRP), left ventricular ejection fraction (LVEF) < 50%, NYHA class III and IV, and cTnI/ULN elevation by 36.25-fold were significantly independently associated with mortality outcomes. Multifactorial logistic analysis indicated that these indices remained associated with mortality. A nomogram model predicting NSTEMI patient mortality was constructed using these indices, with an area under the curve (AUC) of 0.911, sensitivity of 97.5%, and specificity of 72.8%. This predictive model outperformed the Grace score (AUC = 0.840). CONCLUSIONS: In NSTEMI patients, a 36.25-fold increase in cTnI/ULN, coupled with NYHA class III and IV, independently predicted prognosis. We developed a nomogram model integrating cTnI/ULN and cardiac function indices, aiding clinicians in assessing risk and implementing early interventions for improved outcomes.

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