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Acute coronary syndrome vs nonspecific troponin elevation - Clinical predictors and survival analysis

Journal

ARCHIVES OF INTERNAL MEDICINE
Volume 167, Issue 3, Pages 276-281

Publisher

AMER MEDICAL ASSOC
DOI: 10.1001/archinte.167.3.276

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Background: Although troponin is considered a specific marker for the diagnosis of acute coronary syndrome (ACS), recent studies have shown troponin elevation in a variety of nonischemic conditions. Our aim was to determine the predictors for the diagnosis of ACS in the presence of an abnormal troponin level. Methods: All patients with abnormal troponin T levels were analyzed. Demographic and clinical data were collected and death was recorded. The study group was divided into 2 subgroups: ACS vs nonthrombotic troponin elevation. Amultivariate logistic regression analysis was performed to define variables that predict the diagnosis of ACS. The positive predictive value (PPV) for ACS diagnosis was calculated, and a survival analysis was performed. Results: During the study period, 615 patients had elevated troponin T levels. Only 326 patients (53%) received a main diagnosis of ACS, while 254 (41%) had nonthrombotic troponin elevation; for 35 patients (6%), the diagnosis was not conclusive. Positive predictors for the diagnosis of ACS were age between 40 and 70 years, history of hypertension or ischemic heart disease, normal renal function, and a troponin T level higher than 1.0 ng/mL. The overall PPV of troponin T for ACS diagnosis was only 56% (95% CI, 52%-60%). The PPV of troponin T level higher than 1.0 ng/mL in the presence of normal renal function was 90% but was as low as 27% for values of 0.1 to 1.0 ng/mL for elderly patients with renal failure. In-hospital and long-term survival rates were significantly better (P <. 001) for patients with ACS. Conclusions: Nonspecific troponin elevation is a common finding among hospitalized patients and correlates with worse prognosis. The diagnosis of myocardial infarction should still mostly be based on the clinical presentation. The predictors and algorithm suggested in this study might increase the diagnostic accuracy of ACS and direct the appropriate treatment.

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