BACKGROUND: It is unknown to what extent noncardiac causes, including renal dysfunction, may contribute to high-sensitivity cardiac troponin T levels. METHODS: In an observational international multicenter study, we enrolled consecutive patients presenting with acute chest pain to the emergency department. Of 1181 patients enrolled, 572 were adjudicated by 2 independent cardiologists to have a noncardiac cause of chest pain. Multiple linear regression analyses were used to determine the important predictors of log-transformed high-sensitivity cardiac troponin T. Kaplan-Meier curve was used to assess the prognostic significance of high-sensitivity cardiac troponin T>0.014 μg/L (99th percentile). RESULTS: A total of 88 patients (15%) had high-sensitivity cardiac troponin T>0.014 μg/L. Less than 50% of cardiac troponins could be explained by known cardiac or noncardiac diseases. In decreasing order of importance, age, estimated glomerular filtration rate, hypertension, previous myocardial infarction, and chronic kidney disease (adjusted r(2) 0.44) emerged as significant factors in linear regression analysis to predict high-sensitivity cardiac troponin T. High-sensitivity cardiac troponin T was best explained by a linear curve with age as ≤0.014 μg/L. Patients with high-sensitivity cardiac troponin T levels>0.014 μg/L were at increased risk for all-cause mortality (hazard ratio 3.0; 95% confidence interval, 0.8-10.6; P=.02) during follow-up. CONCLUSION: Among the known covariates, age and not renal dysfunction is the most important determinant of high-sensitivity cardiac troponin T. Because known cardiac and noncardiac factors, including renal dysfunction, explain less than 50% of high-sensitivity cardiac troponin T levels among patients with a noncardiac cause of chest pain, unknown or underestimated cardiac involvement during the acute presenting condition seems to be the major cause of elevated high-sensitivity cardiac troponin T.
BACKGROUND: It is unknown to what extent noncardiac causes, including renal dysfunction, may contribute to high-sensitivity cardiac troponin T levels. METHODS: In an observational international multicenter study, we enrolled consecutive patients presenting with acute chest pain to the emergency department. Of 1181 patients enrolled, 572 were adjudicated by 2 independent cardiologists to have a noncardiac cause of chest pain. Multiple linear regression analyses were used to determine the important predictors of log-transformed high-sensitivity cardiac troponin T. Kaplan-Meier curve was used to assess the prognostic significance of high-sensitivity cardiac troponin T>0.014 μg/L (99th percentile). RESULTS: A total of 88 patients (15%) had high-sensitivity cardiac troponin T>0.014 μg/L. Less than 50% of cardiac troponins could be explained by known cardiac or noncardiac diseases. In decreasing order of importance, age, estimated glomerular filtration rate, hypertension, previous myocardial infarction, and chronic kidney disease (adjusted r(2) 0.44) emerged as significant factors in linear regression analysis to predict high-sensitivity cardiac troponin T. High-sensitivity cardiac troponin T was best explained by a linear curve with age as ≤0.014 μg/L. Patients with high-sensitivity cardiac troponin T levels>0.014 μg/L were at increased risk for all-cause mortality (hazard ratio 3.0; 95% confidence interval, 0.8-10.6; P=.02) during follow-up. CONCLUSION: Among the known covariates, age and not renal dysfunction is the most important determinant of high-sensitivity cardiac troponin T. Because known cardiac and noncardiac factors, including renal dysfunction, explain less than 50% of high-sensitivity cardiac troponin T levels among patients with a noncardiac cause of chest pain, unknown or underestimated cardiac involvement during the acute presenting condition seems to be the major cause of elevated high-sensitivity cardiac troponin T.
Authors: Gregor Lindner; Carmen Andrea Pfortmueller; Christian Tasso Braun; Aristomenis Konstantinos Exadaktylos Journal: Intern Emerg Med Date: 2013-12-11 Impact factor: 3.397
Authors: Xiao-Dong Ye; Yi He; Sheng Wang; Gordon T Wong; Michael G Irwin; Zhengyuan Xia Journal: Acta Pharmacol Sin Date: 2018-05-17 Impact factor: 6.150
Authors: Razvan T Dadu; Myriam Fornage; Salim S Virani; Vijay Nambi; Ron C Hoogeveen; Eric Boerwinkle; Alvaro Alonso; Rebecca F Gottesman; Thomas H Mosley; Christie M Ballantyne Journal: Stroke Date: 2013-05-09 Impact factor: 7.914
Authors: Antonio Ivan Lazzarino; Mark Hamer; David Gaze; Paul Collinson; Ann Rumley; Gordon Lowe; Andrew Steptoe Journal: Psychoneuroendocrinology Date: 2015-05-14 Impact factor: 4.905
Authors: Eline P M Cardinaels; Sibel Altintas; Mathijs O Versteylen; Ivo A Joosen; Laurens-Jan C Jellema; Joachim E Wildberger; Marco Das; Harry J Crijns; Otto Bekers; Marja P van Dieijen-Visser; Bastiaan L Kietselaer; Alma M A Mingels Journal: PLoS One Date: 2016-04-20 Impact factor: 3.240
Authors: Raphael Twerenbold; Patrick Badertscher; Jasper Boeddinghaus; Thomas Nestelberger; Karin Wildi; Christian Puelacher; Zaid Sabti; Maria Rubini Gimenez; Sandra Tschirky; Jeanne du Fay de Lavallaz; Nikola Kozhuharov; Lorraine Sazgary; Deborah Mueller; Tobias Breidthardt; Ivo Strebel; Dayana Flores Widmer; Samyut Shrestha; Òscar Miró; F Javier Martín-Sánchez; Beata Morawiec; Jiri Parenica; Nicolas Geigy; Dagmar I Keller; Katharina Rentsch; Arnold von Eckardstein; Stefan Osswald; Tobias Reichlin; Christian Mueller Journal: Circulation Date: 2017-11-03 Impact factor: 29.690