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High-sensitivity troponin I for risk stratification in normotensive pulmonary embolism
Matthias Ebner1,2, Niklas Guddat3, Karsten Keller4,5
1Dept of Cardiology and Angiology, Campus Charité Mitte (CCM), Charité - University Medicine Berlin, Berlin, Germany.
Abstract:
While numerous studies have confirmed the prognostic role of high-sensitivity troponin T (hsTnT) in pulmonary embolism (PE), high-sensitivity troponin I (hsTnI) is inappropriately studied. This study aimed to investigate the prognostic relevance of hsTnI in normotensive PE, establish the optimal cut-off value for risk stratification and to compare the prognostic performances of hsTnI and hsTnT. Based on data from 459 consecutive PE patients enrolled in a single-centre registry, receiver operating characteristic analysis was used to identify an optimal hsTnI cut-off value for prediction of in-hospital adverse outcomes (PE-related death, cardiopulmonary resuscitation or vasopressor treatment) and all-cause mortality. Patients who suffered an in-hospital adverse outcome (4.8%) had higher hsTnI concentrations compared with those with a favourable clinical course (57 (interquartile range (IQR) 22-197) versus 15 (IQR 10-86) pg·mL-1, p=0.03). A hsTnI cut-off value of 16 ng·mL-1 provided optimal prognostic performance and predicted in-hospital adverse outcomes (OR 6.5, 95% CI 1.9-22.4) and all-cause mortality (OR 3.7, 95% CI 1.0-13.3). Between female and male patients, no relevant differences in hsTnI concentrations (17 (IQR 10-97) versus 17 (IQR 10-92) pg·mL-1, p=0.79) or optimised cut-off values were observed. Risk stratification according to the 2019 European Society of Cardiology algorithm revealed no differences if calculated based on either hsTnI or hsTnT (p=0.68). Our findings confirm the prognostic role of hsTnI in normotensive PE. HsTnI concentrations >16 pg·mL-1 predicted in-hospital adverse outcome and all-cause mortality; sex-specific cut-off values do not seem necessary. Importantly, our results suggest that hsTnI and hsTnT can be used interchangeably for risk stratification.
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