Alberto Aimo1, James L Januzzi2, Giuseppe Vergaro3, Andrea Ripoli4, Roberto Latini5, Serge Masson5, Michela Magnoli5, Inder S Anand6, Jay N Cohn7, Luigi Tavazzi8, Gianni Tognoni5, Jørgen Gravning9, Thor Ueland10, Ståle H Nymo11, Hans-Peter Brunner-La Rocca12, Antoni Bayes-Genis13, Josep Lupón13, Rudolf A de Boer14, Akiomi Yoshihisa15, Yasuchika Takeishi15, Michael Egstrup16, Ida Gustafsson16, Hanna K Gaggin2, Kai M Eggers17, Kurt Huber18, Ioannis Tentzeris18, W H Wilson Tang19, Justin L Grodin20, Claudio Passino3, Michele Emdin3. 1. Scuola Superiore Sant'Anna, Pisa, Italy. Electronic address: a.aimo@santannapisa.it. 2. Massachusetts General Hospital, Harvard Clinical Research Institute, Boston, MA, USA. 3. Scuola Superiore Sant'Anna, Pisa, Italy; Fondazione Toscana G. Monasterio, Pisa, Italy. 4. Fondazione Toscana G. Monasterio, Pisa, Italy. 5. Department of Cardiovascular Research, IRCCS - Istituto di Ricerche Farmacologiche - "Mario Negri", Milano, Italy. 6. Division of Cardiovascular Medicine, University of Minnesota, Minneapolis, MN, USA; Department of Cardiology, VA Medical Centre, Minneapolis, MN, USA. 7. Division of Cardiovascular Medicine, University of Minnesota, Minneapolis, MN, USA. 8. GVM Hospitals of Care and Research, E.S. Health Science Foundation, Cotignola, Italy. 9. Department of Cardiology, Oslo University Hospital, Ullevål, Oslo, Norway; Centre for Heart Failure Research, University of Oslo, Oslo, Norway. 10. Research Institute of Internal Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway; Faculty of Medicine, University of Oslo, Oslo, Norway; K. G. Jebsen Thrombosis Research and Expertise Centre, University of Tromsø, Tromsø, Norway. 11. Research Institute of Internal Medicine, Oslo University Hospital, Rikshospitalet, Oslo, Norway. 12. Department of Cardiology, Maastricht University Medical Centre, Maastricht, the Netherlands. 13. Hospital Universitari Germans Trias i Pujol, Badalona, Barcelona, Spain. 14. University Medical Centre Groningen, Groningen, the Netherlands. 15. Department of Cardiovascular Medicine, Fukushima Medical University, Fukushima, Japan. 16. Department of Cardiology, Copenhagen University Hospital Rigshospitalet, Denmark. 17. Department of Medical Sciences, Cardiology, Uppsala University, Uppsala, Sweden. 18. Faculty of Internal Medicine, Wilhelminenspital and Sigmund Freud University, Medical School, Vienna, Austria. 19. Heart and Vascular Institute, Cleveland Clinic, Cleveland, OH, USA. 20. Department of Internal Medicine, Division of Cardiology, University of Texas Southwestern Medical Centre, Dallas, TX, USA.
Abstract
BACKGROUND: In a recent individual patient data meta-analysis, high-sensitivity troponin T (hs-TnT) emerged as robust predictor of prognosis in stable chronic heart failure (HF). In the same population, we compared the relative predictive performances of hs-TnT, N-terminal fraction of pro-B-type natriuretic peptide (NT-proBNP), hs-C-reactive protein (hs-CRP), and estimated glomerular filtration rate (eGFR) for prognosis. METHODS AND RESULTS: 9289 patients (66 ± 12 years, 77% men, 85% LVEF <40%, 60% ischemic HF) were evaluated over a 2.4-year median follow-up. Median eGFR was 58 mL/min/1.73 m2 (interquartile interval 46-70; n = 9220), hs-TnT 16 ng/L (8-20; n = 9289), NT-proBNP 1067 ng/L (433-2470; n = 8845), and hs-CRP 3.3 mg/L (1.4-7.8; n = 7083). In a model including all 3 biomarkers, only hs-TnT and NT-proBNP were independent predictors of all-cause and cardiovascular mortality and cardiovascular hospitalization. hs-TnT was a stronger predictor than NT-proBNP: for example, the risk for all-cause death increased by 54% per doubling of hs-TnT vs. 24% per doubling of NT-proBNP. eGFR showed independent prognostic value from both hs-TnT and NT-proBNP. The best hs-TnT and NT-proBNP cut-offs for the prediction of all-cause death increased progressively with declining renal function (eGFR ≥ 90: hs-TnT 13 ng/L and NT-proBNP 825 ng/L; eGFR < 30: hs-TnT 40 ng/L and NT-proBNP 4608 ng/L). Patient categorization according to these cut-offs effectively stratified patient prognosis across all eGFR classes. CONCLUSIONS: hs-TnT conveys independent prognostic information from NT-proBNP, while hs-CRP does not. Concomitant assessment of eGFR may further refine risk stratification. Patient classification according to hs-TnT and NT-proBNP cut-offs specific for the eGFR classes holds prognostic significance.
BACKGROUND: In a recent individual patient data meta-analysis, high-sensitivity troponin T (hs-TnT) emerged as robust predictor of prognosis in stable chronic heart failure (HF). In the same population, we compared the relative predictive performances of hs-TnT, N-terminal fraction of pro-B-type natriuretic peptide (NT-proBNP), hs-C-reactive protein (hs-CRP), and estimated glomerular filtration rate (eGFR) for prognosis. METHODS AND RESULTS: 9289 patients (66 ± 12 years, 77% men, 85% LVEF <40%, 60% ischemic HF) were evaluated over a 2.4-year median follow-up. Median eGFR was 58 mL/min/1.73 m2 (interquartile interval 46-70; n = 9220), hs-TnT 16 ng/L (8-20; n = 9289), NT-proBNP 1067 ng/L (433-2470; n = 8845), and hs-CRP 3.3 mg/L (1.4-7.8; n = 7083). In a model including all 3 biomarkers, only hs-TnT and NT-proBNP were independent predictors of all-cause and cardiovascular mortality and cardiovascular hospitalization. hs-TnT was a stronger predictor than NT-proBNP: for example, the risk for all-cause death increased by 54% per doubling of hs-TnT vs. 24% per doubling of NT-proBNP. eGFR showed independent prognostic value from both hs-TnT and NT-proBNP. The best hs-TnT and NT-proBNP cut-offs for the prediction of all-cause death increased progressively with declining renal function (eGFR ≥ 90: hs-TnT 13 ng/L and NT-proBNP 825 ng/L; eGFR < 30: hs-TnT 40 ng/L and NT-proBNP 4608 ng/L). Patient categorization according to these cut-offs effectively stratified patient prognosis across all eGFR classes. CONCLUSIONS: hs-TnT conveys independent prognostic information from NT-proBNP, while hs-CRP does not. Concomitant assessment of eGFR may further refine risk stratification. Patient classification according to hs-TnT and NT-proBNP cut-offs specific for the eGFR classes holds prognostic significance.
Authors: Johann M E Jende; Christoph Mooshage; Zoltan Kender; Lukas Schimpfle; Alexander Juerchott; Peter Nawroth; Sabine Heiland; Martin Bendszus; Stefan Kopf; Felix T Kurz Journal: Front Endocrinol (Lausanne) Date: 2022-05-10 Impact factor: 6.055
Authors: Milton Packer; James L Januzzi; Joao Pedro Ferreira; Stefan D Anker; Javed Butler; Gerasimos Filippatos; Stuart J Pocock; Martina Brueckmann; Waheed Jamal; Daniel Cotton; Tomoko Iwata; Faiez Zannad Journal: Eur J Heart Fail Date: 2021-06-21 Impact factor: 17.349
Authors: Faris Al-Khalili; Katrin Kemp-Gudmundsdottir; Emma Svennberg; Tove Fredriksson; Viveka Frykman; Leif Friberg; Mårten Rosenqvist; Johan Engdahl Journal: Open Heart Date: 2020-02-19