Alberto Aimo1, James L Januzzi2, Giuseppe Vergaro3,4, Aldo Clerico3,4, Roberto Latini5, Jennifer Meessen5, Inder S Anand6,7, Jay N Cohn6, Jørgen Gravning8,9, Thor Ueland10,11,12, Ståle H Nymo10, Hans-Peter Brunner-La Rocca13, Antoni Bayes-Genis14, Josep Lupón14, Rudolf A de Boer15, Akiomi Yoshihisa16, Yasuchika Takeishi16, Michael Egstrup17, Ida Gustafsson17, Hanna K Gaggin2, Kai M Eggers18, Kurt Huber19, Ioannis Tentzeris19, Andrea Ripoli4, Claudio Passino3,4, Michele Emdin3,4. 1. Cardiology Division, University Hospital of Pisa, Italy. 2. Massachusetts General Hospital and Baim Institute for Clinical Research, Boston, USA. 3. Institute of Life Sciences, Scuola Superiore Sant'Anna, Pisa, Italy. 4. Fondazione Toscana G. Monasterio, Pisa, Italy. 5. Department of Cardiovascular Research IRCCS - Istituto di Ricerche Farmacologiche - 'Mario Negri', Milan, Italy. 6. Division of Cardiovascular Medicine, University of Minnesota, Minneapolis, USA. 7. Department of Cardiology, VA Medical Centre, Minneapolis, USA. 8. Department of Cardiology, Oslo University Hospital, Ullevål, Oslo, Norway. 9. Centre for Heart Failure Research, University of Oslo, Norway. 10. Research Institute of Internal Medicine, Oslo University Hospital, Rikshospitalet, Norway. 11. Faculty of Medicine, University of Oslo, Norway. 12. K. G. Jebsen Thrombosis Research and Expertise Centre, University of Tromsø, Norway. 13. Department of Cardiology, Maastricht University Medical Centre, The Netherlands. 14. Hospital Universitari Germans Trias i Pujol, Badalona (Barcelona), Spain. 15. University Medical Centre Groningen, The Netherlands. 16. Department of Cardiovascular Medicine, Fukushima Medical University, Japan. 17. Department of Cardiology, Copenhagen University Hospital Rigshospitalet, Denmark. 18. Department of Medical Sciences, Cardiology, Uppsala University, Sweden. 19. Faculty of Internal Medicine, Wilhelminenspital and Sigmund Freud University Medical School, Vienna, Austria.
Abstract
AIMS: Obesity defined by body mass index (BMI) is characterized by better prognosis and lower plasma N-terminal pro-B-type natriuretic peptide (NT-proBNP) in heart failure. We assessed whether another anthropometric measure, per cent body fat (PBF), reveals different associations with outcome and heart failure biomarkers (NT-proBNP, high-sensitivity troponin T (hs-TnT), soluble suppression of tumorigenesis-2 (sST2)). METHODS: In an individual patient dataset, BMI was calculated as weight (kg)/height (m) 2 , and PBF through the Jackson-Pollock and Gallagher equations. RESULTS: Out of 6468 patients (median 68 years, 78% men, 76% ischaemic heart failure, 90% reduced ejection fraction), 24% died over 2.2 years (1.5-2.9), 17% from cardiovascular death. Median PBF was 26.9% (22.4-33.0%) with the Jackson-Pollock equation, and 28.0% (23.8-33.5%) with the Gallagher equation, with an extremely strong correlation (r = 0.996, p < 0.001). Patients in the first PBF tertile had the worst prognosis, while patients in the second and third tertile had similar survival. The risks of all-cause and cardiovascular death decreased by up to 36% and 27%, respectively, per each doubling of PBF. Furthermore, prognosis was better in the second or third PBF tertiles than in the first tertile regardless of model variables. Both BMI and PBF were inverse predictors of NT-proBNP, but not hs-TnT. In obese patients (BMI ≥ 30 kg/m2, third PBF tertile), hs-TnT and sST2, but not NT-proBNP, independently predicted outcome. CONCLUSION: In parallel with increasing BMI or PBF there is an improvement in patient prognosis and a decrease in NT-proBNP, but not hs-TnT or sST2. hs-TnT or sST2 are stronger predictors of outcome than NT-proBNP among obese patients.
AIMS: Obesity defined by body mass index (BMI) is characterized by better prognosis and lower plasma N-terminal pro-B-type natriuretic peptide (NT-proBNP) in heart failure. We assessed whether another anthropometric measure, per cent body fat (PBF), reveals different associations with outcome and heart failure biomarkers (NT-proBNP, high-sensitivity troponin T (hs-TnT), soluble suppression of tumorigenesis-2 (sST2)). METHODS: In an individual patient dataset, BMI was calculated as weight (kg)/height (m) 2 , and PBF through the Jackson-Pollock and Gallagher equations. RESULTS: Out of 6468 patients (median 68 years, 78% men, 76% ischaemic heart failure, 90% reduced ejection fraction), 24% died over 2.2 years (1.5-2.9), 17% from cardiovascular death. Median PBF was 26.9% (22.4-33.0%) with the Jackson-Pollock equation, and 28.0% (23.8-33.5%) with the Gallagher equation, with an extremely strong correlation (r = 0.996, p < 0.001). Patients in the first PBF tertile had the worst prognosis, while patients in the second and third tertile had similar survival. The risks of all-cause and cardiovascular death decreased by up to 36% and 27%, respectively, per each doubling of PBF. Furthermore, prognosis was better in the second or third PBF tertiles than in the first tertile regardless of model variables. Both BMI and PBF were inverse predictors of NT-proBNP, but not hs-TnT. In obesepatients (BMI ≥ 30 kg/m2, third PBF tertile), hs-TnT and sST2, but not NT-proBNP, independently predicted outcome. CONCLUSION: In parallel with increasing BMI or PBF there is an improvement in patient prognosis and a decrease in NT-proBNP, but not hs-TnT or sST2. hs-TnT or sST2 are stronger predictors of outcome than NT-proBNP among obesepatients.
Authors: Nick Marcks; Alberto Aimo; James L Januzzi; Giuseppe Vergaro; Aldo Clerico; Roberto Latini; Jennifer Meessen; Inder S Anand; Jay N Cohn; Jørgen Gravning; Thor Ueland; Antoni Bayes-Genis; Josep Lupón; Rudolf A de Boer; Akiomi Yoshihisa; Yasuchika Takeishi; Michael Egstrup; Ida Gustafsson; Hanna K Gaggin; Kai M Eggers; Kurt Huber; Ioannis Tentzeris; Andrea Ripoli; Claudio Passino; Sandra Sanders-van Wijk; Michele Emdin; Hans-Peter Brunner-La Rocca Journal: Clin Res Cardiol Date: 2021-03-11 Impact factor: 6.138