Longitudinally Measured Fibrinolysis Factors are Strong Predictors of Clinical Outcome in Patients with Chronic Heart Failure: The Bio-SHiFT StudyFunding This work was supported by the Jaap Schouten Foundation and the Foreest Medical School.
08. März 2019
23. Juli 2019
28. Oktober 2019 (online)
Objective This article investigates whether longitudinally measured fibrinolysis factors are associated with cardiac events in patients with chronic heart failure (CHF).
Methods A median of 9 (interquartile range [IQR] 5–10) serial, tri-monthly blood samples per patient were prospectively collected in 263 CHF patients during a median follow-up of 2.2 (IQR 1.4–2.5) years. Seventy patients (cases) reached the composite endpoint of cardiac death, heart failure hospitalization, left ventricular assist device, or heart transplantation. From all longitudinal samples, we selected baseline samples in all patients and the last two samples before the event in cases or the last sample available in event-free patients. Herein, we measured plasminogen activator inhibitor 1 (PAI-1), tissue-type plasminogen activator (tPA), urokinase-type plasminogen activator (uPA), and soluble urokinase plasminogen activator surface receptor (suPAR). Associations between temporal biomarker patterns during follow-up and the cardiac event were investigated using a joint model.
Results Cases were on average older and showed higher New York Heart Association class than those who remained event-free. They also had lower blood pressures, and were more likely to have diabetes, renal failure, and atrial fibrillation. Longitudinally measured PAI-1, uPA, and suPAR were independently associated with adverse cardiac events after correction for clinical characteristics (hazard ratio [95% confidence interval]) per standard deviation increase of 2.09 (1.28–3.45) for PAI-1, 1.91 (1.18–3.24) for uPA, and 3.96 (2.48–6.63) for suPAR. Serial measurements of tPA were not significantly associated with the event after correction for multiple testing.
Conclusion Longitudinally measured PAI-1, uPA, and suPAR are strongly associated with adverse cardiac events during the course of CHF. If future research confirms our results, these fibrinolytic factors may carry potential for improved, and personalized, heart failure surveillance and treatment monitoring.
- 1 Gurbel PA, Tantry US. Antiplatelet and anticoagulant agents in heart failure: current status and future perspectives. JACC Heart Fail 2014; 2 (01) 1-14
- 2 Lip GY, Gibbs CR. Does heart failure confer a hypercoagulable state? Virchow's triad revisited. J Am Coll Cardiol 1999; 33 (05) 1424-1426
- 3 Zannad F, Stough WG, Regnault V. , et al. Is thrombosis a contributor to heart failure pathophysiology? Possible mechanisms, therapeutic opportunities, and clinical investigation challenges. Int J Cardiol 2013; 167 (05) 1772-1782
- 4 Freudenberger RS, Hellkamp AS, Halperin JL. , et al. Risk of thromboembolism in heart failure: an analysis from the Sudden Cardiac Death in Heart Failure Trial (SCD-HeFT). Circulation 2007; 115 (20) 2637-2641
- 5 Loh E, Sutton MSJ, Wun C-CC. , et al. Ventricular dysfunction and the risk of stroke after myocardial infarction. N Engl J Med 1997; 336 (04) 251-257
- 6 Jug B, Vene N, Salobir BG, Sebestjen M, Sabovic M, Keber I. Prognostic impact of haemostatic derangements in chronic heart failure. Thromb Haemost 2009; 102 (02) 314-320
- 7 Koller L, Stojkovic S, Richter B. , et al. Soluble urokinase-type plasminogen activator receptor improves risk prediction in patients with chronic heart failure. JACC Heart Fail 2017; 5 (04) 268-277
- 8 Winter MP, Kleber ME, Koller L. , et al. Prognostic significance of tPA/PAI-1 complex in patients with heart failure and preserved ejection fraction. Thromb Haemost 2017; 117 (03) 471-478
- 9 van Boven N, Battes LC, Akkerhuis KM. , et al. Toward personalized risk assessment in patients with chronic heart failure: detailed temporal patterns of NT-proBNP, troponin T, and CRP in the Bio-SHiFT study. Am Heart J 2018; 196: 36-48
- 10 Dickstein K, Cohen-Solal A, Filippatos G. , et al; ESC Committee for Practice Guidelines (CPG). ESC guidelines for the diagnosis and treatment of acute and chronic heart failure 2008: the Task Force for the diagnosis and treatment of acute and chronic heart failure 2008 of the European Society of Cardiology. Developed in collaboration with the Heart Failure Association of the ESC (HFA) and endorsed by the European Society of Intensive Care Medicine (ESICM). Eur J Heart Fail 2008; 10 (10) 933-989
- 11 Assarsson E, Lundberg M, Holmquist G. , et al. Homogenous 96-plex PEA immunoassay exhibiting high sensitivity, specificity, and excellent scalability. PLoS One 2014; 9 (04) e95192
- 12 Simon DI, Ezratty AM, Loscalzo J. The fibrin(ogen)olytic properties of cathepsin D. Biochemistry 1994; 33 (21) 6555-6563
- 13 Pinheiro J, Bates D, Deb Roy S, Sarkar D. R Core Team (2014) nlme: linear and nonlinear mixed effects models. R package version 3.1–117. 2014. Available at: http://CRAN.R-project.org/package=nlme . Accessed August 22, 2019
- 14 Rizopoulos D. The R package JMbayes for fitting joint models for longitudinal and time-to-event data using MCMC. 2014 . Available at: arXiv preprint arXiv:1404.7625. Accessed August 22, 2019
- 15 Chen J, Normand S-LT, Wang Y, Krumholz HM. National and regional trends in heart failure hospitalization and mortality rates for Medicare beneficiaries, 1998-2008. JAMA 2011; 306 (15) 1669-1678
- 16 Solomon SD, Dobson J, Pocock S. , et al; Candesartan in Heart failure: Assessment of Reduction in Mortality and morbidity (CHARM) Investigators. Influence of nonfatal hospitalization for heart failure on subsequent mortality in patients with chronic heart failure. Circulation 2007; 116 (13) 1482-1487
- 17 Rizopoulos D. Joint Models for Longitudinal and Time-to-Event Data: With Applications in R. Boca Raton, FL: CRC Press; 2012
- 18 Chapin JC, Hajjar KA. Fibrinolysis and the control of blood coagulation. Blood Rev 2015; 29 (01) 17-24
- 19 Thunø M, Macho B, Eugen-Olsen J. suPAR: the molecular crystal ball. Dis Markers 2009; 27 (03) 157-172