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Thromb Haemost 2018; 118(01): 054-062
DOI: 10.1160/TH16-12-0964
Coagulation and Fibrinolysis
Schattauer GmbH Stuttgart

Low Self-rated Health Is Related to Blood Hypercoagulability in Patients Admitted with Acute Myocardial Infarction

Roland von Känel
,
Rebecca E. Meister-Langraf
,
Jean-Paul Schmid
,
Jürgen Barth
,
Hansjörg Znoj
,
Ulrich Schnyder
,
Mary Princip
Further Information

Publication History

24 December 2016

24 August 2017

Publication Date:
05 January 2018 (online)

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Abstract

Self-rated health (SRH) is independently associated with all-cause mortality and adverse cardiovascular outcomes in individuals with and without cardiovascular disease. We examined whether SRH relates to haemostatic factors of a hypercoagulable state with prognostic impact in patients admitted with acute myocardial infarction (MI). We assessed 190 patients (median age: 59 years; all Caucasian; 83% men) within 48 hours of an acute coronary intervention in terms of demographic factors, medical and psychiatric comorbidity, health behaviours, cardiac-related variables and psychosocial characteristics. Patients rated their health state before MI retrospectively with the EuroQol Visual Analogue Scale ranging from 0 (‘worst imaginable health state’) to 100 (‘best imaginable health state’). Circulating levels of fibrinogen, fibrin D-dimer and von Willebrand factor (VWF) antigen were measured the morning after hospital referral. The median score of SRH was 75 (range: 20–100). SRH was inversely associated with fibrinogen (r =  − 0.25, p = 0.001) and D-dimer (r =  − 0.17, p = 0.021) levels in the bivariate analysis. Stronger relationships emerged for fibrinogen (r =  − 0.33, p < 0.001), D-dimer (r =  − 0.25, p = 0.001) and also VWF (r =  − 0.19, p = 0.015) levels in fully adjusted linear regression models. As for SRH, the Global Registry of Acute Coronary Events (GRACE) risk score was the only covariate showing an independent association with all haemostatic factors (fibrinogen: r = 0.31, D-dimer: r = 0.29, VWF: r = 0.30; all p-values < 0.001). Lower SRH was associated with greater coagulability in patients with acute MI, independent of covariates and comparable with the GRACE risk score. The findings provide a novel psychobiological mechanism that may potentially link SRH with cardiovascular outcome in patients with an acute coronary syndrome.

Keywords

cardiovascular diseases - coagulation factors - interoception - psychobiology - psychosocial risk factors
 

  • References

  • 1 DeSalvo KB, Bloser N, Reynolds K, He J, Muntner P. Mortality prediction with a single general self-rated health question. A meta-analysis. J Gen Intern Med 2006; 21 (03) 267-275
    CrossrefPubMedGoogle Scholar
  • 2 Mavaddat N, Parker RA, Sanderson S, Mant J, Kinmonth AL. Relationship of self-rated health with fatal and non-fatal outcomes in cardiovascular disease: a systematic review and meta-analysis. PLoS One 2014; 9 (07) e103509
    CrossrefPubMedGoogle Scholar
  • 3 Olson KL, Stiefel M, Ross C. , et al. Self-rated health among patients with coronary artery disease enrolled in a cardiovascular risk reduction service. Popul Health Manag 2016; 19 (01) 24-30
    CrossrefPubMedGoogle Scholar
  • 4 Venskutonyte L, Brismar K, Öhrvik J, Rydén L, Kjellström B. Self-rated health predicts outcome in patients with type 2 diabetes and myocardial infarction: a DIGAMI 2 quality of life sub-study. Diab Vasc Dis Res 2013; 10 (04) 361-367
    CrossrefPubMedGoogle Scholar
  • 5 Thombs BD, Ziegelstein RC, Stewart DE, Abbey SE, Parakh K, Grace SL. Usefulness of a single-item general self-rated health question to predict mortality 12 months after an acute coronary syndrome. Eur J Cardiovasc Prev Rehabil 2008; 15 (04) 479-481
    CrossrefPubMedGoogle Scholar
  • 6 Benyamini Y, Gerber Y, Molshatzki N, Goldbourt U, Drory Y. ; Israel Study Group on First Acute Myocardial Infarction. Recovery of self-rated health as a predictor of recurrent ischemic events after first myocardial infarction: a 13-year follow-up. Health Psychol 2014; 33 (04) 317-325
    CrossrefPubMedGoogle Scholar
  • 7 Jylhä M. What is self-rated health and why does it predict mortality? Towards a unified conceptual model. Soc Sci Med 2009; 69 (03) 307-316
    CrossrefPubMedGoogle Scholar
  • 8 Benyamini Y. Why does self-rated health predict mortality? An update on current knowledge and a research agenda for psychologists. Psychol Health 2011; 26 (11) 1407-1413
    CrossrefPubMedGoogle Scholar
  • 9 Fried LP, Kronmal RA, Newman AB. , et al. Risk factors for 5-year mortality in older adults: the Cardiovascular Health Study. JAMA 1998; 279 (08) 585-592
    CrossrefPubMedGoogle Scholar
  • 10 van der Linde RM, Mavaddat N, Luben R. , et al. Self-rated health and cardiovascular disease incidence: results from a longitudinal population-based cohort in Norfolk, UK. PLoS One 2013; 8 (06) e65290
    CrossrefPubMedGoogle Scholar
  • 11 Jarczok MN, Kleber ME, Koenig J. , et al. Investigating the associations of self-rated health: heart rate variability is more strongly associated than inflammatory and other frequently used biomarkers in a cross sectional occupational sample. PLoS One 2015; 10 (02) e0117196
    CrossrefPubMedGoogle Scholar
  • 12 Janszky I, Lekander M, Blom M, Georgiades A, Ahnve S. Self-rated health and vital exhaustion, but not depression, is related to inflammation in women with coronary heart disease. Brain Behav Immun 2005; 19 (06) 555-563
    CrossrefPubMedGoogle Scholar
  • 13 Dantzer R, O'Connor JC, Freund GG, Johnson RW, Kelley KW. From inflammation to sickness and depression: when the immune system subjugates the brain. Nat Rev Neurosci 2008; 9 (01) 46-56
    CrossrefPubMedGoogle Scholar
  • 14 Irwin MR. Inflammation at the intersection of behavior and somatic symptoms. Psychiatr Clin North Am 2011; 34 (03) 605-620
    CrossrefPubMedGoogle Scholar
  • 15 Kaplan GA, Goldberg DE, Everson SA. , et al. Perceived health status and morbidity and mortality: evidence from the Kuopio ischaemic heart disease risk factor study. Int J Epidemiol 1996; 25 (02) 259-265
    CrossrefPubMedGoogle Scholar
  • 16 Stenholm S, Kivimäki M, Jylhä M. , et al. Trajectories of self-rated health in the last 15 years of life by cause of death. Eur J Epidemiol 2016; 31 (02) 177-185
    CrossrefPubMedGoogle Scholar
  • 17 Borissoff JI, Spronk HM, ten Cate H. The hemostatic system as a modulator of atherosclerosis. N Engl J Med 2011; 364 (18) 1746-1760
    CrossrefPubMedGoogle Scholar
  • 18 Chapman J. Coagulation in inflammatory diseases of the central nervous system. Semin Thromb Hemost 2013; 39 (08) 876-880
    Article in Thieme ConnectPubMedGoogle Scholar
  • 19 Davalos D, Ryu JK, Merlini M. , et al. Fibrinogen-induced perivascular microglial clustering is required for the development of axonal damage in neuroinflammation. Nat Commun 2012; 3: 1227
    CrossrefPubMedGoogle Scholar
  • 20 López JA. Sticky business: von Willebrand factor in inflammation. Blood 2006; 108: 3627
    CrossrefPubMedGoogle Scholar
  • 21 Toss H, Lindahl B, Siegbahn A, Wallentin L. Prognostic influence of increased fibrinogen and C-reactive protein levels in unstable coronary artery disease. FRISC Study Group. Fragmin during Instability in Coronary Artery Disease. Circulation 1997; 96 (12) 4204-4210
    CrossrefPubMedGoogle Scholar
  • 22 Lee KW, Lip GY, Tayebjee M, Foster W, Blann AD. Circulating endothelial cells, von Willebrand factor, interleukin-6, and prognosis in patients with acute coronary syndromes. Blood 2005; 105 (02) 526-532
    CrossrefPubMedGoogle Scholar
  • 23 Oldgren J, Linder R, Grip L, Siegbahn A, Wallentin L. Coagulation activity and clinical outcome in unstable coronary artery disease. Arterioscler Thromb Vasc Biol 2001; 21 (06) 1059-1064
    CrossrefPubMedGoogle Scholar
  • 24 Brügger-Andersen T, Pönitz V, Staines H, Grundt H, Hetland Ø, Nilsen DW. The prognostic utility of D-dimer and fibrin monomer at long-term follow-up after hospitalization with coronary chest pain. Blood Coagul Fibrinolysis 2008; 19 (07) 701-707
    CrossrefPubMedGoogle Scholar
  • 25 Meister R, Princip M, Schmid JP. , et al. Myocardial Infarction - Stress PRevention INTervention (MI-SPRINT) to reduce the incidence of posttraumatic stress after acute myocardial infarction through trauma-focused psychological counseling: study protocol for a randomized controlled trial. Trials 2013; 14: 329
    CrossrefPubMedGoogle Scholar
  • 26 Windecker S, Kolh P, Alfonso F. , et al; Authors/Task Force members. 2014 ESC/EACTS Guidelines on myocardial revascularization: The Task Force on Myocardial Revascularization of the European Society of Cardiology (ESC) and the European Association for Cardio-Thoracic Surgery (EACTS)Developed with the special contribution of the European Association of Percutaneous Cardiovascular Interventions (EAPCI). Eur Heart J 2014; 35 (37) 2541-2619
    CrossrefPubMedGoogle Scholar
  • 27 Roffi M, Patrono C, Collet JP. , et al; Management of Acute Coronary Syndromes in Patients Presenting without Persistent ST-Segment Elevation of the European Society of Cardiology. 2015 ESC Guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation: Task Force for the Management of Acute Coronary Syndromes in Patients Presenting without Persistent ST-Segment Elevation of the European Society of Cardiology (ESC). Eur Heart J 2016; 37 (03) 267-315
    CrossrefPubMedGoogle Scholar
  • 28 Dyer MT, Goldsmith KA, Sharples LS, Buxton MJ. A review of health utilities using the EQ-5D in studies of cardiovascular disease. Health Qual Life Outcomes 2010; 8: 13
    CrossrefPubMedGoogle Scholar
  • 29 von Känel R, Hari R, Schmid JP, Saner H, Begré S. Distress related to myocardial infarction and cardiovascular outcome: a retrospective observational study. BMC Psychiatry 2011; 11: 98
    CrossrefPubMedGoogle Scholar
  • 30 Mitchell PH, Powell L, Blumenthal J. , et al. A short social support measure for patients recovering from myocardial infarction: the ENRICHD Social Support Inventory. J Cardiopulm Rehabil 2003; 23 (06) 398-403
    CrossrefPubMedGoogle Scholar
  • 31 Barth J, Paul J, Klesse C. , et al. Die Diskriminationsleistung des Beck-Depressions-Inventars (BDI) hinsichtlich depressiver Störungen bei Patienten mit einer körperlichen Erkrankung. Z Klin Psychol Psychother 2007; 36: 73-82
    CrossrefPubMedGoogle Scholar
  • 32 Bopp M, Minder CE. ; Swiss National Cohort. Mortality by education in German speaking Switzerland, 1990-1997: results from the Swiss National Cohort. Int J Epidemiol 2003; 32 (03) 346-354
    CrossrefPubMedGoogle Scholar
  • 33 Fox KA, Dabbous OH, Goldberg RJ. , et al. Prediction of risk of death and myocardial infarction in the six months after presentation with acute coronary syndrome: prospective multinational observational study (GRACE). BMJ 2006; 333 (7578): 1091
    CrossrefPubMedGoogle Scholar
  • 34 Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis 1987; 40 (05) 373-383
    CrossrefPubMedGoogle Scholar
  • 35 Banfi G, Del Fabbro M. Biological variation in tests of hemostasis. Semin Thromb Hemost 2008; 34 (07) 635-641
    Article in Thieme ConnectPubMedGoogle Scholar
  • 36 Danesh J, Lewington S, Thompson SG. , et al; Fibrinogen Studies Collaboration. Plasma fibrinogen level and the risk of major cardiovascular diseases and nonvascular mortality: an individual participant meta-analysis. JAMA 2005; 294 (14) 1799-1809
    PubMedGoogle Scholar
  • 37 Ryu JK, Davalos D, Akassoglou K. Fibrinogen signal transduction in the nervous system. J Thromb Haemost 2009; 7 (Suppl. 01) 151-154
    CrossrefPubMedGoogle Scholar
  • 38 Hayes AJ, Clarke PM, Glasziou PG, Simes RJ, Drury PL, Keech AC. Can self-rated health scores be used for risk prediction in patients with type 2 diabetes?. Diabetes Care 2008; 31 (04) 795-797
    CrossrefPubMedGoogle Scholar