Advertisement

Diabetologia

pp 1–11 | Cite as

Echocardiography improves prediction of major adverse cardiovascular events in a population with type 1 diabetes and without known heart disease: the Thousand & 1 Study

  • Magnus T. JensenEmail author
  • Peter Sogaard
  • Ida Gustafsson
  • Jan Bech
  • Thomas F. Hansen
  • Thomas Almdal
  • Simone Theilade
  • Tor Biering-Sørensen
  • Peter G. Jørgensen
  • Søren Galatius
  • Henrik U. Andersen
  • Peter Rossing
Article

Abstract

Aims/hypothesis

Cardiovascular disease is the most common comorbidity in type 1 diabetes. However, current guidelines do not include routine assessment of myocardial function. We investigated whether echocardiography provides incremental prognostic information in individuals with type 1 diabetes without known heart disease.

Methods

A prospective cohort of individuals with type 1 diabetes without known heart disease was recruited from the outpatient clinic. Follow-up was performed through Danish national registers. The association of echocardiography with major adverse cardiovascular events (MACE) and the incremental prognostic value when added to the clinical Steno T1D Risk Engine were examined.

Results

A total of 1093 individuals were included: median (interquartile range) age 50.2 (39.2–60.3) years and HbA1c 65 (56–74) mmol/mol; 53% men; and mean (SD) BMI 25.5 (3.9) kg/m2 and diabetes duration 25.8 (14.6) years. During 7.5 years of follow-up, 145 (13.3%) experienced MACE. Echocardiography significantly and independently predicted MACE: left ventricular ejection fraction (LVEF) <45% (n = 18) vs ≥45% (n = 1075), HR (95% CI) 3.93 (1.91, 8.08), p < 0.001; impaired global longitudinal strain (GLS), 1.65 (1.17, 2.34) (n = 263), p = 0.005; diastolic mitral early velocity (E)/early diastolic tissue Doppler velocity (e′) <8 (n = 723) vs E/e′ 8–12 (n = 285), 1.59 (1.04, 2.42), p = 0.031; and E/e′ <8 vs E/e′ ≥12 (n = 85), 2.30 (1.33, 3.97), p = 0.003. In individuals with preserved LVEF (n = 1075), estimates for impaired GLS were 1.49 (1.04, 2.15), p = 0.032; E/e′ <8 vs E/e′ 8–12, 1.61 (1.04, 2.49), p = 0.033; and E/e′ <8 vs E/e′ ≥12, 2.49 (1.41, 4.37), p = 0.001. Adding echocardiographic variables to the Steno T1D Risk Engine significantly improved risk prediction: Harrell’s C statistic, 0.791 (0.757, 0.824) vs 0.780 (0.746, 0.815), p = 0.027; and net reclassification index, 52%, p < 0.001.

Conclusions/interpretation

In individuals with type 1 diabetes without known heart disease, echocardiography significantly improves risk prediction over and above guideline-recommended clinical risk factors alone and could have a role in clinical care.

Keywords

Cardiovascular Diabetes Echocardiography Heart disease Prognosis Type 1 diabetes 

Abbreviations

CABG

Coronary artery bypass graft

CVD

Cardiovascular disease

e′

Early diastolic tissue Doppler velocity

E

Early mitral peak diastolic velocity

GLS

Global longitudinal strain

IDI

Integrated discrimination improvement

LVEF

Left ventricular ejection fraction

MACE

Major adverse cardiovascular events

NRI

Net reclassification index

PCI

Percutaneous coronary intervention

UAER

Urinary AER

Notes

Acknowledgements

We gratefully express our appreciation to the former Chair of Cardiology J. K. Madsen and the late Professor J. S. Jensen (1962–2018) both from Department of Cardiology, Copenhagen University Hospital Herlev-Gentofte, whose importance for the establishment of the Thousand & 1 Study cannot be overstated. We are indebted to the staff and patients of Steno Diabetes Center Copenhagen for their participation and contribution to the Thousand & 1 Study.

Contribution statement

MTJ made substantial contributions to the conception and design of the work, the acquisition, analysis and interpretation of data and drafting the manuscript and revising it critically for important intellectual content. MTJ gave final approval of the version to be published. MTJ had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. PS, HUA, TA and PR made substantial contributions to the conception and design of the work and interpretation of data; they revised the manuscript critically for important intellectual content and gave final approval of the version to be published. IG, JB, TFH, TA, ST, TB-S, PGJ and SG made substantial contributions to the acquisition and interpretation of data, revised the manuscript critically for important intellectual content and gave final approval of the version to be published.

Funding

The work was supported by The European Foundation for the Study of Diabetes/Pfizer European Programme 2010 for Research into Cardiovascular Risk Reduction in Patients with Diabetes and the Danish Heart Foundation (no. 12-04-R90-A3840-22725). The funding sources had no influence on: the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review nor approval of the manuscript; nor the decision to submit the manuscript for publication.

Duality of interest

MTJ has served as consultant on advisory boards or as an invited speaker for Astra Zeneca, Novo Nordisk, Novartis and GE Healthcare. PGJ has received lecture fees from Novo Nordisk. PR has: board memberships for Astra Zeneca, Astellas, Boehringer Ingelheim, Lilly and Novo Nordisk; received grants and/or has grants pending from Novo Nordisk and Astra Zeneca; received payment for lectures (all payments to institution) from Astra Zeneca/BMS, Novartis and Sanofi Aventis; and stocks in Novo Nordisk. HUA is a member of advisory boards for Abbott, Astra Zeneca and Novo Nordisk, has received lecture fees from Nordic Infucare and has stocks in Novo Nordisk. All other authors declare that there is no duality of interest associated with their contribution to this manuscript.

Supplementary material

125_2019_5009_MOESM1_ESM.pdf (388 kb)
ESM (PDF 388 kb)

References

  1. 1.
    de Ferranti SD, de Boer IH, Fonseca V et al (2014) Type 1 diabetes mellitus and cardiovascular disease: a scientific statement from the American Heart Association and American Diabetes Association. Diabetes Care 37(10):2843–2863.  https://doi.org/10.2337/dc14-1720 CrossRefPubMedPubMedCentralGoogle Scholar
  2. 2.
    Soedamah-Muthu SS, Fuller JH, Mulnier HE, Raleigh VS, Lawrenson RA, Colhoun HM (2006) High risk of cardiovascular disease in patients with type 1 diabetes in the U.K.: a cohort study using the general practice research database. Diabetes Care 29(4):798–804.  https://doi.org/10.2337/diacare.29.04.06.dc05-1433 CrossRefPubMedGoogle Scholar
  3. 3.
    Laing SP, Swerdlow AJ, Slater SD et al (2003) Mortality from heart disease in a cohort of 23,000 patients with insulin-treated diabetes. Diabetologia 46(6):760–765.  https://doi.org/10.1007/s00125-003-1116-6 CrossRefPubMedGoogle Scholar
  4. 4.
    Onkamo P, Väänänen S, Karvonen M, Tuomilehto J (1999) Worldwide increase in incidence of type I diabetes--the analysis of the data on published incidence trends. Diabetologia 42(12):1395–1403.  https://doi.org/10.1007/s001250051309 CrossRefPubMedGoogle Scholar
  5. 5.
    Xu G, Liu B, Sun Y et al (2018) Prevalence of diagnosed type 1 and type 2 diabetes among US adults in 2016 and 2017: population based study. BMJ 362:k1497.  https://doi.org/10.1136/bmj.k1497 CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Rydén L, Grant PJ, Anker SD et al (2013) ESC guidelines on diabetes, pre-diabetes, and cardiovascular diseases developed in collaboration with the EASD: the task force on diabetes, pre-diabetes, and cardiovascular diseases of the European Society of Cardiology (ESC) and developed in collaboration with the European Association for the Study of Diabetes (EASD). Eur Heart J 34(39):3035–3087.  https://doi.org/10.1093/eurheartj/eht108
  7. 7.
    Vistisen D, Andersen GS, Hansen CS et al (2016) Prediction of first cardiovascular disease event in type 1 diabetes mellitus. Circulation 133(11):1058–1066.  https://doi.org/10.1161/CIRCULATIONAHA.115.018844 CrossRefGoogle Scholar
  8. 8.
    BMJ Best Practice (2018) Type 1 diabetes - monitoring. Available from https://bestpractice.bmj.com/topics/en-gb/25/monitoring. Accessed 28 Oct 2018
  9. 9.
    Jensen MT, Sogaard P, Andersen HU et al (2014) Prevalence of systolic and diastolic dysfunction in patients with type 1 diabetes without known heart disease: the Thousand & 1 Study. Diabetologia 57(4):672–680.  https://doi.org/10.1007/s00125-014-3164-5 CrossRefPubMedGoogle Scholar
  10. 10.
    Jensen MT, Sogaard P, Andersen HU et al (2015) Global longitudinal strain is not impaired in type 1 diabetes patients without albuminuria: the Thousand & 1 Study. JACC Cardiovasc Imaging 8(4):400–410.  https://doi.org/10.1016/j.jcmg.2014.12.020 CrossRefPubMedGoogle Scholar
  11. 11.
    Jensen MT, Sogaard P, Andersen HU et al (2016) Early myocardial impairment in type 1 diabetes patients without known heart disease assessed with tissue Doppler echocardiography: the Thousand & 1 study. Diab Vasc Dis Res 13(4):260–267.  https://doi.org/10.1177/1479164116637310 CrossRefPubMedGoogle Scholar
  12. 12.
    Nouhravesh N, Andersen HU, Jensen JS, Rossing P, Jensen MT (2016) Retinopathy is associated with impaired myocardial function assessed by advanced echocardiography in type 1 diabetes patients – the Thousand & 1 Study. Diabetes Res Clin Pract 116:263–269.  https://doi.org/10.1016/j.diabres.2016.04.024 CrossRefPubMedGoogle Scholar
  13. 13.
    Lang RM, Bierig M, Devereux RB et al (2005) Recommendations for chamber quantification: a report from the American Society of Echocardiography’s Guidelines and Standards Committee and the Chamber Quantification Writing Group, developed in conjunction with the European Association of Echocardiography, a branch of the European Society of Cardiology. J Am Soc Echocardiogr 18(12):1440–1463.  https://doi.org/10.1016/j.echo.2005.10.005 CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Nagueh SF, Appleton CP, Gillebert TC et al (2009) Recommendations for the evaluation of left ventricular diastolic function by echocardiography. Eur J Echocardiogr 10(2):165–193.  https://doi.org/10.1093/ejechocard/jep007 CrossRefPubMedGoogle Scholar
  15. 15.
    Delgado V, Mollema SA, Ypenburg C et al (2008) Relation between global left ventricular longitudinal strain assessed with novel automated function imaging and biplane left ventricular ejection fraction in patients with coronary artery disease. J Am Soc Echocardiogr 21(11):1244–1250.  https://doi.org/10.1016/j.echo.2008.08.010 CrossRefPubMedGoogle Scholar
  16. 16.
    Gorcsan J 3rd, Tanaka H (2011) Echocardiographic assessment of myocardial strain. J Am Coll Cardiol 58(14):1401–1413.  https://doi.org/10.1016/j.jacc.2011.06.038 CrossRefPubMedGoogle Scholar
  17. 17.
    Pandey A, Omar W, Ayers C et al (2018) Sex and race differences in lifetime risk of heart failure with preserved ejection fraction and heart failure with reduced ejection fraction. Circulation 137(17):1814–1823.  https://doi.org/10.1161/CIRCULATIONAHA.117.031622 CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Wang Y, Yang H, Huynh Q, Nolan M, Negishi K, Marwick TH (2018) Diagnosis of nonischemic stage b heart failure in type 2 diabetes mellitus: optimal parameters for prediction of heart failure. JACC Cardiovasc Imaging 11(10):1390–1400.  https://doi.org/10.1016/j.jcmg.2018.03.015 CrossRefPubMedGoogle Scholar
  19. 19.
    Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D (1999) A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of diet in renal disease study group. Ann Intern Med 130(6):461–470.  https://doi.org/10.7326/0003-4819-130-6-199903160-00002 CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Vittinghoff E, McCulloch CE (2007) Relaxing the rule of ten events per variable in logistic and Cox regression. Am J Epidemiol 165(6):710–718.  https://doi.org/10.1093/aje/kwk052 CrossRefPubMedGoogle Scholar
  21. 21.
    Pencina M, D’Agostino RS, D’Agostino RJ, Vasan R (2008) Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med 27:11–21Google Scholar
  22. 22.
    Pencina M, D’Agostino RS, Steyerberg EW (2011) Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med 30(1):11–21.  https://doi.org/10.1002/sim.4085 CrossRefPubMedGoogle Scholar
  23. 23.
    Orchard TJ, Stevens LK, Forrest KY, Fuller JH (1998) Cardiovascular disease in insulin dependent diabetes mellitus: similar rates but different risk factors in the US compared with Europe. Int J Epidemiol 27(6):976–983.  https://doi.org/10.1093/ije/27.6.976 CrossRefPubMedGoogle Scholar
  24. 24.
    Rubler S, Dlugash J, Yuceoglu YZ, Kumral T, Branwood AW, Grishman A (1972) New type of cardiomyopathy associated with diabetic glomerulosclerosis. Am J Cardiol 30(6):595–602.  https://doi.org/10.1016/0002-9149(72)90595-4 CrossRefPubMedGoogle Scholar
  25. 25.
    Fang ZY, Prins JB, Marwick TH (2004) Diabetic cardiomyopathy: evidence, mechanisms, and therapeutic implications. Endocr Rev 25(4):543–567.  https://doi.org/10.1210/er.2003-0012 CrossRefPubMedGoogle Scholar
  26. 26.
    Gilbert RE, Connelly K, Kelly DJ, Pollock CA, Krum H (2006) Heart failure and nephropathy: catastrophic and interrelated complications of diabetes. Clin J Am Soc Nephrol 1(2):193–208.  https://doi.org/10.2215/CJN.00540705 CrossRefPubMedGoogle Scholar
  27. 27.
    Fang ZY, Schull-Meade R, Downey M, Prins J, Marwick TH (2005) Determinants of subclinical diabetic heart disease. Diabetologia 48(2):394–402.  https://doi.org/10.1007/s00125-004-1632-z CrossRefPubMedGoogle Scholar
  28. 28.
    Di Bonito P, Moio N, Cavuto L et al (2005) Early detection of diabetic cardiomyopathy: usefulness of tissue Doppler imaging. Diabet Med J Br Diabet Assoc 22(12):1720–1725.  https://doi.org/10.1111/j.1464-5491.2005.01685.x CrossRefGoogle Scholar
  29. 29.
    Salem M, El Behery S, Adly A, Khalil D, El Hadidi E (2009) Early predictors of myocardial disease in children and adolescents with type 1 diabetes mellitus. Pediatr Diabetes 10(8):513–521.  https://doi.org/10.1111/j.1399-5448.2009.00517.x CrossRefPubMedGoogle Scholar
  30. 30.
    Gul K, Celebi AS, Kacmaz F et al (2009) Tissue Doppler imaging must be performed to detect early left ventricular dysfunction in patients with type 1 diabetes mellitus. Eur J Echocardiogr 10(7):841–846.  https://doi.org/10.1093/ejechocard/jep086 CrossRefPubMedGoogle Scholar
  31. 31.
    Lo SS, Leslie RD, Sutton MS (1995) Effects of type 1 diabetes mellitus on cardiac function: a study of monozygotic twins. Br Heart J 73(5):450–455.  https://doi.org/10.1136/hrt.73.5.450 CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Raev DC (1994) Which left ventricular function is impaired earlier in the evolution of diabetic cardiomyopathy? An echocardiographic study of young type I diabetic patients. Diabetes Care 17(7):633–639.  https://doi.org/10.2337/diacare.17.7.633 CrossRefPubMedGoogle Scholar
  33. 33.
    Zarich SW, Arbuckle BE, Cohen LR, Roberts M, Nesto RW (1988) Diastolic abnormalities in young asymptomatic diabetic patients assessed by pulsed Doppler echocardiography. J Am Coll Cardiol 12(1):114–120.  https://doi.org/10.1016/0735-1097(88)90364-6 CrossRefPubMedGoogle Scholar
  34. 34.
    Karamitsos TD, Karvounis HI, Didangelos T, Parcharidis GE, Karamitsos DT (2008) Impact of autonomic neuropathy on left ventricular function in normotensive type 1 diabetic patients: a tissue Doppler echocardiographic study. Diabetes Care 31(2):325–327.  https://doi.org/10.2337/dc07-1634 CrossRefPubMedGoogle Scholar
  35. 35.
    Fang ZY, Yuda S, Anderson V, Short L, Case C, Marwick TH (2003) Echocardiographic detection of early diabetic myocardial disease. J Am Coll Cardiol 41(4):611–617.  https://doi.org/10.1016/S0735-1097(02)02869-3 CrossRefPubMedGoogle Scholar
  36. 36.
    Guha A, Harmancey R, Taegtmeyer H (2008) Nonischemic heart failure in diabetes mellitus. Curr Opin Cardiol 23(3):241–248.  https://doi.org/10.1097/HCO.0b013e3282fcc2fa CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Cook N (2008) Statistical evaluation of prognostic versus diagnostic models: beyond the ROC curve. Clin Chem 54:17–23CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Magnus T. Jensen
    • 1
    • 2
    • 3
    Email author
  • Peter Sogaard
    • 4
  • Ida Gustafsson
    • 5
  • Jan Bech
    • 5
  • Thomas F. Hansen
    • 1
  • Thomas Almdal
    • 6
  • Simone Theilade
    • 2
  • Tor Biering-Sørensen
    • 1
  • Peter G. Jørgensen
    • 1
  • Søren Galatius
    • 5
  • Henrik U. Andersen
    • 2
  • Peter Rossing
    • 2
    • 7
  1. 1.Department of CardiologyCopenhagen University Hospital Herlev-GentofteHellerupDenmark
  2. 2.Steno Diabetes Center CopenhagenCopenhagenDenmark
  3. 3.Department of CardiologyCopenhagen University Hospital RigshospitaletCopenhagenDenmark
  4. 4.Department of Clinical MedicineAalborg University HospitalAalborgDenmark
  5. 5.Department of CardiologyCopenhagen University Hospital BispebjergCopenhagenDenmark
  6. 6.Department of EndocrinologyCopenhagen University Hospital RigshospitaletCopenhagenDenmark
  7. 7.Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health SciencesUniversity of CopenhagenCopenhagenDenmark

Personalised recommendations