Skip to main content

Advertisement

SpringerLink
Log in

Prognostic value of myocardial perfusion imaging in patients with chronic kidney disease: A systematic review and meta-analysis

  • ORIGINAL ARTICLE
  • Published:
Journal of Nuclear Cardiology Aims and scope

Abstract

Background

We performed a systematic review and meta-analysis to investigate the prognostic value of stress myocardial perfusion single-photon emission computed tomography (MPS) in predicting adverse cardiovascular events in patients with chronic kidney disease (CKD).

Methods

Studies published from inception until July 2020 were identified by PubMed and Embase databases search. Studies were included if they evaluated CKD patients referred for stress MPS, providing data on adjusted hazard ratio (HR) for the occurrence of adverse events. For studies providing only non-adjusted HR, the univariable risk estimate was included in the analysis. Pooled HR and 95% confidence interval (CI) were estimated using a random effects model to compare patients with abnormal and normal MPS. Whenever possible, incidence rate ratio (IRR) was also calculated and pooled.

Results

Sixteen eligible studies were identified including 7834 patients with a follow-up range from 1 to 4.4 years. Eleven articles included patients with end-stage renal disease (IV-V CKD stage), 3 articles with III-V CKD stage and 2 articles with I-V CKD stage. The pooled HR for the occurrence of adverse events was 2.02 (95% CI 1.68-2.42) and heterogeneity was 34%. Among the included studies, 5 reported the HR for the occurrence of hard events, with a pooled HR of 2.36 (95% CI 1.77-3.13). A total of 8 studies reported data useful to calculate the IRR in patients with normal and abnormal perfusion. The pooled IRR was 2.37 (95% CI 1.63-3.47) and heterogeneity was 60%. At meta-regression analysis, we found an association between HR for adverse events and age, hypertension and smoking, while no significant association was found between HR for hard events and demographic and clinical variables.

Conclusions

In patients with CKD an abnormal myocardial perfusion at stress MPS is associated with adverse cardiovascular events.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8

Similar content being viewed by others

Abbreviations

CKD:

Chronic kidney disease

CAD:

Coronary artery disease

ESRD:

End-stage renal disease

MPS:

Myocardial perfusion single-photon emission computed tomography

HR:

Hazard ratio

QUIPS:

Quality in prognostic studies

CI:

Confidence interval

IRR:

Incidence rate ratio

References

  1. Sarnak MJ, Amann K, Bangalore S, Cavalcante JL, Charytan DM, Craig JC, et al. Chronic kidney disease and coronary artery disease: JACC state-of-the-art review. J Am Coll Cardiol 2019;74:1823-38.

    Article  CAS  PubMed  Google Scholar 

  2. Shroff GR, Chang TI. Risk stratification and treatment of coronary disease in chronic kidney disease and end-stage kidney disease. Rev Semin Nephrol 2018;38:582-99.

    Article  Google Scholar 

  3. Levi A, Simard T, Glover C. Coronary artery disease in patients with end-stage kidney disease; current perspective and gaps of knowledge. Semin Dial 2020;33:187-97.

    Article  PubMed  Google Scholar 

  4. Winther S, Svensson M, Jørgensen HS, Rasmussen LD, Holm NR, Gormsen LC, et al. Prognostic value of risk factors, calcium score, coronary CTA, myocardial perfusion imaging, and invasive coronary angiography in kidney transplantation candidates. JACC Cardiovasc Imaging 2018;11:842-54.

    Article  PubMed  Google Scholar 

  5. Al-Mallah MH, Hachamovitch R, Dorbala S, Di Carli MF. Incremental prognostic value of myocardial perfusion imaging in patients referred to stress single-photon emission computed tomography with renal dysfunction. Circ Cardiovasc Imaging 2009;2:429-36.

    Article  PubMed  Google Scholar 

  6. Rabbat CG, Treleaven DJ, Russell JD, Ludwin D, Cook DJ. Prognostic value of myocardial perfusion studies in patients with end-stage renal disease assessed for kidney or kidney-pancreas transplantation: A meta-analysis. J Am Soc Nephrol 2003;14:431-9.

    Article  PubMed  Google Scholar 

  7. Chew CG, Unger S, Shakib S. Value of myocardial perfusion imaging in renal transplant evaluation. Nephrology 2013;18:376-81.

    Article  PubMed  Google Scholar 

  8. Hage FG, Smalheiser S, Zoghbi GJ, Perry GJ, Deierhoi M, Warnock D, et al. Predictors of survival in patients with end-stage renal disease evaluated for kidney transplantation. Am J Cardiol 2007;100:1020-5.

    Article  PubMed  Google Scholar 

  9. Wang LW, Masson P, Turner RM, Lord SW, Baines LA, Craig JC, et al. Prognostic value of cardiac tests in potential kidney transplant recipients: A systematic review. Transplantation 2015;99:731-45.

    Article  PubMed  Google Scholar 

  10. Helve S, Nieminen T, Helanterä I, Finne P, Rajala H, Sinisalo J, et al. The value of myocardial perfusion imaging in screening coronary artery disease before kidney transplantation. Clin Transplant 2020;34(8):e13894.

    Article  CAS  PubMed  Google Scholar 

  11. Spruance SL, Reid JE, Grace M, Samore M. Hazard ratio in clinical trials. Antimicrob Agents Chemother 2004;48:2787-92.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Moher D, Liberati A, Tetzlaff J, Altman DG, PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Med 2009;6:e1000097.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Hayden JA, Côté P, Bombardier C. Evaluation of the quality of prognosis studies in systematic reviews. Ann Intern Med 2006;144:427-37.

    Article  PubMed  Google Scholar 

  14. Tierney JF, Stewart LA, Ghersi D, Burdett S, Sydes MR. Practical methods for incorporating summary time-to-event data into meta-analysis. Trials 2007;8:16.

    Article  PubMed  PubMed Central  Google Scholar 

  15. DerSimonian R, Laird N. Meta-analysis in clinical trials. Control Clin Trials 1986;7:177-88.

    Article  CAS  PubMed  Google Scholar 

  16. Cleophas TJ, Zwinderman AH. Meta-analysis. Circulation 2007;115:2870-5.

    Article  PubMed  Google Scholar 

  17. Higgins JP, Thompson SG. Quantifying heterogeneity in a meta-analysis. Stat Med 2002;21:1539-58.

    Article  PubMed  Google Scholar 

  18. Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ 1997;315:629-34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Duval S, Tweedie R. A nonparametric “trim and fill” method of accounting for publication bias in meta-analysis. J Am Stat Assoc 2000;95:89-98.

    Google Scholar 

  20. Duval S, Tweedie R. Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics 2000;56:455-63.

    Article  CAS  PubMed  Google Scholar 

  21. Wallace BC, Schmid CH, Lau J, Trikalinos TA. Meta-Analyst: software for meta-analysis of binary, continuous and diagnostic data. BMC Med Res Methodol 2009;9:80.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Hakeem A, Bhatti S, Dillie KS, Cook JR, Samad Z, Roth-Cline MD, et al. Predictive value of myocardial perfusion single-photon emission computed tomography and the impact of renal function on cardiac death. Circulation 2008;118:2540-9.

    Article  PubMed  Google Scholar 

  23. Chan MY, Wong HB, Ong HY, Yeo TC. Prognostic value of left atrial size in chronic kidney disease. Eur J Echocardiogr 2008;9:736-40.

    Article  PubMed  Google Scholar 

  24. Venkataraman R, Hage FG, Dorfman T, Heo J, Aqel RA, de Mattos AM, et al. Role of myocardial perfusion imaging in patients with end-stage renal disease undergoing coronary angiography. Am J Cardiol 2008;102:1451-6.

    Article  PubMed  Google Scholar 

  25. De Vriese AS, De Bacquer DA, Verbeke FH, De Winter O, Franken PR, De Sutter JH, et al. Comparison of the prognostic value of dipyridamole and dobutamine myocardial perfusion scintigraphy in hemodialysis patients. Kidney Int 2009;76:428-36.

    Article  PubMed  Google Scholar 

  26. Hatta T, Nishimura S, Nishimura T. Prognostic risk stratification of myocardial ischaemia evaluated by gated myocardial perfusion SPECT in patients with chronic kidney disease. Eur J Nucl Med Mol Imaging 2009;36:1835-41.

    Article  PubMed  Google Scholar 

  27. Furuhashi T, Moroi M, Joki N, Hase H, Masai H, Kunimasa T, et al. Impact of chronic kidney disease and stress myocardial perfusion imaging as a predictor of cardiovascular events. Ann Nucl Med 2011;25:616-24.

    Article  PubMed  Google Scholar 

  28. Kim JK, Kim SG, Kim HJ, Song YR. Cardiac risk assessment by gated single-photon emission computed tomography in asymptomatic end-stage renal disease patients at the start of dialysis. J Nucl Cardiol 2012;19:438-47.

    Article  PubMed  Google Scholar 

  29. Joki N, Hase H, Kawano Y, Nakamura S, Nakajima K, Hatta T, et al. Myocardial perfusion imaging for predicting cardiac events in Japanese patients with advanced chronic kidney disease: 1-year interim report of the J-ACCESS 3 investigation. Eur J Nucl Med Mol Imaging 2014;4:1701-9.

    Article  Google Scholar 

  30. Moody WE, Lin EL, Stoodley M, McNulty D, Thomson LE, Berman DS, et al. Prognostic utility of calcium scoring as an adjunct to stress myocardial perfusion scintigraphy in end-stage renal disease. Am J Cardiol 2016;117:1387-96.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. Callan PD, Bhandari S, Clark AL, Eadington D, Papadopoulos E, Tweddel AC. The utility of myocardial perfusion imaging before renal transplantation: A retrospective analysis. Nucl Med Commun 2018;39:228-35.

    Article  PubMed  Google Scholar 

  32. Helve S, Laine M, Sinisalo J, Helanterä I, Hänninen H, Lammintausta O, et al. Even mild reversible myocardial perfusion defects predict mortality in patients evaluated for kidney transplantation. Eur Heart J Cardiovasc Imaging 2018;19:1019-25.

    Article  PubMed  Google Scholar 

  33. Park GH, Song JW, Lee CM, Song YR, Kim SG, Kim HJ, et al. Long-term prognosis of end-stage renal disease patients with normal myocardial perfusion as determined by single photon emission computed tomography. Korean J Intern Med 2018;33:148-56.

    Article  PubMed  Google Scholar 

  34. Kolkailah AA, Iskander M, Iskander F, Patel PP, Khan R, Doukky R. The prognostic utility of regadenoson SPECT myocardial perfusion imaging in patients with end-stage renal disease: The largest cohort to date. J Nucl Cardiol 2020. https://doi.org/10.1007/s12350-020-02259-1.

    Article  PubMed  Google Scholar 

  35. Golzar Y, Doukky R. Stress SPECT myocardial perfusion imaging in end-stage renal disease. Curr Cardiovasc Imaging Rep 2017;10:13.

    Article  PubMed  PubMed Central  Google Scholar 

  36. Kahn MR, Fallahi A, Kim MC, Esquitin R, Robbins MJ. Coronary artery disease in a large renal transplant population: Implications for management. Am J Transplant 2011;11:2665-74.

    Article  CAS  PubMed  Google Scholar 

  37. De Lima JJ, Wolff Gowdak LH, de Paula FJ, Ianhez LE, Franchini Ramires JA, Krieger EM. Validation of a strategy to diagnose coronary artery disease and predict cardiac events in high-risk renal transplant candidates. Coron Artery Dis 2010;21:164-7.

    Article  PubMed  Google Scholar 

  38. Sterne JA, Sutton AJ, Ioannidis JP, Terrin N, Jones DR, Lau J, et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomized controlled trials. BMJ 2011;343:4002.

    Article  Google Scholar 

Download references

Disclosure

V. Cantoni, R. Green, W. Acampa, R. Assante, E. Zampella, C. Nappi, V. Gaudieri, T. Mannarino, A. D’Antonio, M. Petretta, and A. Cuocolo declare that they have no financial conflict of interest.

Author information

Author notes

  1. Valeria Cantoni and Roberta Green equally to the study and are considered as first authors

Authors and Affiliations

  1. Department of Advanced Biomedical Sciences, University Federico II, Via Pansini 5, 80131, Naples, Italy

    Valeria Cantoni PhD, Roberta Green PhD, Wanda Acampa MD, PhD, Roberta Assante MD, PhD, Emilia Zampella MD, PhD, Carmela Nappi MD, PhD, Valeria Gaudieri MD, PhD, Teresa Mannarino MD, Adriana D’Antonio MD & Alberto Cuocolo MD

  2. Institute of Biostructure and Bioimaging, National Council of Research, Naples, Italy

    Wanda Acampa MD, PhD

  3. Department of Translational Medical Sciences, University Federico II, Naples, Italy

    Mario Petretta MD, FAHA

Authors
  1. Valeria Cantoni PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Roberta Green PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Wanda Acampa MD, PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Roberta Assante MD, PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Emilia Zampella MD, PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Carmela Nappi MD, PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Valeria Gaudieri MD, PhD
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Teresa Mannarino MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Adriana D’Antonio MD
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Mario Petretta MD, FAHA
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Alberto Cuocolo MD
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alberto Cuocolo MD.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The authors of this article have provided a PowerPoint file, available for download at SpringerLink, which summarises the contents of the paper and is free for re-use at meetings and presentations. Search for the article DOI on SpringerLink.com.

The authors have also provided an audio summary of the article, which is available to download as ESM, or to listen to via the JNC/ASNC Podcast.

Central illustration

Forest plots for the occurrence of adverse and hard events in patients with chronic kidney disease. HR, hazard ratio; CI, confidence interval.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Cantoni, V., Green, R., Acampa, W. et al. Prognostic value of myocardial perfusion imaging in patients with chronic kidney disease: A systematic review and meta-analysis. J. Nucl. Cardiol. 29, 141–154 (2022). https://doi.org/10.1007/s12350-020-02449-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12350-020-02449-x

Keywords

Search

Navigation