A Novel Risk Stratification System for Predicting In-Hospital Mortality Following Coronary Artery Bypass Grafting Surgery with Impaired Left Ventricular Ejection Fraction

Authors

  • Hongyuan Lin, MD Cardiac Surgery Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
  • Jianfeng Hou, MD, PhD Cardiac Surgery Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
  • Hanwei Tang, MD Cardiac Surgery Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
  • Kai Chen, MD Cardiac Surgery Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
  • Shaoxian Guo, MD Cardiac Surgery Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
  • Liqing Wang, MD Cardiac Surgery Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
  • Hansong Sun, MD Cardiac Surgery Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
  • Zhe Zheng, MD, PhD Cardiac Surgery Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
  • Shengshou Hu, MD, PhD Cardiac Surgery Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China

DOI:

https://doi.org/10.1532/hsf.3089

Keywords:

Coronary artery bypass grafting, CABG, Risk assessment, Heart failure, Risk factors, PGLANCE, Ejection fraction

Abstract

Background: Coronary artery disease (CAD) is the most common cause of heart failure (HF), and impaired ejection fraction (EF<50%) is a crucial precursor to HF. Coronary artery bypass grafting (CABG) is an effective surgical solution to CAD-related HF. In light of the high risk of cardiac surgery, appropriate scores for groups of patients are of great importance. We aimed to establish a novel score to predict in-hospital mortality for impaired EF patients undergoing CABG.

Methods: Clinical information of 1,976 consecutive CABG patients with EF<50% was collected from January 2012 to December 2017. A novel system was developed using the logistic regression model to predict in-hospital mortality among patients with EF<50% who were to undergo CABG. The scoring system was named PGLANCE, which is short for seven identified risk factors, including previous cardiac surgery, gender, load of surgery, aortic surgery, NYHA stage, creatinine, and EF. AUC statistic was used to test discrimination of the model, and the calibration of this model was assessed by the Hosmer-lemeshow (HL) statistic. We also evaluated the applicability of PGLANCE to predict
in-hospital mortality by comparing the 95% CI of expected mortality to the observed one. Results were compared with the European Risk System in Cardiac Operations
(EuroSCORE), EuroSCORE II, and Sino System for
Coronary Operative Risk Evaluation (SinoSCORE).

Results: By comparing with EuroSCORE,
EuroSCORE II and SinoSCORE, PGLANCE was well calibrated (HL P = 0.311) and demonstrated powerful discrimination (AUC=0.846) in prediction of in-hospital mortality among impaired EF CABG patients. Furthermore, the 95% CI of mortality estimated by PGLANCE was closest to the observed value.

Conclusion: PGLANCE is better with predicting in-hospital mortality than EuroSCORE, EuroSCORE II, and SinoSCORE for Chinese impaired EF CABG patients.

References

Carosella VC, Navia JL, Alruzzeh S, et al. 2009. The first Latin-American risk stratification system for cardiac surgery: can be used as a graphic pocket-card score. Interact Cardiovasc Thorac Surg. 9(2):203-208.

Choong CK, Sergeant P, Nashef SA, Smith JA, Bridgewater B. 2009. The EuroSCORE risk stratification system in the current era: how accurate is it and what should be done if it is inaccurate? Eur J Cardiothorac Surg. Jan 35(1):59-61.

Edwards FH, Grover FL, Shroyer AL, Schwartz M, Bero J. 1997. The Society of Thoracic Surgeons National Cardiac Surgery Database: current risk assessment. Annals of Thoracic Surgery. 63(3):903-8.

F WSKPA. 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. 35(37):78.

Gardner SC, Grunwald GK, Rumsfeld JS, et al. 2004. Comparison of short-term mortality risk factors for valve replacement versus coronary artery bypass graft surgery. Annals of Thoracic Surgery. 77(2):549-56.

Hannan EL, Wu C, Bennett EV, et al. 2006. Risk stratification of in-hospital mortality for coronary artery bypass graft surgery. Journal of the American College of Cardiology. 47(3):661-668.

Hu S, Zheng Z, Wu Q. 2000. Risk factors of in-hospital mortality of CABG patients: a Chinese experience. 28.

Mark DB, Knight JD, Velazquez EJ, et al. 2011. Quality-of-Life Outcomes in Surgical Treatment of Ischemic Heart Failure Quality-of-Life Outcomes With Coronary Artery Bypass Graft Surgery in Ischemic Left Ventricular Dysfunction: A Randomized Trial. Annals of Internal Medicine. 161(6):392-399.

Nagendran J, Norris CM, Graham MM, et al. 2013. Coronary revascularization for patients with severe left ventricular dysfunction. Annals of Thoracic Surgery. 96(6):2038-2044.

Nashef SA, Roques F, Michel P, Gauducheau E, Lemeshow S, Salamon R. 1999. European system for cardiac operative risk evaluation (EuroSCORE). Eur J Cardiothorac Surg. 16(1):9-13.

Nashef SA, Roques F, Sharples LD, et al. 2012. EuroSCORE II. Eur J Cardiothorac Surg. 41(4):734-744.

Peterson ED, Coombs LP, Ferguson TB, et al. 2002. Hospital variability in length of stay after coronary artery bypass surgery: results from the Society of Thoracic Surgeon's National Cardiac Database. Annals of Thoracic Surgery. 74(2):464-473.

Ponikowski P, Voors AA, Anker SD, et al. 2016. 2016 ESC Guidelines for the Diagnosis and Treatment of Acute and Chronic Heart Failure. European Heart Journal. 18(8):2129.

Varma PK, Kundan S, Ananthanarayanan C, et al. 2014. Demographic profile, clinical characteristics and outcomes of patients undergoing coronary artery bypass grafting—retrospective analysis of 4,024 patients. journal article. Indian Journal of Thoracic and Cardiovascular Surgery. December 01 30(4):272-277.

Velazquez EJ, Lee KL, Deja MA, et al. 2011. Coronary-Artery Bypass Surgery in Patients with Left Ventricular Dysfunction. New England Journal of Medicine. 364(17):1607-16.

Yancy CW, Jessup M, Bozkurt B, et al. 2013. 2013 ACCF/AHA Guideline for the Management of Heart Failure A Report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines. Journal of the American College of Cardiology. 128(16):240-319.

Zheng Z, Li Y, Zhang S, Hu S. 2009. The Chinese coronary artery bypass grafting registry study: how well does the EuroSCORE predict operative risk for Chinese population? Eur J Cardiothorac Surg. Jan 35(1):54-8.

Zheng Z, Zhang L, Hu S, Li X, Yuan X, Gao H. 2012. Risk factors and in-hospital mortality in Chinese patients undergoing coronary artery bypass grafting: analysis of a large multi-institutional Chinese database. J Thorac Cardiovasc Surg. 144(2):355-359.

Zheng Z, Zhang L, Li X, Hu S. 2013. SinoSCORE: A Logistically Derived Additive Prediction Model for Post-Coronary Artery Bypass Grafting In-Hospital Mortality in a Chinese Population. Frontiers of Medicine. 7(4):477-485.

Published

2020-08-28

How to Cite

Lin, H., Hou, J., Tang, H., Chen, K., Guo, S., Wang, L., Sun, H., Zheng, Z., & Hu, S. (2020). A Novel Risk Stratification System for Predicting In-Hospital Mortality Following Coronary Artery Bypass Grafting Surgery with Impaired Left Ventricular Ejection Fraction. The Heart Surgery Forum, 23(5), E621-E626. https://doi.org/10.1532/hsf.3089

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