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International Journal of Clinical and Experimental Medicine Research

ISSN Online: 2575-7970 ISSN Print: 2575-7989 CODEN: IJCEMH
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ArticleOpen Access http://dx.doi.org/10.26855/ijcemr.2023.04.029

A Nomogram to Predict the Risk of Low Cardiac Output Syndrome after Heart Valve Replacement in Cardiac Valvular Disease Patients

Qiushan Qing1,#, Xin Wei1,#, Hong Zheng1, Zhi Wen2, Xiaokang Sun2, Junrong Yang2, Peirui Chen2,*

1Department of Ultrasonography, People's Hospital of Deyang, Deyang, Sichuan, China.

2Department of Cardiothoracic Surgery, People's Hospital of Deyang, Deyang, Sichuan, China.

#Both authors contributed equally to this manuscript.

*Corresponding author: Peirui Chen

Published: June 6,2023

Abstract

Background and Aim: Low cardiac output syndrome (LCOS) is a serious postoperative complication, affecting the prognosis of patients underwent heart valve replacement (HVR). We aim to create a nomogram to predict LCOS after HVR in cardiac valvular disease patients. Methods: We performed a retrospective review of 500 cardiac valvular disease patients underwent HVR from 2016 to 2020 in our department. Univariate analysis evaluated the associations between clinical/echocardiographic parameters and LCOS. Independent t‐test or Mann–Whitney U‐test: for continuous variables. Fisher's exact test or χ2 test: for categorical variables. Variables with a P < 0.05 in the univariate analysis were entered into least absolute shrinkage and selection operator (LASSO) regression to select factors. Then, multivariable logistic regression was performed to develop the predictive model and a nomogram. Results: Of 500 patients, 92 developed postoperative LCOS (18.4%). The nomogram included the following variables: body mass index (BMI), left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS). The nomogram showed favorable calibration and favorite performance for LCOS detection with C-index 0.826 in the development group and 0.783 in validation group. Conclusions: We created a nomogram of predicting postoperative LCOS in cardiac valvular disease patients received HVR. This nomogram could be an important tool of LCOS risk prediction after HVR to guide the therapeutic strategy in cardiac valvular disease patients.

Keywords

Nomogram, low cardiac output syndrome, heart valve replacement

References

[1] Domenech B, Pomar JL, Prat-González S, et al. (2016). Valvular Heart Disease Epidemics. J Heart Valve Dis., 2016; 25: 1-7.

[2] Vahanian A, Alfieri O, Andreotti F, et al. (2012). Guidelines on the management of valvular heart disease (version 2012): the Joint Task Force on the Management of Valvular Heart Disease of the European Society of Cardiology (ESC) and the European Association for Cardio-Thoracic Surgery (EACTS). Eur J Cardiothorac Surg., 2012; 42: S1-44.

[3] Maganti MD, Rao V, Borger MA, et al. (2005). Predictors of low cardiac output syndrome after isolated aortic valve surgery. Circulation, 2005; 112: I448-452.

[4] Lomivorotov VV, Efremov SM, Kirov MY, et al. (2017). Low-Cardiac-Output Syndrome After Cardiac Surgery. J Cardiothorac Vasc Anesth, 2017; 31: 291-308.

[5] Duncan AE, Kartashov A, Robinson SB, et al. (2020). Risk factors, resource use, and cost of postoperative low cardiac output syndrome. J Thorac Cardiovasc Surg, 2020.

[6] Maganti M, Badiwala M, Sheikh A, et al. (2010). Predictors of low cardiac output syndrome after isolated mitral valve surgery. J Thorac Cardiovasc Surg, 2010; 140: 790-796.

[7] Balderas-Muñoz K, Rodríguez-Zanella H, Fritche-Salazar JF, et al. (2017). Improving risk assessment for post-surgical low cardiac output syndrome in patients without severely reduced ejection fraction undergoing open aortic valve replacement. The role of global longitudinal strain and right ventricular free wall strain. Int J Cardiovasc Imaging, 2017; 33: 1483-1489.

[8] Yijun. L, Sheng. D, Rongsheng. X. (2014). Risk factors for low cardiac discharge syndrome in elderly patients after cardiac valve replacement. Guangxi Medical Journal, 2014; 36: 770-772.

[9] Sauerbrei W, Royston P, Binder H. (2007). Selection of important variables and determination of functional form for continuous predictors in multivariable model building. Stat Med, 2007; 26: 5512-5528.

[10] Lu, J., Shi, M., Dong, N., Zhang, Y., Cheng, W., Gao, H., ... & Ge, J. (2022). Preoperative sST2 and NT-proBNP predict the risk of low cardiac output syndrome after cardiac surgery. The Annals of Thoracic Surgery, 113(1), 95-102.

[11] Tabata, N., Sakaguchi, T., Tsuruta, H., Yamamoto, K., Kuroda, Y., Inoue, M., ... & Matsuura, Y. (2021). Preoperative frailty index predicts low cardiac output syndrome after valve surgery. Journal of Cardiac Surgery, 36(11), 3966-3972.

[12] Chen, J., Liu, B., Zhang, M., Yang, J., Li, J., Li, T., ... & Hu, S. (2021). Predictive value of serum NT-proBNP in patients with low ejection fraction after mitral or aortic valve replacement. Frontiers in Cardiovascular Medicine, 8, 23.

[13] Lomivorotov, V. V., Efremov, S. M., Boboshko, V. A., Nikolaev, D. A., Vedernikov, P. E., Tatarinov, O. A., ... & Karaskov, A. M. (2019). Multi-marker approach in predicting low cardiac output syndrome after cardiac surgery: B-type natriuretic peptide, high-sensitivity C-reactive protein, and uric acid. Journal of Cardiothoracic and Vascular Anesthesia, 33(4), 1025-1032.

[14] Rosenhek, R., Binder, T., Maurer, G., Baumgartner, H., Rader, F., & Bach, D. S. (2017). Predictors of outcome in severe, asymptomatic aortic stenosis. The New England Journal of Medicine, 377(9), 830-841.

How to cite this paper

A Nomogram to Predict the Risk of Low Cardiac Output Syndrome after Heart Valve Replacement in Cardiac Valvular Disease Patients

How to cite this paper:  Qiushan Qing, Xin Wei, Hong Zheng, Zhi Wen, Xiaokang Sun, Junrong Yang, Peirui Chen. (2023) A Nomogram to Predict the Risk of Low Cardiac Output Syndrome after Heart Valve Replacement in Cardiac Valvular Disease Patients. International Journal of Clinical and Experimental Medicine Research7(2), 255-259.

DOI: http://dx.doi.org/10.26855/ijcemr.2023.04.029