Analysis of Influencing Factors on Survival Time of Patients with Heart Failure
- 1 School of Science, East China University of Science and Technology, Shanghai, China
- 2 School of Science, East China University of Science and Technology, Shanghai, China
- 3 School of Information Science and Engineering, East China University of Science and Technology, Shanghai, China
Abstract
To explore the influencing factors of survival time of patients with heart failure, a total of 1789 patients with heart failure were collected from Shanghai Shuguang Hospital. The Cox proportional hazards model and the mixed effects Cox model were used to analyze the factors on survival time of patients. The results of Cox proportional hazards model showed that age (RR = 1.32), hypertension (RR = 0.67), ARB (RR = 0.55), diuretic (RR = 1.48) and antiplatelet (RR = 0.53) have significant impacts on the survival time of patients. The results of mixed effects Cox model showed that age (RR = 1.16), hypertension (RR = 0.61), lung infection (RR = 1.43), ARB (RR = 0.64), β -blockers (RR = 0.77) and antiplatelet (RR = 0.69) have a significant impact on the survival time of patients. The results are consistent with the covariates age, hypertension, ARB and antiplatelet but inconsistent with the covariates lung infection and β -blockers.
- Mosterd, A. and Hoes, A.W. (2007) Clinical Epidemiology of Heart Failure. Heart, 93, 1137-1146. https://doi.org/10.1136/hrt.2003.025270
- McMurray, J.J., Adamopoulos, S., Anker, S.D., et al. (2012) ESC Guidelines for the Diagnosis and Treatment of Acute and Chronic Heart Failure. European Heart Journal, 33, 1787-1146.
- Cowie, M.R., Wood, D.A., Coats, A.J., et al. (1999) Incidence an Aetiology of Heart Failure: A Population-Based Study. European Heart Journal, 20, 421-428. https://doi.org/10.1053/euhj.1998.1280
- Guo, Y., Zhao, D. and Liu, J. (2015) Epidemiological Study of Heart Failure in China. Cardiovascular Innovations and Applications, 1, 47-55. https://doi.org/10.15212/CVIA.2015.0003
- Gu, D.F., Huang, G.Y., He, J., et al. (2003) Investigation of Prevalence and Distribution Feature of Chronic Heart Failure in Chinese Adult Population. Chinese Journal Cardio, 1, 3-6.
- Bland, J.M. (2000) An Introduction to Medical Statistics. 3rd Edition, Oxford University Press, New York.
- Kirkwood, B.R. and Sterne, J.C. (2003) Essential Medical Statistics. 2nd Edition, Blackwell Publishers, Malden.
- Klein, J.P. (2013) Handbook of Survival Analysis. CRC Press, Boca Raton.
- Lawless, J.F. (2003) Statistical Models and Methods for Lifetime Data. 2nd Edition, John Wiley and Sons, New York.
- Kalbfleisch, J.D. and Prentice, R.L. (2002) The Statistical Analysis of Failure Time Data. John Wiley and Sons, New York. https://doi.org/10.1002/9781118032985
- Cox, D.R. (1972) Regression Models and Lifetables (with Discussion). Journal of the Royal Statistical Society B, 34, 187-220.
- Frees, E. (2004) Longitudinal and Panel Data: Analysis and Applications in the Social Sciences. Cambridge University Press, New York. https://doi.org/10.1017/CBO9780511790928
- Diggle, P.J., Heagerty, P., Liang, K.-Y. and Zeger, S.L. (2002) Analysis of Longitudinal Data. 2nd Edition, Oxford University Press, Oxford.
- Therneau. T.M. (2015) Mixed Effects Cox Models. BMC Genetics, 6, S127.
- Therneau, T.M. and Grambsch, P.M. (2000) Modeling Survival Data: Extending the Cox Model. Springer, New York. https://doi.org/10.1007/978-1-4757-3294-8
- Wooldridge, J.M. (2013) Introductory Econometrics: A Modern Approach. 5th Edition, South-Western, Mason, OH.