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In this study, we use Cox proportional hazards model to analyze the abdominal aortic aneurysms clinical data of Veterans General Hospital in Taipei, Taiwan. The data includes patient’s demographic and characteristic variables, disease history, clinical examination and treatment data. The response variable in this study is hospitalization days. The rest of variables are prognostic factors or covariates that are divided into three categories: chronic disease variables, cardiovascular disease routine tests of pre-surgery and 1-day after surgery, as well as general illness variables. The summary statistics of each covariates and the correlation with the response variable are given. The analysis was carried out in three steps. We first obtain the preliminary fitting of the raw data by using the Cox PH model. Because of the large proportion of missing values in the dataset, the missing values are estimated and then the data were analyzed. Finally, by employing the findings of the previous analysis, we obtain the result of fitting the raw dataset into the Cox PH regression model. The stepwise Cox PH regression analysis shows that the significant covariates associated with the hospitalization days (and the hazard ratio) are: PAOD ( 0.705 ), Chronic renal disease ( 0.689 ), Hgb_Pre_op ( 1.091 ), Albumin_Pre_op ( 1.601 ), BUN_Day1 ( 0.982 ) ,Hct_Day1 ( 1.053 ), ASA class ( 0.639 ) , Operative time ( 0.888 ), ICU stay ( 0.968 )and Discharge condition ( 1.887 ).
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