Predictive Model of the Risk of In-Hospital Mortality in Colorectal Cancer Surgery, Based on the Minimum Basic Data Set

• DOI: 10.3390/ijerph17124216
• Publication Date: 2020-06-15T07:17:32Z
• Authors: Juan Manuel Garcí...; María Carmen Olve...; Manuel Ferrer-Már...; Carmen Rosa-Garrido; Miguel Rodríguez-...; María Carmen Lea-...; Francisco Rubio-Gil; María-José Sánchez
• Keywords: Minimum Data Set; Data set

Various models have been proposed to predict mortality rates for hospital patients undergoing colorectal cancer surgery. However, none developed in Spain using clinical administrative databases and are based exclusively on the variables available upon admission. Our study aim is detect factors associated with in-hospital surgery and, this basis, generate a predictive score. A population cohort analysis was obtained as all admissions during period 2008-2014, according Spanish Minimum Basic Data Set. The main measure actual expected after application of considered mathematical model. logistic regression model score were created, internal validation performed. 115,841 hospitalization episodes studied. Of these, 80% included training set. age (OR: 1.06, 95%CI: 1.05-1.06), urgent admission 4.68, 95% CI: 4.36-5.02), pulmonary disease 1.43, 1.28-1.60), stroke 1.87, 1.53-2.29) renal insufficiency 7.26, 6.65-7.94). level discrimination (area under curve) 0.83. This first be episodes. achieves moderate-high discrimination.