ArticleInternational journal of environmental research and public health2020
Predictive Model of the Risk of In-Hospital Mortality in Colorectal Cancer Surgery, Based on the Minimum Basic Data Set.
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 8 citations in OpenAlex.
- Validation of the Surgical Outcome Risk Tool (SORT) and SORT v2 for Predicting Postoperative Mortality in Patients with Pancreatic Cancer Undergoing Surgery.Journal of clinical medicine · 2023Article
- Validation of the Surgical Outcome Risk Tool (SORT) for Predicting Postoperative Mortality in Colorectal Cancer Patients Undergoing Surgery and Subgroup Analysis.World journal of surgery · 2021Article
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Authors and funding
8 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundVarious models have been proposed to predict mortality rates for hospital patients undergoing colorectal cancer surgery. However, none have been developed in Spain using clinical administrative databases and none are based exclusively on the variables available upon admission. Our study aim is to detect factors associated with in-hospital mortality in patients undergoing surgery for colorectal cancer and, on this basis, to generate a predictive mortality score.
methodsA population cohort for analysis was obtained as all hospital admissions for colorectal cancer during the period 2008-2014, according to the Spanish Minimum Basic Data Set. The main measure was actual and expected mortality after the application of the considered mathematical model. A logistic regression model and a mortality score were created, and internal validation was performed.
results115,841 hospitalization episodes were studied. Of these, 80% were included in the training set. The variables associated with in-hospital mortality were age (OR: 1.06, 95%CI: 1.05-1.06), urgent admission (OR: 4.68, 95% CI: 4.36-5.02), pulmonary disease (OR: 1.43, 95%CI: 1.28-1.60), stroke (OR: 1.87, 95%CI: 1.53-2.29) and renal insufficiency (OR: 7.26, 95%CI: 6.65-7.94). The level of discrimination (area under the curve) was 0.83.
conclusionsThis mortality model is the first to be based on administrative clinical databases and hospitalization episodes. The model achieves a moderate-high level of discrimination.
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