Cultural advice

The Australian National University acknowledges, celebrates and pays our respects to the Ngunnawal and Ngambri people of the Canberra region and to all First Nations Australians on whose traditional lands we meet and work, and whose cultures are among the oldest continuing cultures in human history.

Aboriginal and Torres Strait Islander peoples are advised that ANU Library collections may include images, names, voices, and other representations of deceased persons.

Material in the collection may contain terms, language or views that reflect the period in which the item was created and may be considered inappropriate today.

Relative importance of clinical and sociodemographic factors in association with post-operative in-hospital deaths in colorectal cancer patients in New South Wales: An artificial neural network approach

Loading...
Thumbnail Image

Date

Authors

Sha, Sha
Du, Wei
Parkinson, Anne
Glasgow, Nicholas

Journal Title

Journal ISSN

Volume Title

Publisher

Blackwell Publishing Inc.

Abstract

Rationale, Aims and Objectives Co‐morbidities in colorectal cancer patients complicate hospital care, and their relative importance to post‐operative deaths is largely unknown. This study was conducted to examine a range of clinical and sociodemographic factors in relation to post‐operative in‐hospital deaths in colorectal cancer patients and identify whether these contributions would vary by severity of co‐morbidities. Methods In this multicentre retrospective cohort study, we used the complete census of New South Wales inpatient data to select colorectal cancer patients admitted to public hospitals for acute surgical care, who underwent procedures on the digestive system during the period of July 2001 to June 2014. The primary outcome was in‐hospital death at the end of acute care. Multilayer perceptron and back‐propagation artificial neural networks (ANNs) were used to quantify the relative importance of a wide range of clinical and sociodemographic factors in relation to post‐operative deaths, stratified by severity of co‐morbidities based on Charlson co‐morbidity index. Results Of 6288 colorectal cancer patients, approximately 58.3% (n = 3669) had moderate to severe co‐morbidities. A total of 464 (7.4%) died in hospitals. The performance for ANN models was superior to logistic models. Co‐morbid musculoskeletal and mental disorders, adverse events in health care, and socio‐economic factors including rural residence and private insurance status contributed to post‐operative deaths in hospitals. Conclusion Identification of relative importance of factors contributing to in‐hospital deaths in colorectal cancer patients using ANN may help to enhance patient‐centred strategies to meet complex needs during acute surgical care and prevent post‐operative in‐hospital deaths.

Description

Keywords

Citation

Source

Journal of Evaluation in Clinical Practice

Book Title

Entity type

Access Statement

License Rights

Restricted until

2037-12-31