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临床和社会人口因素与新南威尔士州结直肠癌患者术后院内死亡的相关性:人工神经网络方法。

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.

机构信息

Research School of Population Health, Australian National University, Canberra, Australia.

出版信息

J Eval Clin Pract. 2020 Oct;26(5):1389-1398. doi: 10.1111/jep.13318. Epub 2019 Nov 16.

DOI:10.1111/jep.13318
PMID:31733029
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.

摘要

背景、目的和目标:结直肠癌患者的合并症使医院治疗复杂化,其对术后死亡的相对重要性在很大程度上尚不清楚。本研究旨在检查一系列临床和社会人口统计学因素与结直肠癌患者术后院内死亡的关系,并确定这些因素的贡献是否因合并症的严重程度而有所不同。

方法

在这项多中心回顾性队列研究中,我们使用新南威尔士州住院患者数据的完整普查,选择 2001 年 7 月至 2014 年 6 月期间在公立医院接受急性外科治疗的结直肠癌患者,这些患者接受消化系统手术。主要结局是急性治疗结束时的院内死亡。我们使用多层感知器和反向传播人工神经网络(ANN)来量化与术后死亡相关的广泛临床和社会人口统计学因素的相对重要性,这些因素根据 Charlson 合并症指数按合并症严重程度分层。

结果

在 6288 例结直肠癌患者中,约 58.3%(n=3669)有中度至重度合并症。共有 464 例(7.4%)在医院死亡。ANN 模型的性能优于逻辑模型。合并的肌肉骨骼和精神障碍、医疗保健中的不良事件以及农村居住和私人保险状况等社会经济因素导致了医院内的术后死亡。

结论

使用 ANN 识别导致结直肠癌患者院内死亡的因素的相对重要性,可能有助于增强以患者为中心的策略,以满足急性外科治疗期间的复杂需求,并预防术后院内死亡。

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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.临床和社会人口因素与新南威尔士州结直肠癌患者术后院内死亡的相关性:人工神经网络方法。
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