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基于日本行政数据的社区获得性肺炎患者住院时间延长预测模型。

Prediction model for prolonged length of stay in patients with community-acquired pneumonia based on Japanese administrative data.

机构信息

Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University, Yoshida Konoe-cho, Sakyo-ku, Kyoto City, Kyoto, 606-8501, Japan.

出版信息

Respir Investig. 2021 Mar;59(2):194-203. doi: 10.1016/j.resinv.2020.08.005. Epub 2020 Nov 8.

Abstract

BACKGROUND

The length of hospital stay in community-acquired pneumonia patients is closely associated with medical costs, the burden of which is increasing in aging societies. Herein, we developed and validated models for predicting prolonged length of stay in community-acquired pneumonia patients to support efficient care in these patients.

METHODS

We obtained data of 32,916 patients hospitalized for pneumonia who were discharged between 2012 and 2013 from 304 acute care hospitals in Japan. Logistic regression models were developed with prolonged length of stay as the outcome and patient characteristics as predictors. The models were internally validated using bootstrapping and externally validated using pneumonia patients discharged in 2014.

RESULTS

The median length of stay was 11 (interquartile range, 8-17) days. The following were significant predictors of prolonged length of stay (odds ratio >1.6): age ≥75 years, Barthel index score ≤6, fraction of inspired oxygen ≥35%, Japan Coma Scale score of 100-300, anemia, muscle wasting and atrophy, bedsores, dysphasia, and methicillin-resistant Staphylococcus aureus infection. Our validation models had a c-statistic of 0.78 (95% confidence interval, 0.77-0.79) and a calibration slope of 0.98.

CONCLUSIONS

Our prediction models may help policymakers in developing strategies for the optimal management of community-acquired pneumonia patients with a focus on patients at a high risk of prolonged length of stay.

摘要

背景

社区获得性肺炎患者的住院时间与医疗费用密切相关,而在老龄化社会中,医疗费用负担正在增加。在此,我们开发并验证了用于预测社区获得性肺炎患者住院时间延长的模型,以支持这些患者的高效护理。

方法

我们从日本 304 家急性护理医院获得了 2012 年至 2013 年期间因肺炎出院的 32916 名患者的数据。使用逻辑回归模型,将延长的住院时间作为结果,将患者特征作为预测因子。使用 bootstrap 对内模型进行内部验证,并使用 2014 年出院的肺炎患者对外模型进行验证。

结果

中位住院时间为 11 天(四分位间距,8-17 天)。以下是延长住院时间的显著预测因子(优势比>1.6):年龄≥75 岁、巴氏指数评分≤6、吸入氧分数≥35%、日本昏迷量表评分为 100-300、贫血、肌肉减少和萎缩、褥疮、构音障碍和耐甲氧西林金黄色葡萄球菌感染。我们的验证模型的 C 统计量为 0.78(95%置信区间,0.77-0.79),校准斜率为 0.98。

结论

我们的预测模型可以帮助决策者制定策略,以优化管理社区获得性肺炎患者,重点关注住院时间延长风险较高的患者。

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