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需要轮椅或医用推车帮助才能抵达病房、动脉血氧合指数、年龄、白蛋白和中性粒细胞计数评分:预测中国慢性阻塞性肺疾病急性加重患者的住院死亡率。

The arrival ward requiring help by wheelchair or medical cart, arterial oxygenation index, age, albumin and neutrophil count score: Predicting in-hospital mortality in Chinese patients with acute exacerbations of chronic obstructive pulmonary disease.

机构信息

Department of Nephrology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China.

Department of Nephrology, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.

出版信息

Chron Respir Dis. 2023 Jan-Dec;20:14799731231197226. doi: 10.1177/14799731231197226.

Abstract

BACKGROUND

In this study, we will derive and validate a prognostic tool to predict in-hospital death based on Chinese acute exacerbation of chronic obstructive pulmonary disease (AECOPD) patients.

METHODS

Independent predictors of in-hospital death were identified by logistic regression analysis and incorporated into a clinical prediction tool.

RESULTS

The clinical prediction model was developed with data from 1121 patients and validated with data from 245 patients. The five predictors of in-hospital death from the development cohort (Arrival ward requiring help by wheelchair or medical cart, Arterial oxygenation index, Age, Albumin and Neutrophil count) were combined to form the AAAAN Score. The AAAAN Score achieved good discrimination (AUC = 0.85, 95% CI 0.81-0.89) and calibration (Hosmer-Lemeshow chi-square value was 3.33, = 0.65). The AAAAN Score, which underwent internal bootstrap validation, also showed excellent discrimination for mortality (AUC = 0.85, 95% CI 0.81 to 0.89) and performed more strongly than other clinical prediction tools. Patients were categorized into 3 risk groups based on the scores: low risk (0-2 points, 0.7% in-hospital mortality), intermediate risk (3-4 points, 4.1% in-hospital mortality), and high risk (5-7 points, 23.4% in-hospital mortality). Predictive performance was confirmed by external validation.

CONCLUSIONS

The AAAAN Score is a prognostic tool to predict in-hospital death in Chinese AECOPD patients.

摘要

背景

本研究旨在建立并验证一个基于中国慢性阻塞性肺疾病急性加重(AECOPD)患者的院内死亡预测工具。

方法

采用逻辑回归分析确定院内死亡的独立预测因素,并将其纳入临床预测工具。

结果

该临床预测模型基于 1121 例患者的数据进行开发,并在 245 例患者的数据中进行验证。来自开发队列的院内死亡的五个预测因素(到达病房需要轮椅或医疗车帮助、动脉血氧指数、年龄、白蛋白和中性粒细胞计数)被组合成 AAAAN 评分。AAAAN 评分具有良好的区分度(AUC=0.85,95%CI 0.81-0.89)和校准度(Hosmer-Lemeshow χ2 值为 3.33,=0.65)。经过内部自举验证,AAAAN 评分对死亡率也具有出色的区分能力(AUC=0.85,95%CI 0.81-0.89),表现优于其他临床预测工具。根据评分,患者被分为 3 个风险组:低危(0-2 分,院内死亡率为 0.7%)、中危(3-4 分,院内死亡率为 4.1%)和高危(5-7 分,院内死亡率为 23.4%)。外部验证证实了预测性能。

结论

AAAAN 评分是预测中国 AECOPD 患者院内死亡的一种预后工具。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8380/10448383/f570541f2f50/10.1177_14799731231197226-fig1.jpg

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