开发和验证工具,用于预测非 HIV 感染肺炎患者的死亡和 ICU 入院风险。

Development and validation of tools for predicting the risk of death and ICU admission of non-HIV-infected patients with pneumonia.

机构信息

Department of Infectious Diseases, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Clinical Pharmacology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

出版信息

Front Public Health. 2022 Nov 8;10:972311. doi: 10.3389/fpubh.2022.972311. eCollection 2022.

Abstract

INTRODUCTION

The mortality rate of non-HIV-infected pneumonia (PCP) is high. This research aimed to develop and validate two clinical tools for predicting the risk of death and intensive care unit (ICU) admission in non-HIV-infected patients with PCP to reduce mortality.

METHODS

A retrospective study was conducted at Peking Union Medical College Hospital between 2012 and 2021. All proven and probable non-HIV-infected patients with PCP were included. The least absolute shrinkage and selection operator method and multivariable logistic regression analysis were used to select the high-risk prognostic parameters. In the validation, the receiver operating characteristic curve and concordance index were used to quantify the discrimination performance. Calibration curves were constructed to assess the predictive consistency compared with the actual observations. A likelihood ratio test was used to compare the tool and CURB-65 score.

RESULTS

In total, 508 patients were enrolled in the study. The tool for predicting death included eight factors: age, chronic lung disease, respiratory rate, blood urea nitrogen (BUN), lactate dehydrogenase (LDH), cytomegalovirus infection, shock, and invasive mechanical ventilation. The tool for predicting ICU admission composed of the following factors: respiratory rate, dyspnea, lung moist rales, LDH, BUN, C-reactive protein/albumin ratio, and pleural effusion. In external validation, the two clinical models performed well, showing good AUCs (0.915 and 0.880) and fit calibration plots. Compared with the CURB-65 score, our tool was more informative and had a higher predictive ability (AUC: 0.880 vs. 0.557) for predicting the risk of ICU admission.

CONCLUSION

In conclusion, we developed and validated tools to predict death and ICU admission risks of non-HIV patients with PCP. Based on the information from the tools, clinicians can tailor appropriate therapy plans and use appropriate monitoring levels for high-risk patients, eventually reducing the mortality of those with PCP.

摘要

简介

非 HIV 感染性肺炎(PCP)的死亡率很高。本研究旨在开发和验证两种临床工具,以预测非 HIV 感染性 PCP 患者死亡和入住重症监护病房(ICU)的风险,从而降低死亡率。

方法

本回顾性研究于 2012 年至 2021 年在北京协和医院进行。所有确诊和可能的非 HIV 感染性 PCP 患者均纳入研究。采用最小绝对收缩和选择算子法和多变量逻辑回归分析筛选高危预后参数。在验证中,采用受试者工作特征曲线和一致性指数来量化区分性能。构建校准曲线以评估与实际观察相比的预测一致性。采用似然比检验比较工具和 CURB-65 评分。

结果

本研究共纳入 508 例患者。预测死亡的工具包括 8 个因素:年龄、慢性肺部疾病、呼吸频率、血尿素氮(BUN)、乳酸脱氢酶(LDH)、巨细胞病毒感染、休克和有创机械通气。预测 ICU 入住的工具包括以下因素:呼吸频率、呼吸困难、肺部湿啰音、LDH、BUN、C 反应蛋白/白蛋白比值和胸腔积液。在外部验证中,这两个临床模型表现良好,具有良好的 AUC(0.915 和 0.880)和拟合校准图。与 CURB-65 评分相比,我们的工具更具信息性,预测 ICU 入住风险的能力更高(AUC:0.880 与 0.557)。

结论

总之,我们开发和验证了预测非 HIV 感染性 PCP 患者死亡和 ICU 入住风险的工具。基于工具提供的信息,临床医生可以为高危患者制定合适的治疗计划,并使用适当的监测水平,最终降低 PCP 患者的死亡率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3f53/9679649/4b6823c34c3d/fpubh-10-972311-g0001.jpg

相似文献

本文引用的文献

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索