AUTHOR=Jin Fan , Liang Hao , Chen Wen-can , Xie Jing , Wang Huan-ling 

TITLE=Development and validation of tools for predicting the risk of death and ICU admission of non-HIV-infected patients with Pneumocystis jirovecii pneumonia

JOURNAL=Frontiers in Public Health

VOLUME=Volume 10 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2022.972311

DOI=10.3389/fpubh.2022.972311

ISSN=2296-2565

ABSTRACT=Abstract
Introduction
The mortality of non-HIV-infected pneumocystis jirovecii pneumonia (PCP) is high. This research aimed to develop and validate two clinical tools for predicting the risks of death and intensive care unit (ICU) admission in non-HIV-infected PCP patients 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 PCP patients 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 measured to quantify the discrimination performance. Calibration curves were constructed to assess the predictive consistency 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 8 factors: age, chronic lung disease, respiratory rate, blood urea nitrogen (BUN), lactate dehydrogenase (LDH), cytomegalovirus infection, shock, and invasive mechanical ventilation. The predictive tool for ICU admission was composed of respiratory rate, dyspnoea, lung moist rales, LDH, BUN, C-reactive protein and albumin ratio and pleural effusion. In the external validation, the two clinical models performed well, which was supported by the good AUCs (0.915 and 0.880) and the 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.
Conclusions
In conclusion, we developed and validated predictive tools to evaluate the death and ICU admission risks of non-HIV PCP patients. Based on the information from the tools, clinicians can tailor proper therapy plans and choose appropriate monitoring levels for high-risk patients, eventually reducing the mortality of all PCP patients.