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Clinical characteristics and risk factor analysis of Pneumocystis jirovecii pneumonia in patients with CKD: a machine learning–based approach

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Abstract

Patients with chronic kidney disease (CKD) who are being treated with immunosuppressive medications are at risk for developing Pneumocystis jirovecii pneumonia (PCP). We attempted to characterize the clinical aspects of PCP in CKD patients in order to alert high-risk patients with bad prognosis. A retrospective study of CKD patients was conducted from June 2018 to June 2022. Based on PCP diagnostic criteria, these patients were divided into PCP and non-PCP groups. Using univariate and multivariate logistic regression analysis, risk indicators were evaluated, and nomogram and decision tree were developed. Of the CKD patients screened for Pneumocystis carinii nucleic acid, 1512 were included. Two-hundred forty four (16.14%) were diagnosed with PCP. Of the PCP, 88.5% was receiving glucocorticoid (GC) therapy, of which 66.3% received more than 0.5 mg/kg GC. Multivariate analysis showed that membranous nephropathy (OR 2.35, 95% CI 1.45–3.80), immunosuppressive therapy (OR 1.94, 95% CI 1.06–3.69), and ground glass opacity of CT scanning (OR 1.71, 95% CI 1.10–2.65) were associated with increased risk of Pneumocystis carinii infection. The AUC of nomogram based on logistics regression was 0.78 (0.75–0.81). The mortality in patients with PCP was 32.40%. Univariate analysis and decision tree showed that pulmonary insufficiency (PO2: OR 0.98, 95% CI 0.96–1.00), elevated APTT (OR 1.07, 95% CI 1.04–1.11), and reduced hemoglobin (OR 0.97, 95% CI 0.96–0.98) were associated with poor prognosis. PCP is not rare in CKD patients, particularly in those treated with immunosuppressive therapy. Considering the high mortality of the cases, further studies on the prevention and management of these patients are needed.

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Funding

This work was financially supported by project supported by the National Natural Science Foundation of China (Grant Nos. 82170702, 82230021, 81602104, 82100730, 82200771), Major Research Plan of the National Natural Science Foundation of China (Grant No. 91742204), and National Key R&D Program of China (Grant No. 2021YFC2500200).

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  1. Shu-Wang Ge and Gang Xu contributed equally to this work.

Authors and Affiliations

  1. Division of Internal Medicine, Department of Nephrology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, No. 1095 Jiefang Road, Wuhan, 430030, China

    Xiao-Yu Cai, Yi-Chun Cheng, Shu-Wang Ge & Gang Xu

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Contributions

X. Y. C. designed the study, conducted the statistical analyses, and wrote the paper; Y. C. C. contributed to data interpretation and the critical review of the manuscript; S. W. G. and G. X. designed the study, supervised the study process, and contributed to data interpretation and the critical review of the manuscript; and all authors read and approved the final manuscript.

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Correspondence to Shu-Wang Ge or Gang Xu.

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The study was approved by the Institutional Ethics Committee of Tongji Hospital. Informed patient consent was waived since the data set of this research consisted of de-identified secondary data.

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Cai, XY., Cheng, YC., Ge, SW. et al. Clinical characteristics and risk factor analysis of Pneumocystis jirovecii pneumonia in patients with CKD: a machine learning–based approach. Eur J Clin Microbiol Infect Dis 42, 323–338 (2023). https://doi.org/10.1007/s10096-023-04555-3

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