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Erschienen in:

04.03.2024 | Nephrology - Original Paper

Predicting the risk of pulmonary infection in patients with chronic kidney failure: A-C2GH2S risk score—a retrospective study

verfasst von: Wenqian Deng, Chen Liu, Qianhui Cheng, Jingwen Yang, Wenwen Chen, Yao Huang, Yu Hu, Jiangan Guan, Jie Weng, Zhiyi Wang, Chan Chen

Erschienen in: International Urology and Nephrology | Ausgabe 7/2024

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Abstract

Purpose

The objective of this study is to investigate the associated risk factors of pulmonary infection in individuals diagnosed with chronic kidney disease (CKD). The primary goal is to develop a predictive model that can anticipate the likelihood of pulmonary infection during hospitalization among CKD patients.

Methods

This retrospective cohort study was conducted at two prominent tertiary teaching hospitals. Three distinct models were formulated employing three different approaches: (1) the statistics-driven model, (2) the clinical knowledge-driven model, and (3) the decision tree model. The simplest and most efficient model was obtained by comparing their predictive power, stability, and practicability.

Results

This study involved a total of 971 patients, with 388 individuals comprising the modeling group and 583 individuals comprising the validation group. Three different models, namely Models A, B, and C, were utilized, resulting in the identification of seven, four, and eleven predictors, respectively. Ultimately, a statistical knowledge-driven model was selected, which exhibited a C-statistic of 0.891 (0.855–0.927) and a Brier score of 0.012. Furthermore, the Hosmer–Lemeshow test indicated that the model demonstrated good calibration. Additionally, Model A displayed a satisfactory C-statistic of 0.883 (0.856–0.911) during external validation. The statistical-driven model, known as the A-C2GH2S risk score (which incorporates factors such as albumin, C2 [previous COPD history, blood calcium], random venous blood glucose, H2 [hemoglobin, high-density lipoprotein], and smoking), was utilized to determine the risk score for the incidence rate of lung infection in patients with CKD. The findings revealed a gradual increase in the occurrence of pulmonary infections, ranging from 1.84% for individuals with an A-C2GH2S Risk Score ≤ 6, to 93.96% for those with an A-C2GH2S Risk Score ≥ 18.5.

Conclusion

A predictive model comprising seven predictors was developed to forecast pulmonary infection in patients with CKD. This model is characterized by its simplicity, practicality, and it also has good specificity and sensitivity after verification.
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Metadaten
Titel
Predicting the risk of pulmonary infection in patients with chronic kidney failure: A-C2GH2S risk score—a retrospective study
verfasst von
Wenqian Deng
Chen Liu
Qianhui Cheng
Jingwen Yang
Wenwen Chen
Yao Huang
Yu Hu
Jiangan Guan
Jie Weng
Zhiyi Wang
Chan Chen
Publikationsdatum
04.03.2024
Verlag
Springer Netherlands
Erschienen in
International Urology and Nephrology / Ausgabe 7/2024
Print ISSN: 0301-1623
Elektronische ISSN: 1573-2584
DOI
https://doi.org/10.1007/s11255-024-03953-6

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