Development and validation of risk prediction model for carbapenem-resistant <italic style="font-style: italic">Klebsiella pneumoniae</italic> infection

MO Yinzhu; CHENG Xianxiong; SONG Cangsang; LYU Shijie; REN Baojun; LI Zhiwei; BAO Jinying; YANG Huanzhi

doi:10.6039/j.issn.1001-0408.2025.14.17

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Development and validation of risk prediction model for carbapenem-resistant Klebsiella pneumoniae infection

更新时间：2025-09-24

- Development and validation of risk prediction model for carbapenem-resistant Klebsiella pneumoniae infection
- ZHONGGUO YAOFANG Vol. 36, Issue 14, Pages: 1786-1791(2025)
- 作者机构：
  
  1.昆明市第一人民医院药学部，昆明　650034
  2.昆明医科大学附属甘美医院药学部，昆明　650034
  3.昆明市第一人民医院检验科，昆明　650034
  4.昆明市第一人民医院重症医学科，昆明　650034
- 作者简介：
- 基金信息：
- DOI：10.6039/j.issn.1001-0408.2025.14.17
  CLC： R978.1
- Received：26 February 2025，
  
  Revised：2025-06-20，
  
  Accepted：20 June 2025，
  
  Published：30 July 2025
- 稿件说明：
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莫银竹,程贤雄,宋沧桑,等.耐碳青霉烯类肺炎克雷伯菌感染风险预测模型的构建及验证[J].中国药房,2025,36(14):1786-1791.

MO Yinzhu,CHENG Xianxiong,SONG Cangsang,et al.Development and validation of risk prediction model for carbapenem-resistant Klebsiella pneumoniae infection[J].ZHONGGUO YAOFANG,2025,36(14):1786-1791.
莫银竹,程贤雄,宋沧桑,等.耐碳青霉烯类肺炎克雷伯菌感染风险预测模型的构建及验证[J].中国药房,2025,36(14):1786-1791. DOI： 10.6039/j.issn.1001-0408.2025.14.17.

MO Yinzhu,CHENG Xianxiong,SONG Cangsang,et al.Development and validation of risk prediction model for carbapenem-resistant Klebsiella pneumoniae infection[J].ZHONGGUO YAOFANG,2025,36(14):1786-1791. DOI： 10.6039/j.issn.1001-0408.2025.14.17.

摘要

目的

探讨耐碳青霉烯类肺炎克雷伯菌（CRKP）感染的独立危险因素，构建列线图预测模型并进行验证。

方法

收集昆明市第一人民医院2020年4月至2023年5月住院并感染CRKP的患者资料，按1∶1比例同期收集住院并感染碳青霉烯敏感肺炎克雷伯菌（CSKP）患者资料，作为建模组。另按相同标准收集2023年6月至2024年6月住院并感染CRKP及匹配CSKP的患者资料，作为验证组。采用单因素、LASSO回归及多因素Logistic回归分析确定CRKP感染的独立危险因素，并构建列线图预测模型；采用Bootstrap重抽样法对预测模型进行内部验证，使用验证组数据对模型进行外部验证，并通过受试者工作特征（ROC）曲线及校准曲线评估模型的预测性能。

结果

共纳入530例患者，其中建模组372例，验证组158例。脑血管疾病、留置胃管、机械通气、碳青霉烯类抗生素暴露以及

-内酰胺酶抑制剂复方制剂暴露经分析确定为CRKP感染的独立危险因素（

＜0.05）。CRKP感染风险列线图预测模型的内部和外部验证的ROC曲线下面积分别为0.729、0.803；校准曲线的预测概率与实际概率的一致性较高。

结论

脑血管疾病、留置胃管、机械通气、碳青霉烯类抗生素暴露以及

-内酰胺酶抑制剂复方制剂暴露是CRKP感染的独立危险因素；所构建的CRKP感染风险列线图预测模型具有良好的预测效能，能早期识别CRKP感染高风险患者。

Abstract

OBJECTIVE

To investigate the

independent risk factors for carbapenem-resistant

Klebsiella pneumoniae

（CRKP） infection， develop a nomogram prediction model and validate it.

METHODS

Clinical data of hospitalized patients infected with CRKP between April 2020 and May 2023 at Kunming First People’s Hospital were retrospectively collected and matched 1∶1 with patients infected with carbapenem-susceptible

Klebsiella pneumoniae

（CSKP） during the same period as the modeling group. Using the same criteria， data from patients hospitalized and infected with CRKP and matched CSKP between June 2023 and June 2024 were collected as the validation group. Univariate analysis， LASSO regression and multivariate Logistic regression were conducted to identify independent risk factors for CRKP infection and to develop a nomogram prediction model. Internal validation of the model was performed using Bootstrap resampling， and external validation was carried out using the data of validation group. The predictive performance of the model was evaluated using receiver operating characteristic （ROC） curves and calibration plots.

RESULTS

A total of 530 patients were enrolled， with 372 in the modeling group and 158 in the validation group. Cerebrovascular disease， indwelling gastric tube， mechanical ventilation， exposure to carbapenem antibiotics， and exposure to

-lactamase inhibitor compound agents were identified as independent risk factors for CRKP infection （

＜0.05）. The nomogram predicting CRKP infection risk achieved an area under ROC of 0.729 and 0.803 in internal and external validations， respectively. Calibration curves indicated a high degree of consistency between predicted and observed probabilities.

CONCLUSIONS

Cerebrovascular disease， indwelling gastric tube， mechanical ventilation， exposure to carbapenem antibiotics， and exposure to

-lactamase inhibitor compound agent are independ

ent risk factors for CRKP infection. The developed nomogram model for predicting CRKP infection risk demonstrates good predictive performance and can aid in the early identification of patients at high risk for CRKP infection.

关键词

Keywords

references

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Development and validation of risk prediction model for carbapenem-resistant Klebsiella pneumoniae infection

DOI：10.6039/j.issn.1001-0408.2025.14.17

摘要

Abstract

关键词

Keywords

references