Volume 21 Issue 11
Nov.  2023
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Article Navigation >  Chinese Journal of General Practice  > 2023  >  21(11): 1860-1864
ZHAO Shiqi, WANG Shu, ZHANG Ying, WANG Shasha, LI Jing, TANG Wenjuan, LI Jing, ZHANG Xuemin, LI Fang. Establishment and validation of model for the risk of Carbapenem-Resistant Enterobacteriaceae infection in elderly patients with pulmonary infection[J]. Chinese Journal of General Practice, 2023, 21(11): 1860-1864. doi: 10.16766/j.cnki.issn.1674-4152.003243
Citation: ZHAO Shiqi, WANG Shu, ZHANG Ying, WANG Shasha, LI Jing, TANG Wenjuan, LI Jing, ZHANG Xuemin, LI Fang. Establishment and validation of model for the risk of Carbapenem-Resistant Enterobacteriaceae infection in elderly patients with pulmonary infection[J]. Chinese Journal of General Practice, 2023, 21(11): 1860-1864. doi: 10.16766/j.cnki.issn.1674-4152.003243
shu

Establishment and validation of model for the risk of Carbapenem-Resistant Enterobacteriaceae infection in elderly patients with pulmonary infection

doi: 10.16766/j.cnki.issn.1674-4152.003243
  • 1.

    Cadre Ward, the Third Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230000, China

Funds:

 Hwk2022zd003

 2022AH052334

  • Received Date: 2023-07-19
    Available Online: 2024-01-13
    Abstract
  •   Objective  To analyze and screen the high-risk factors for CRE infection in elderly people with pulmonary infection, and to construction and validate a risk nomogram prediction model.  Methods  Clinical data of a total of 894 elderly (≥60 years old) hospitalized patients with pulmonary infection cultured by Enterobacteriaceae bacteria in Anhui Province were retrospectively collected. Two hospitals were selected as verification group (250 cases), and the rest were used as training group(644 cases). Univariate Lasso regression and multivariate logistic regression analysis were used to analyze the modeling group data to identify independent risk factors for CRE infection. Construct a Nomogram prediction model and verify the model in multiple centers.  Results  The independent risk factors of CRE infection in the elderly were endotracheal intubation≥72 h, long-term bed rest, ≥2 types of antibiotics, cerebrovascular disease and malnutrition. Based on the above five independent risk factors, a Nomogram model for predicting risk was established, and the AUC values of the training group and verification group were 0.862 and 0.858. The Hosmer-Lemeshow test shows that the training group P=0.761 and the verification group P=0.339. Decision curve analysis shows that the model has good benefit within large thresholds.  Conclusion  The construction of a risk prediction model for the risk of CRE infection in the lungs of elderly people have some clinical significance, allowing early individualized intervention according to controllable factors.

     

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