A prediction model to predict the prognosis of elderly patients with community-acquired pneumonia-associated sepsis
10.3760/cma.j.issn.1671-0282.2024.08.012
- VernacularTitle:老年社区获得性肺炎相关脓毒症患者预后的预测模型
- Author:
Yanru FANG
1
;
Xingyi WANG
;
Tao ZHAO
;
Cong WANG
;
Lishan YANG
Author Information
1. 宁夏医科大学总医院急诊科,银川 750000
- Keywords:
Old age;
CAP;
Sepsis;
Nomogram;
Predictive models
- From:
Chinese Journal of Emergency Medicine
2024;33(8):1151-1156
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To explore the prognostic factors of elderly patients with community-acquired pneumonia-related sepsis and to construct a prediction model.Methods:The clinical data of elderly patients with community-acquired pneumonia-associated sepsis from October 2020 to October 2022 in the General Hospital of Ningxia Medical University from October 2020 to October 2022 were retrospectively included, and the clinical data of the two groups were divided into the modeling population and the validation population in the ratio of 7:3 by random number table method, and the clinical data of the two groups were compared. According to the 30-day outcomes of admission, the patients were divided into survival group and death group, and the independent risk factors for the prognosis of elderly patients with community-acquired pneumonia-related sepsis were screened out by LASSO regression and multivariate logistic regression analysis, and the nomogram prediction model was constructed by R software. The area under the curve (AUC), calibration curve and decision curve of the receiver operating characteristic curve were used to validate the nomogram prediction model in the modeling population and the validation population to judge its discrimination, calibration and clinical practicability.Results:A total of 472 patients were included, with 331 and 141 models and validations, respectively, indicating that the clinical data were comparable between the modeled and validated populations. LASSO regression and multivariate logistic regression analysis showed that pneumonia severity index (PSI) score and sequential organ failure assessment (SOFA) score were independent risk factors for the prognosis of elderly patients with community-acquired pneumonia-associated sepsis. The AUC of the modeled population prediction model was 0.984 (95% CI: 0.975-0.994), and the AUC of the validated population prediction model was 0.961 (95% CI: 0.926-0.996). The nomogram prediction model has good discrimination, calibration and clinical practicability in both the modeled and validated populations. Conclusions:The nomogram prediction model established in the study has high accuracy for early identification and risk of sepsis in elderly patients with CAP and can guide for clinicians to formulate personalized interventions.
