Construction of a risk prediction model for secondary multiple organ dysfunction syndromein patients with severe pneumonia complicated by acute respiratory distress syndrome
GONG Ziyang
JIANG Zhuojuan
YU Hehua
YU Ke
LI Cuirong
Abstract：Objective To explore the risk factors for secondary multiple organ dysfunction syndrome(MODS)in patients with severe pneumonia complicated by acute respiratory distress syndrome(ARDS)and to construct a predictive model.Methods A total of 346 patients with severe pneumonia complicated by ARDS admitted to the Second Affiliated Hospital of Naval Medical University between January 2021 and December 2023 were enrolled,including 181 males and 165 females,aged(62.5±10.8)years old,ranging from 28 to 89 years old.According to the occurrence of MODS,the patients were divided into an occurrence group(n=52)and a non-occurrence group(n=294).Univariate analysis and multivariate Logistic regression analysis were used to screen for risk factors,and a prediction model was constructed accordingly.The area under the receiver operating characteristic curve(AUC)was used to evaluate the discrimination of the model,the Hosmer-Lemeshow test and calibration curves were used to assess calibration,and decision curve analysis(DCA)was used to evaluate clinical net benefit.To further validate the model's generalization ability,150 patients meeting the same inclusion and exclusion criteria from January to December 2024 were collected as an independent validation set for external validation.Results Multivariate logistic regression analysis revealed that advanced age,elevated levels of CRP,elevated procalcitonin,elevated blood lactate,and higher APACHE Ⅱ score were risk factors for secondary MODS(P<0.05).Based on these factors,the prediction model achieved an AUC of 0.874(95％CI:0.831 to 0.917)in the development set,with a sensitivity of 87.06％and a specificity of 83.74％.In the external validation set,the AUC was 0.852(95％CI:0.791 to 0.913),with a sensitivity of 84.62％and a specificity of 80.61％.The Hosmer-Lemeshow test indicated good calibration in both the development set(χ²=1.909,P=0.984)and the validation set(χ²=7.324,P=0.502).DCA demonstrated that the model provided high clinical net benefit across a wide range of threshold probabilities.Conclusion The model constructed based on logistic regression analysis has a high predictive value for secondary MODS in patients with severe pneumonia complicated by ARDS and can be used to predict the risk of secondary MODS in such patients.
Keywords：severe pneumoniaacute respiratory distress syndromemultiple organ dysfunction syndromerisk factorsprediction model
Publication Date：2026-01-25
Online Publishing Date：2026-03-03(First online date of this platform, not the publication date of the document)
Pages：7( 19-24,30 )