Photo Credit: YakobchukOlena

The following is a summary of “Development of a prediction model for in-hospital mortality in immunocompromised chronic kidney diseases patients with severe infection,” published in the February 2025 issue of BMC Nephrology by Wang et al. 

Researchers conducted a retrospective study to identify risk factors for in-hospital mortality in immunocompromised patients suffering from chronic kidney diseases (CKD) with severe infections. 

They conducted a retrospective analysis of clinical data from 272 patients with CKD who received immunosuppressive agents and presented severe infections, with 73 experiencing mortalities during hospitalization. Logistic regression was applied to the training set to identify key feature variables and construct a predictive model for in-hospital mortality. A nomogram was created to visually represent the predictive model for clinical application. 

The results showed that ventilator use, vasoactive drug administration, elevated lactate dehydrogenase (LDH), total bilirubin (TBIL) levels, and persistent lymphopenia (PL) are effective predictors of in-hospital mortality in immunocompromised patients with severe infections. The predictive model demonstrated excellent discriminative ability (AUC = 0.959, 95% CI 0.924–0.994), outperforming the Sequential Organ Failure Assessment (SOFA) score (AUC = 0.878, 95% CI 0.825–0.930) and quick Pitt Bacteremia Score (qPBS) (AUC = 0.897, 95% CI 0.846–0.947). Calibration curve analysis and the Hosmer-Lemeshow (HL) test confirmed model concordance, while decision curve analysis (DCA) highlighted its superior clinical utility compared to the SOFA and qPBS scores. PL was identified as the most important predictor of in-hospital mortality. 

Investigators identified PL as the most significant predictor of in-hospital mortality in immunocompromised patients with CKD. The clinical prediction model incorporating PL demonstrated strong diagnostic accuracy and clinical utility. 

Source: bmcnephrol.biomedcentral.com/articles/10.1186/s12882-025-04002-9#Abs1