ArticleBMC infectious diseases2026
A nomogram for predicting 30-day mortality in patients with carbapenem-resistant Klebsiella pneumoniae infection: a retrospective cohort study.
Article in BMC infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundCarbapenem-resistant Klebsiella pneumoniae (CRKP) has emerged as a significant global health threat due to its high virulence. This study aims to analyze the risk factors of 30-day mortality in patients with CRKP infection and to construct a nomogram model for predicting 30-day mortality risk, offering valuable insights for clinical decision-making.
methodsThis study retrospectively enrolled 290 patients with CRKP infection from January 2022 to December 2025 at the Public Health Clinical Center Affiliated to Shandong University. Patients were categorized into the survival (n = 230) and non-survival (n = 60) groups based on clinical outcomes at 30 days. Multivariate logistic analysis was conducted to identify independent risk factors. A nomogram model was developed using R software. The model's performance was evaluated using the area under the ROC curve (AUC), the Hosmer-Lemeshow test, and calibration plots. The clinical utility of the model was evaluated using decision curve analysis (DCA), while the bootstrap technique was applied for the model's internal validation.
resultsThe 30-day mortality rate was 20.7% in patients with CRKP infection. Septic shock (aOR 16.850, 95% CI 5.915-48.000, P < 0.001), Charlson Comorbidity Index (CCI) score (aOR 1.242, 95% CI 1.032-1.493, P = 0.022), and appropriate antibiotic therapy within 3 days of infection onset (aOR 0.200, 95% CI 0.074-0.542, P = 0.002) were identified as independent predictors of mortality. Compared with thrombocytopenia (< 100 × 10⁹/L), normal platelet count (aOR 0.046, 95% CI 0.014-0.151) and thrombocytosis (aOR 0.030, 95% CI 0.006-0.155) were independently protective (both P < 0.001). A nomogram incorporating these predictors demonstrated excellent discrimination (AUC 0.908, 95% CI 0.865-0.951) and adequate calibration (Hosmer-Lemeshow P = 0.989, Brier score = 0.092). The DCA curve demonstrated significant potential for clinical application. Internal validation was conducted using 1,000 bootstrap cycles. The model bias-corrected C-index was 0.903 (95% CI 0.835-0.966).
conclusionsThe study identified independent risk factors associated with the 30-day mortality of CRKP-infected patients. The nomogram model exhibited promising discriminatory capability and clinical applicability, providing an effective tool for early identification of at-risk patients.
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