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May 6, 2026Biomedicines1 citationsOpen Access

Development and Validation of a Nomogram for Predicting Sepsis Risk in Patients with Non-Ventilator Hospital-Acquired Pneumonia

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HZHan ZhouZWZhenchao WuBLB H Liu

Key Points

  • To develop a nomogram for assessing sepsis risk in patients with non-ventilator hospital-acquired pneumonia.
  • Retrospective screening of 408 hospitalized patients with pneumonia
  • Division into training (n=260) and validation cohorts (n=108)
  • Multivariable logistic regression analysis to identify sepsis predictors
  • Constructed and validated a nomogram based on the predictors
  • Identified six predictors of sepsis: male sex, diabetes, coagulation dysfunction, lower PaO2/FiO2, lower platelet count, and higher bilirubin
  • Nomogram showed an apparent C-index of 0.809 in the training cohort
  • Validation cohorts had C-indices of 0.750 and 0.754, indicating acceptable performance

Abstract

Objective: To identify risk factors for progression to sepsis in patients with non-ventilator hospital-acquired pneumonia (NV-HAP) and to develop a practical nomogram for individualized risk assessment in this population. Methods: We retrospectively screened 408 hospitalized patients with hospital-acquired pneumonia at Peking University Third Hospital between January 2017 and December 2021. After excluding patients with an unclear diagnosis date or missing critical variables required for SOFA score calculation, 368 eligible patients with NV-HAP were included and randomly divided into a training cohort (n = 260) and an internal validation cohort (n = 108). An independent temporal validation cohort of 68 patients admitted between January 2022 and December 2022 at the same center was further used for temporal validation. Univariable and multivariable logistic regression analyses with backward stepwise selection were performed in the training cohort to identify predictors associated with progression to sepsis. A nomogram was then constructed based on the final model and evaluated by discrimination, calibration, and decision curve analysis. Results: A total of 368 patients were included in the model development dataset. The final multivariable model retained six predictors: male sex (OR = 2.393, 95% CI: 1.333–4.296), diabetes (OR = 2.205, 95% CI: 1.126–4.319), coagulation dysfunction (OR = 3.327, 95% CI: 1.726–6.413), PaO2/FiO2 (OR = 0.955 per 10-unit increase, 95% CI: 0.912–1.001), platelet count (OR = 0.900 per 10 × 109/L increase, 95% CI: 0.853–0.949), and bilirubin (OR = 1.176 per 1 μmol/L increase, 95% CI: 1.100–1.258). The nomogram showed acceptable performance, with an apparent C-index of 0.809 and a bootstrap-corrected C-index of 0.792 in the training cohort. The C-index was 0.750 (95% CI: 0.658–0.841) in the internal validation cohort and 0.754 (95% CI: 0.639–0.870) in the temporal validation cohort. Calibration analysis showed acceptable agreement between predicted and observed probabilities, and decision curve analysis indicated a positive net clinical benefit across clinically relevant threshold probabilities. Conclusions: In patients with NV-HAP, male sex, diabetes, coagulation dysfunction, lower PaO2/FiO2, lower platelet count, and higher bilirubin were associated with progression to sepsis. The developed nomogram showed acceptable discrimination, calibration, and clinical utility, and may serve as a practical tool for early individualized risk stratification in patients with NV-HAP.

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Cite This Study

Zhou et al. (2026) studied this question.

synapsesocial.com/papers/69fa983604f884e66b53214ahttps://doi.org/10.3390/biomedicines14050987
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