Nomogram Prediction Model for Risk Factors of Secondary Infection in Sepsis Patients

View Full Paper

Ask AI

Bookmark

Authors

Discussion

Observational analysis identified clinical factors influencing secondary infection in sepsis patients, suggesting a nomogram may help predict risks.

Reduced oxygen saturation correlates with an increased risk of secondary infection in sepsis patients, indicating a significant clinical finding.
Logistic regression analysis revealed critical factors, such as lymphocyte and platelet counts, affecting secondary infection risks in ICU admissions.
Utilized a nomogram tool for predicting secondary infection risks, integrating multiple clinical characteristics relevant to sepsis patients.
The findings support personalized treatment strategies in sepsis management, although external validation is necessary for broader application.

Lu et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark

Observational analysis identified clinical factors influencing secondary infection in sepsis patients, suggesting a nomogram may help predict risks.