Nomogram for Predicting Central Nervous System Infection Following Traumatic Brain Injury in the Elderly

Area of Science:

• Neuroscience
• Infectious Diseases
• Geriatrics

Background:

• Central nervous system (CNS) infections pose a significant risk to elderly patients with traumatic brain injury (TBI).
• Identifying predictive factors for CNS infection in this vulnerable population is crucial for effective management.

Purpose of the Study:

• To identify risk factors for CNS infection in elderly TBI patients.
• To develop a predictive tool for assessing CNS infection risk in hospitalized elderly TBI patients.

Main Methods:

• Retrospective study of 742 elderly TBI patients.
• Logistic regression analysis to identify predictors.
• Development and validation of a nomogram predictive model.

Main Results:

• Surgical intervention, red blood cell count, C-reactive protein, and cerebrospinal fluid leakage were significant predictors of CNS infection.
• The predictive model demonstrated high accuracy (AUC-training=0.832, AUC-validation=0.824).

Conclusions:

• A nomogram effectively predicts CNS infection risk in elderly TBI patients.
• The predictive tool can facilitate timely interventions and improve patient outcomes.