Pilot Biomarker Analysis and Decision Tree Algorithm Modeling of Patients with Chronic Subdural Hematomas

Area of Science:

• Neurosurgery
• Inflammation Biology
• Biomarker Discovery

Background:

• Elderly individuals face high risks for chronic subdural hematoma (cSDH), a common neurosurgical condition.
• Surgical evacuation is a primary treatment, but recurrence rates remain significant.
• Identifying inflammatory markers could improve prediction of cSDH development and outcomes.

Purpose of the Study:

• To identify potential inflammatory biomarkers associated with the development and recurrence of chronic subdural hematoma (cSDH) in elderly patients.
• To evaluate the predictive power of these biomarkers for clinical parameters like midline shift and hematoma thickness.
• To assess the correlation of biomarkers with post-operative outcomes and recurrence rates.

Main Methods:

• Prospective enrollment of patients over 65 years with symptomatic cSDH requiring surgery.
• Analysis of cSDH fluid for inflammatory markers including CXCL9, IL-6, VEGF-A, IL-5, and RANTES.
• Correlation of biomarker concentrations with CT-measured cSDH thickness, midline shift (MLS), Glasgow Outcome Scale-Extended (GOS-E) scores, and recurrence, using a decision tree model.

Main Results:

• CXCL9 correlated with cSDH thickness; IL-6 and VEGF-A correlated with MLS.
• IL-5 concentrations were associated with better GOS-E scores, while RANTES correlated with complete cSDH resolution.
• Higher CXCL9 predicted MLS, higher IL-5 predicted cSDH thickness, and lower RANTES predicted recurrence (RR=2.2).

Conclusions:

• CXCL9, IL-6, VEGF, IL-5, and RANTES are implicated in cSDH recurrence.
• These markers show potential as predictive biomarkers for cSDH recurrence and neurological outcomes in the elderly.
• Further research is warranted to validate these findings and explore therapeutic targets.