Prognostic Value of Peripheral Blood Inflammatory Markers in Chronic Subdural Hematoma Patients Under 65 Years

Abstract Objectives and Background Chronic subdural hematoma (CSDH) is characterized by the develeopment of a membranous hematoma following mild to moderate head trauma, with its pathophysiology involving posttraumatic inflammatory processes. The aim of our study was to investigate the relationship between peripheral blood cell inflammatory markers and various clinical and radiological parameters in CSDH patients under 65 years. Methods We conducted a retrospective analysis of 53 patients diagnosed with unilateral CSDH who underwent surgical intervention with a closed drainage system via burrhole. We assessed peripheral blood inflammatory markers, radiological findings based on Nakaguchi classification, clinical status, length of hospital stay, intensive care unit (ICU) admission, and the need for reoperation. Results Prolonged stays exceeding 6 days was associated with postoperative complications. The majority (86.8%) of patients required ICU treatment, and 15.1% necessitated reoperation. Nakaguchi classification showed heterogeneous distribution, with no statistically significant association observed between classification and the need for reoperation. Preoperative, postoperative, and mean values of neutrophil-to-lymphocyte (N/L), platelet-to-lymphocyte (P/L), and monocyte-to-lymphocyte (M/L) ratios were not significant predictors of recurrence. However, a moderately significant negative correlation was found between the GCS score and preoperative M/L ratio ( p = 0.026), while a significant positive correlation was noted between the length of hospital stay and changes in N/L, P/L, and M/L ratios ( p = 0.001). Conclusion Inflammatory markers in peripheral blood cells exhibit potential as accessible indicators for monitoring CSDH prognosis and treatment duration. While Nakaguchi classification did not correlate with the need for reoperation, preoperative and postoperative inflammatory markers, alongside clinical parameters, could aid in predicting patient outcomes.