OBJECTIVE: Chronic subdural hematoma (CSDH) is a prevalent neurosurgical condition, particularly among the elderly. Hematoma volume (HV) and midline shift (MLS) on CT imaging are critical for assessing CSDH severity and recurrence risk. Brain atrophy has also been linked to recurrence. This study investigates the impact of HV and MLS on clinical symptoms and recurrence, considering brain atrophy. METHODS: A retrospective analysis was conducted on patients with unilateral CSDH who underwent burr hole surgery for symptoms such as headache, disturbances of consciousness, hemiparesis, and gait disturbance. HV, MLS, and relative cortical atrophy index (RCAI) were measured using preoperative (pre-) and postoperative (post-) CT images. The rate of change in RCAI (RCAI-CR) between pre- and post-CT images was calculated to assess contralateral brain compression. Associations between HV, MLS, RCAI, RCAI-CR, symptoms, and recurrence were analyzed. RESULTS: The study included 293 patients (mean age 79.4 ± 12.1 years), with a recurrence rate of 15.0 % (44/293). Pre-HV (per 10 mL) was significantly associated with hemiparesis and gait disturbance (odds ratio [OR] 1.12, 95 % confidence interval [CI] 1.03-1.21, p = 0.011
OR 1.14, 95 % CI 1.05-1.24, p = 0.003). Pre-MLS was significantly correlated with disturbances of consciousness (OR 1.26, 95 % CI 1.14-1.39, p <
0.001) and was elevated in patients with high RCAI-CR. Significant predictors of recurrence included Pre-HV (per 10 mL) (OR 1.16, 95 % CI 1.03-1.31, p = 0.014), postoperative subdural cavity volume (per 10 mL) (OR 1.18, 95 % CI 1.02-1.36, p = 0.026), antiplatelet drug use (OR 0.23, 95 % CI 0.06-0.89, p = 0.032), and CT classification (OR 2.35, 95 % CI 1.15-4.82, p = 0.020). CONCLUSIONS: HV and MLS have distinct clinical implications in CSDH. Pre-HV is linked to motor disturbances, while Pre-MLS correlates with disturbances of consciousness, with high RCAI-CR indicating significant brain compression. HV is a key predictor of recurrence, while MLS and RCAI are not. These findings may improve outcome prediction and management strategies.