Risk factors of recurrence in chronic subdural hematoma and a proposed extended classification of internal architecture as a predictor of recurrence

Abstract

Chronic subdural hematomas (cSDHs) constitute one of the most prevalent intracranial disease entities requiring surgical treatment. Although mostly taking a benign course, recurrence after treatment is common and associated with additional morbidity and costs. Aim of this study was to develop hematoma-specific characteristics associated with risk of recurrence. All consecutive patients treated for cSDH in a single university hospital between 2015 and 2019 were retrospectively considered for inclusion. Size, volume, and midline shift were noted alongside relevant patient-specific factors. We applied an extended morphological classification system based on internal architecture in CT imaging consisting of eight hematoma subtypes. A logistic regression model was used to assess the classification’s performance on predicting hematoma recurrence. Recurrence was observed in 122 (32.0%) of 381 included patients. Apart from postoperative depressed brain volume (OR 1.005; 95% CI 1.000 to 1.010; p = 0.048), neither demographic nor factors related to patient comorbidity affected recurrence. The extended hematoma classification was identified as a significant predictor of recurrence (OR 1.518; 95% CI 1.275 to 1.808; p < 0.001). The highest recurrence rates were observed in hematomas of the homogenous (isodense: 41.4%; hypodense: 45.0%) and sedimented (50.0%) types. Our results support that internal architecture subtypes might represent stages in the natural history of chronic subdural hematoma. Detection and treatment at a later stage of spontaneous repair can result in a reduced risk of recurrence. Based on their high risk of recurrence, we advocate follow-up after treatment of sedimented and homogenous hematomas.

Seizure after surgical treatment of chronic subdural hematoma—Associated factors and effect on outcome

“…Hematoma volume was excluded based on collinearity with hematoma width. The logistic regression model was statistically significant χ 2 ( 6 ) = 16.129, p = 0.013. The model explained 13.2% (Nagelkerke R 2 ) of the variance in seizure occurrence and correctly classified 81.2% of cases.…”

“…All patients who were surgically treated for chronic subdural hematoma in a single tertiary care center between 2015 and 2019, were considered for inclusion. This study constitutes a subgroup analysis of previously published data ( 6 ). In the latter study, the influence of hematoma architecture on recurrence rates was assessed.…”

“…Our cSDH treatment algorithm has been previously described in detail ( 6 ). In summary, indication for the surgical evacuation of cSDH was based on the presence of neurological deficits, i.e., paresis, gait disturbance, or speech disorder.…”

“…The presence of midline shift and its extension (mm) was noted. Two independent assessors (HH and MV), blinded to the outcome, classified each hematoma according to its structural appearance in CT imaging into one of eight subtypes, as described previously ( 6 ). All eight hematoma subtypes are depicted in Figure 1 .…”

“…Fibroproliferation results in the membranization of the hematoma and the development of septa within. This most likely reflects an attempt toward natural repair and developmental stages in internal hematoma architecture have proved predictive of hematoma recurrence after treatment ( 5 , 6 ).…”