Predicting Dural Tear in Compound Depressed Skull Fractures: A Prospective Multicenter Correlational Study

Area of Science:

• Neurosurgery
• Trauma Surgery
• Radiology

Background:

• Compound depressed skull fractures (DSF) represent a critical neurosurgical emergency.
• Accurate preoperative assessment of dural status is vital for effective treatment planning.
• Identifying predictors of dural tear is essential for managing these complex injuries.

Purpose of the Study:

• To identify clinical and imaging predictors of dural tear in patients with compound DSF.
• To develop a predictive model for dural tear probability.
• To aid treatment decision-making, especially in resource-limited settings.

Main Methods:

• Prospective, multicenter correlational study involving 128 patients with compound DSF.
• Evaluation of clinical, imaging, and intraoperative findings.
• Univariate, multivariate, and logistic regression analyses, with ROC curve validation.

Main Results:

• Dural tear occurred in 55.5% of patients.
• Significant predictors of dural tear included fracture depression depth (OR 1.3), pneumocephalus (OR 2.8), and brain contusions/hematoma (OR 5.5).
• A logistic regression model achieved 93.0% sensitivity and 43.9% specificity at a 30% cutoff for predicting dural tear.

Conclusions:

• Preoperative factors can reliably predict dural tear in compound DSF with high sensitivity (93.0%).
• This predictive capability can guide surgical intervention, balancing risks and benefits.
• The findings are particularly relevant for resource-limited environments requiring optimized treatment strategies.