Abstract Background Cranial neurosurgical procedures often result in significant blood loss, particularly in conditions such as brain tumors, traumatic brain injury (TBI), and hemorrhagic stroke. Accurate estimation of blood loss is crucial for fluid management and prevention of complications during surgery. Objectives To compare intraoperative blood loss measured using the adhesive gutter drape technique (AGDT) versus the conventional draping method across three cranial neurosurgical indications—brain tumors, TBI, and hemorrhagic stroke—and to develop predictive models for blood loss based on operative duration using AGDT-derived measurements. Methods This cross-sectional comparative study included 216 adult patients (72 with brain tumors, 72 with TBI, 72 with hemorrhagic stroke). Draping methods were assigned using a systematic alternating sequence. Intraoperative blood loss was calculated as net suction volume after subtracting irrigation fluid. Independent t-tests compared blood loss between draping techniques. Predictive modeling used simple linear regression for each diagnostic category based on AGDT-derived measurements. Results AGDT consistently yielded higher and more complete measurements of blood loss than the conventional method across all diagnoses (brain tumors: 2550.0 ± 743.9 mL vs. 1188.9 ± 678.1 mL; TBI: 788.9 ± 381.6 mL vs. 419.4 ± 216.2 mL; hemorrhagic stroke: 650.0 ± 209.1 mL vs. 370.8 ± 150.4 mL; all p < 0.0001). Operative duration was the strongest predictor of blood loss. Final regression models were: Brain tumors: EBL = 1036.6 + 269.7 × duration (hours) ( R² = 0.641), TBI: EBL = − 128.8 + 351.5 × duration (hours) ( R² = 0.413), Hemorrhagic stroke: EBL = − 61.5 + 284.6 × duration (hours) ( R² = 0.688). Conclusion AGDT captures a substantially greater measurable volume of intraoperative blood loss compared with conventional draping. Operative duration is a significant predictor of blood loss across three major neurosurgical conditions. The derived regression equations may aid clinicians in preoperative planning, transfusion management, and intraoperative decision-making.
Suroso et al. (Mon,) studied this question.