The optimal timing of pharmacologic venous thromboembolism (VTE) prophylaxis after traumatic brain injury (TBI) remains one of the most challenging questions in trauma care. Clinicians must balance the risk of intracranial hemorrhage progression against VTE-related morbidity and mortality. Although guidelines have attempted to standardize care,1 2 considerable variability persists across trauma centers. Recent evidence suggests that this balance may be less uncertain than traditionally believed. A systematic review found no significant difference in hemorrhage progression between early and delayed chemoprophylaxis, while prospective multicenter data demonstrated that prophylaxis initiated within 48 hours reduced VTE without increasing hemorrhagic progression.3 4
Conversely, the consequences of delay are well documented. In one study, patients with TBI had longer delays prior to the initiation of enoxaparin (7.5 days vs 1.5 days), were more likely to receive unfractionated heparin prior to enoxaparin (46.3% vs 11.5%) and had much higher VTE rates, at 22%.5 A dedicated textbook on VTE management in TBI patients addresses these challenges, offering guidance on optimal timing, dosing, and societal guidelines.6
Against this backdrop, Rhodes-Lyons and colleagues present the early VTE prophylaxis in TBI (EViTBI) algorithm, a risk-stratification tool derived from more than 58 000 isolated TBI patients in the American College of Surgeons Trauma Quality Improvement Program (ACS-TQIP) database.7 The investigators developed an interpretable bedside score that incorporates injury characteristics, physiologic variables, and comorbidities to classify patients into low-risk, moderate-risk, and high-risk groups, with progressively increasing mortality and thromboembolic events. Their decision to prioritize an explainable model over more complex machine-learning approaches enhances clinical usability and implementation.
Nevertheless, EViTBI should be viewed as an important step rather than a practice-changing solution. Its retrospective design, modest discrimination (Area Under the Curve 0.68), and reliance on all-cause in-hospital mortality as a validation endpoint limit its ability to predict hemorrhagic progression. Although intended as a decision-support tool rather than a replacement for neurosurgical assessment, EViTBI remains fundamentally a static, admission-time model applied to a decision that evolves according to serial neurological examinations and repeat neuroimaging.1 2 The exclusion of patients who never received chemoprophylaxis further limits its generalizability.
Despite these limitations, EViTBI represents meaningful progress toward objective, data-driven decision support. Importantly, EViTBI moves beyond purely neuroanatomic classification by incorporating systemic physiology and comorbidities, acknowledging that the decision to initiate anticoagulation is rarely determined by head CT findings alone. Prospective validation will determine whether individualized risk assessment can safely facilitate earlier and more effective VTE prophylaxis in patients with brain trauma.
