BACKGROUND:The optimal enoxaparin dosing strategy to achieve venous thromboembolism (VTE) prophylaxis in trauma patients remains unclear.Current dosing guidelines often include weight, age, and renal function but still fail to achieve appropriate prophylactic anti-Xa levels in many patients. We hypothesized that additional patient factors influence anti-Xa response to enoxaparin in trauma patients.
METHODS:This is a retrospective review of patients admitted to a Level 1 trauma center for ≥4 days from July 2015 to September 2020, who received enoxaparin VTE prophylaxis per protocol (50-59 kg, 30 mg/dose; 60-99 kg, 40 mg/dose; ≥100 kg, 50 mg/dose; all doses every 12 hours) and had an appropriately timed peak anti-Xa level. Multivariate regression was performed to identify independent predictors of prophylactic anti-Xa levels (0.2-0.4 IU/mL) upon first measurement.
RESULTS:The cohort (N = 1,435) was 76.4% male, with a mean ± SD age of 49.9 ± 20.0 years and a mean ± SD weight of 82.5 ± 20.2 kg (males, 85.2 kg; females, 73.7 kg; p <0.001). Overall, 68.6% of patients (n = 984) had a prophylactic anti-Xa level on first assessment (69.6% of males, 65.1% of females). Males were more likely to have a subprophylactic level than females (22.1% vs. 8.0%, p <0.001), whereas females were more likely to have supraprophylactic levels than males (26.9% vs. 8.3%, p < 0.001). When controlling for creatinine clearance, anti-Xa level was independently associated with dose-to-weight ratio (odds ratio, 0.191 for 0.5 mg/kg; p < 0.001; confidence interval, 0.151-0.230) and female sex (odds ratio, 0.060; p < 0.001; confidence interval, 0.047-0.072). Weight and age were not significant when controlling for the other factors.
CONCLUSION:Male patients have a decreased anti-Xa response to enoxaparin when compared with female patients, leading to a greater incidence of subprophylactic anti-Xa levels in male patients at all dose-to-weight ratios. To improve the accuracy of VTE chemoprophylaxis, sex should be considered as a variable in enoxaparin dosing models.