Admission serum myoglobin and the development of acute kidney injury after major trauma

Background Myoglobin and creatine kinase (CK) are both established markers of muscle injury but their hospital admission values have never been compared to predict post-traumatic acute kidney injury (AKI). Methods An observational registry study of consecutive trauma patients admitted to a major regional trauma centre. The primary outcome was stage 1 or more AKI in the first 7 days after trauma. We assessed the association of hospital admission myoglobin or CK with development of AKI both alone and when added to two existing risk prediction models for post traumatic AKI. Results Of the 857 trauma patients (median age 36 [25-52], 96% blunt trauma, median ISS of 20 [12-47]) included, 102 (12%) developed AKI. Admission myoglobin performed better than CK to predict AKI any stage with an AUC-ROC of 0.74 (95% CI 0.68-0.79) and 0.63 (95% CI 0.57-0.69), respectively (p < 0.001). Admission myoglobin also performed better than CK to predict AKI stage 2 or 3 [AUC-ROC of 0.79 (95% CI 0.74-0.84) and 0.74 (95% CI 0.69-0.79), respectively (p < 0.001)] with a best cutoff value of 1217 mu g/L (sensitivity 74%, specificity 77%). Admission myoglobin added predictive value to two established models of AKI prediction and showed significant ability to reclassify subjects regarding AKI status, while admission CK did not. Decision curve analysis also revealed that myoglobin added net benefit to established predictive models. Admission myoglobin was better than CK at predicting development of significant rhabdomyolysis. Conclusions Admission myoglobin better predicts the development of AKI and severe rhabdomyolysis after major trauma. Admission myoglobin should be added in established predictive models of post-traumatic AKI to early identify high-risk patients.

Automated summary

This study demonstrates that in trauma patients, admission myoglobin performs better than CK in predicting AKI, and myoglobin adds predictive value to established models of AKI prediction.