Eur J Orthop Surg Traumatol. 2026 Jul 4;36(1):273. doi: 10.1007/s00590-026-04854-3.
ABSTRACT
PURPOSE: To evaluate whether incorporation of arterial injury into CT-based zone-of-injury (ZOI) models improves complication prediction after open tibial shaft fractures.
METHODS: A retrospective cohort study was conducted at an urban multicenter academic hospital (2012-2024). Patients ≥ 18 years with open OTA 42A-C tibia fractures, preoperative CT, and ≥ 6 months follow-up were included. Arterial injury and wound location within the anterior tibial, posterior tibial, or peroneal angiosomes were identified on CT angiography. Soft-tissue ZOI (longitudinal extent of soft-tissue air) and fracture ZOI (fracture span) were normalized to tibial length. The primary outcome was a composite complication of fracture-related infection, nonunion, or amputation. Logistic regression identified predictors, and ROC analysis compared discrimination of (1) an angiosome-augmented ZOI model, (2) a standard ZOI model, and (3) Gustilo-Anderson classification.
RESULTS: Eighty-two patients were included: 32 (39.0%) developed major complications. Arterial injury was present in 11 patients and significantly associated with complications (72.7% vs 33.8%, p = 0.020). The augmented ZOI model included arterial injury, anterior angiosome involvement, number of angiosomes affected, normalized soft-tissue ZOI, and BMI (AUROC 0.777), outperforming the standard ZOI model (AUROC 0.707) and Gustilo-Anderson classification (AUROC 0.592). DeLong testing showed no significant difference between ZOI and the augmented model.
CONCLUSION: The original CT-based ZOI model, which incorporates soft-tissue injury measurements normalized to tibial length and BMI, remains a robust objective predictor of complications following open tibial shaft fractures, consistent with prior published work. While arterial injury is associated with adverse outcomes, its addition to ZOI-based models does not significantly improve predictive performance. Notably, only the arterial-augmented ZOI model demonstrated a statistically significant improvement in discrimination over the Gustilo-Anderson classification, whereas the standard ZOI model did not reach significance in this cohort, suggesting that augmentation may be necessary to meaningfully surpass subjective wound grading.
LEVEL OF EVIDENCE: III.
PMID:42400670 | DOI:10.1007/s00590-026-04854-3
