ArticleInternational orthopaedics2026
The early diagnostic value of emergency laboratory indicators in patients with acute compartment syndrome after tibiofibular fractures.
Article in International orthopaedics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
purposeAcute compartment syndrome (ACS) is a serious complication after tibiofibular fractures, which may cause muscle necrosis or even amputation due to challenges in making a prompt diagnosis. Therefore, this study tries to investigate its potential biomarkers from emergency blood tests.
methodsData on patients with tibiofibular fractures from January 2016 to January 2026 were gathered from three Level I trauma centres and categorized into ACS and non-ACS groups. Propensity score matching (PSM) analysis was used to reduce the impact of potential confounding variables. Then, univariate, logistic regression, and ROC curve analyses, as well as a nomogram prediction model, were performed to examine predictors of ACS.
resultsAfter PSM analysis, 260 patients were assigned to each group. Even though univariate analysis identified several indicators related to ACS, logistic regression analysis demonstrated that creatine kinase [CK, p < 0.001, OR = 1.003, 95% CI (1.002, 1.004)], creatine kinase myocardial band [CK-MB, p < 0.001, OR = 1.171, 95% CI (1.125, 1.219)], and C-reactive protein [CRP, p < 0.001, OR = 1.259, 95% CI (1.150, 1.377)] are predictors. Furthermore, ROC curve analysis identified 1219.5 U/L, 34.5 U/L, and 13.5 mg/L as the optimal cut-off values to diagnose ACS in patients with tibiofibular fractures. Our model predicts with an AUC of 0.8519 [95% CI (0.8184, 0.8813)], showing consistent calibration and effective clinical application as evidenced by decision curve analysis.
conclusionsThe levels of CK, CK-MB, and CRP were found to be potential biomarkers for ACS, with their optimal cut-off values identified. Our nomogram prediction model can accurately predict ACS in patients with tibiofibular fractures. We still need large sample data to validate these results.
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