Development and validation of a nomogram for predicting fasciotomy requirement in lower extremity arterial injuries: a retrospective case–control study
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Acute compartment syndrome (ACS) following lower extremity arterial injuries necessitates urgent fasciotomy to prevent limb loss, yet current diagnostic tools lack specificity for ischemia-reperfusion pathophysiology. Our study aimed to develop a nomogram combining biomarkers and clinical indicators to predict fasciotomy risk, enhancing early risk stratification and optimizing surgical decision-making. MATERIALS AND METHODS: In this retrospective case-control study (2010-2024), data were sourced from a tertiary hospital in China. A total of 146 patients with traumatic femoral or popliteal artery injuries were stratified into fasciotomy (n = 45) and non-fasciotomy (n = 101) groups. Adhering to the events-per-variable (EPV) principle (10:1), predictors were selected via least absolute shrinkage and selection operator (LASSO) regression and bootstrap validation. A multivariable logistic regression model was internally validated using tenfold cross-validation and 1000 bootstrap replicates. RESULTS: (OR = 6.99, 95% CI: 2.60-21.73), creatine kinase (CK; OR = 1.18, 95% CI: 1.08-1.30), and neutrophils (NEU) with a nonlinear threshold effect (OR = 1.20, 95% CI: 1.10-1.33). The nomogram demonstrated excellent discrimination (area under the curve [AUC] = 0.877, 95% CI: 0.819-0.934), precise calibration (Hosmer-Lemeshow P = 0.417), and broad clinical utility (net benefit threshold: 3-87%). CONCLUSIONS: , CK, and NEU as factors associated with fasciotomy risk. A nomogram based on these variables demonstrated reliable predictive performance and strong clinical applicability, enabling timely risk assessment and early intervention in patients with lower extremity arterial injuries. LEVEL OF EVIDENCE: Level 4.
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,190
Funder: Hebei Medical University
OpenAlex ID: W4416597289