MRI-based Predictors and Risk Constellations of Chronic Ankle Instability After Acute Lateral Ankle Sprain: A Multicenter Study.

RATIONALE AND

OBJECTIVES

Chronic ankle instability (CAI) is a common but under-recognized consequence of acute lateral ankle sprain (LAS), yet early identification of high-risk patients remains challenging. This study aimed to identify independent Magnetic resonance imaging (MRI) predictors of CAI assessed following an initial acute LAS and to explore clinically meaningful risk constellations.

MATERIALS AND

METHODS

This multicenter retrospective study included 474 patients with initial acute LAS who underwent ankle MRI within two weeks. Patients were classified as CAI or "Coper" (recovered without instability) at 24-month follow-up using the Cumberland Ankle Instability Tool and symptom assessment. Two blinded musculoskeletal radiologists evaluated ligament injuries, bone marrow edema, joint effusion, and osteochondral lesions. Multivariable logistic regression identified independent predictors, and risk constellations were analyzed using multiplicative and additive interaction analyses. Prediction models were developed to assess the clinical significance of risk constellations.

RESULTS

CAI developed in 163 patients (34.4%). Independent predictors included age (OR=1.07, p < 0.001), talar osteochondral lesions (TOL; OR=1.35, p = 0.042), and talonavicular ligament (TNL) injury Odds ratio (OR)=1.48, p=0.009). Several interaction-based risk constellations increased CAI risk, including TOL with male sex or severe calcaneofibular ligament injury, severe TNL injury with anterior talofibular or tibiocalcaneal ligament injury, and higher age with grade 2 talocalcaneal effusion (synergy index=3.24-4.45). Incorporation of risk constellations into prediction models improved patient risk reclassification Net reclassification improvement (NRI)=14.8%).

CONCLUSION

Beyond age, MRI-detected TOL and TNL injuries after initial LAS are independent predictors of CAI. Risk constellations based on these predictors substantially increase CAI risk and may facilitate early identification of high-risk patients.