Ankle Fracture Classification: An Innovative System for Describing Ankle Fractures

Abstract

A good classification system is important for clinical handoffs, research, and clinical treatment guidelines. A reliable classification system shows good interobserver and intraobserver agreement. This study analyzed the interobserver and intraobserver agreement of a descriptive system for ankle fractures and the Lauge-Hansen classification. Three groups of observers (experts, semiexperts, and novices) scored a total of 20 ankle radiographs. All ankle radiographs were classified according to the Lauge-Hansen and Danis-Weber classifications. The ankle fractures were subsequently reviewed in a descriptive manner for the following features: number of affected malleoli, type of fracture of the lateral and medial malleolus, and congruence of the ankle joint. After 2 weeks, the same set of radiographs were reviewed. For interobserver and intraobserver variability, the separate groups were used for analysis, and the Fleiss (multirater) κ values were calculated. The interobserver agreement for the Lauge-Hansen classification was moderate for the experts, fair for semiexperts, and slight for novices (κ = 0.45, κ = 0.37, and κ = 0.16). All factors of the descriptive system had better interobserver agreement than the Lauge-Hansen classification, except for the agreement on the type of fracture of the lateral malleolus. The intraobserver agreement of the Lauge-Hansen classification was substantial for the experts, moderate for the semiexperts, and fair for the novice observers (κ = 0.70, κ = 0.49, and κ = 0.26). The intraobserver agreement was better for all factors of the descriptive system compared with the Lauge-Hansen classification. The descriptive system presented in this study shows less variability between observers than the Lauge-Hansen classification. This system has clinical implications and is easy to use for clinicians with mixed levels of experience. It has the potential to improve clinical and research handoffs and overcome the limitations of current classification systems.