Abstract
BACKGROUND: Currently, two classification systems, namely Stephens and Sanders, based on axial CT images, and Zwipp and Rammelt, which consider deformities, are used for calcaneus malunions. Existing classifications have limitations due to their pure anatomical basis, and the complexity of the problem, involving both bone and soft tissues. As a solution, the senior author proposed a novel ADIENS classification system for calcaneal malunion, based on pain generators. This study aimed to introduce and evaluate the inter- and intra-observer reliability of a new classification system for calcaneal malunions. METHODS: This retrospective cohort study included adult cases with post-traumatic calcaneus malunion. Three experienced foot and ankle surgeon volunteers underwent training session on the classification system, which classifies malunions based on A arthritis, D deformity, E exostosis, I implant issues, N nerve issues, and S soft tissue issues. Post-training, two rounds of classification exercises were conducted. Inter-rater and intra-rater agreements were determined using Gwet's AC coefficient. RESULTS: Out of 15 cases, 6 were of Stephen and Sanders types, and 8 were of Zwipp and Rammelt types, the rest fell out of these classifications. Inter-rater agreement for ADEINS classification was noted to be 'very good' for all six domains. Intra-observer agreements were 'very good' for four out of six domains of classification and 'fair' for two domains of classification. CONCLUSION: Pain generators-based new ADEINS classification has demonstrated good intra- and inter-observer reliability and seemed user-friendly. However, results need to be replicated in a larger, multicentric cohort before wider clinical applicability. LEVEL OF EVIDENCE: Level IV, retrospective study.