Predictors of Deformity in Patients with Progressive Collapsing Foot Deformity and Valgus of the Ankle

Category: Ankle; Hindfoot Introduction/Purpose: Markers of diagnosis and severity are well studied in patients with Progressive Collapsing Foot Deformity (PCFD). Medial facet subluxation (MFS) in weight-bearing computerized tomography (WBCT) has been established as an indicator of peritalar subluxat...

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Published in:Foot & ankle orthopaedics 2022-01, Vol.7 (1), p.2473011421S00343
Main Authors: Mansur, Nacime S., Lalevee, Matthieu, Vivtcharenko, Victoria, Dibbern, Kevin N., Ellis, Scott J., Deland, Jonathan T., Godoy-Santos, Alexandre L., Femino, John E., Auch, Elijah, Netto, Cesar de Cesar
Format: Article
Language:English
Subjects:
Ankle
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Summary:Category: Ankle; Hindfoot Introduction/Purpose: Markers of diagnosis and severity are well studied in patients with Progressive Collapsing Foot Deformity (PCFD). Medial facet subluxation (MFS) in weight-bearing computerized tomography (WBCT) has been established as an indicator of peritalar subluxation and an earlier detector of the disease. When the disease affects the ankle leading to a valgus talar tilt (class E), structures distal to this topography may behavior differently, trying to compensate proximal deformity. The aim of this study is to assess predictors of deformity in PCFD patients with and without valgus of the ankle. Our hypothesis is that MFS could not be used in class E patients as an accurate value for estimation and staging of PCFD. Methods: In this IRB-approved retrospective case-control study we analyzed WBCT acquisitions of 21 consecutive patients with PCFD presenting valgus of the ankle and 64 controls (flexible PCFD with no ankle involvement). MFS (percentage of uncoverage), middle facet incongruence angle, middle cuneiform-to-floor distance, forefoot arch angle, talonavicular uncoverage angle, hindfoot moment arm (HMA), Foot and Ankle Offstet (FAO) and talar tilt angle (TTA) were obtained and compared between groups using oneway ANOVA. A multivariate regression analysis was performed to evaluate which of the measurements influenced the alignment. A partition prediction model was also constructed to find how the variables contributed to the deformity and its aspects. Statistical significancy was set in p values
ISSN:2473-0114
2473-0114
DOI:10.1177/2473011421S00343