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Phenotypic Spectrum and Limb-Length Discrepancy in Congenital Lower Limb Deficiencies: A Tertiary Care Center
Fahad Alshayhan1, Mishari Alanezi2, Abdullah Addar1
1Department of Orthopedic Surgery, College of Medicine, King Saud University, Riyadh 11362, Saudi Arabia.
Background/Objectives:
Congenital lower-limb deficiencies, including proximal femoral focal deficiency (PFFD), fibular hemimelia (FH), and tibial hemimelia (TH), are rare, phenotypically heterogeneous disorders with important implications for reconstructive planning. However, phenotypic data remain limited. This study aimed to characterize the clinical and radiological spectrum of these deficiencies and evaluate associated anomalies and limb-length discrepancy (LLD) across diagnostic groups.
Materials And Methods:
A retrospective cohort study included all patients diagnosed with PFFD, FH, or TH at a tertiary referral center between January 2021 and December 2025. Demographic, clinical, and radiographic data were extracted from electronic medical records. Patients were classified using established systems, and associated anomalies, distal morphology, laterality, and LLD were evaluated. Descriptive statistics and exploratory non-parametric comparisons across diagnostic groups were performed.
Results:
A total of 143 patients were included: 91 (63.6%) with PFFD, 23 (16.1%) with FH, 10 (7.0%) with TH, 18 (12.6%) with combined PFFD + FH, and 1 (0.7%) with combined PFFD + TH. Isolated PFFD was predominantly unilateral and clustered within the milder spectrum, most commonly Paley type 1a and Aitken type A. In contrast, FH was dominated by the severe Paley type 3b phenotype, whereas TH showed marked classification heterogeneity. Upper-limb anomalies were more common in FH and TH than in isolated PFFD. LLD differed significantly among diagnostic groups (p = 0.003), with the greatest median discrepancies observed in combined PFFD + FH and isolated PFFD.
Conclusions:
Congenital lower-limb deficiencies are highly heterogeneous, with combined deficiencies exhibiting greater LLD and anomaly burden. These findings provide structured regional data to support classification and reconstructive planning.
