Preoperative gap phenotypes in functionally aligned robotic total knee arthroplasty: derivation and internal coherence of a driver-based classification

Robotic total knee arthroplasty (TKA) enables repeated intraoperative quantification of preoperative alignment, flexion deformity, and medial and lateral compartment gaps in extension and at 90° flexion before component positioning, but the preoperative patterns guiding functional-alignment planning remain incompletely characterized. This study aimed to derive a pragmatic driver-based classification from preoperative robotic data and evaluate its internal coherence across the surgical workflow. We analyzed 68 consecutive primary functionally aligned robotic TKAs performed by a single surgeon using a CT-based robotic-arm platform. Preoperative variables included hip-knee-ankle angle (HKA), flexion deformity, and independent medial and lateral gaps in extension and at 90° flexion. A 10-case formative series informed concept generation; the finalized hierarchy was then applied to all cases using preoperative variables only. Four phenotypes were derived: bone-driven, ligament-driven, flexion-dominant, and mixed/complex (defined as the co-occurrence of two or more severe deformity drivers). Internal coherence was assessed through release escalation, corrected-state behavior, plan-to-final HKA fidelity, and mechanical and functional-alignment balance. Inter-observer reliability was tested by having five independent surgeons classify all cases blinded, with agreement quantified by Fleiss' and Cohen's kappa. All knees were classified: bone-driven, 40/68 (58.8%); ligament-driven, 6/68 (8.8%); flexion-dominant, 10/68 (14.7%); and mixed/complex, 12/68 (17.6%). Release escalation occurred in 1/68 (1.5%), with no posterior capsulotomy. Overall, 58/63 (92.1%) finished within ± 2° of planned HKA; strict mechanical balance was achieved in 58/62 (93.5%) and functional-alignment balance in 61/62 (98.4%). Flexion-dominant knees showed lower coronal fidelity but complete final balance, suggesting a coronal-sagittal trade-off during functional planning. Inter-observer agreement among the five surgeons was almost perfect (Fleiss' kappa 0.88, 95% CI 0.81-0.93; 92.4% overall agreement). Preoperative HKA, sagittal deformity, and medial-lateral gap asymmetry revealed recurring patterns organized into a four-phenotype driver framework. This classification is best interpreted as an internally coherent derivation framework that showed almost perfect inter-observer reliability (Fleiss' kappa 0.88) but still requires external, multicenter validation and threshold-sensitivity analysis before its clinical utility can be established.