Aim:
Current total knee arthroplasty (TKA) phenotype classifications primarily describe osseous morphology and
coronal limb alignment, but do not adequately characterize the periarticular soft-tissue envelope. The aim of
this study was to propose and validate the Surgical Evaluation of Knee Soft-Tissue Envelope (SEKSE) classification as a
standardized nomenclature system for describing native and surgically achieved knee soft-tissue phenotypes
during robotic-assisted TKA, which is comprehensive yet easy to use and system agnostic.
Methods:
The SEKSE classification describes the knee soft-tissue envelope using three principal domains: coronal
balance, sagittal balance, and terminal extension status. Coronal balance describes the medial–lateral gap
relationship in extension and flexion, expressed as E and F components. Sagittal balance describes the
relationship between extension and flexion gaps separately on the medial and lateral sides, expressed as
M and L components. Each coronal and sagittal component is graded according to the magnitude of the
measured gap difference: Type 1, ≤1 mm; Type 2, >1–3 mm; Type 3, >3–5 mm; and Type 4, >5 mm.
Directionality is indicated using positive or negative notation, allowing the classification to specify whether
the medial or lateral compartment is relatively tighter in the coronal plane, and whether the extension
or flexion gap is relatively tighter in the sagittal plane. Terminal extension status is expressed separately as
hyperextension, neutral extension, flexion deformity, or severe flexion deformity. The result is a comprehensive description of soft tissue behaviour using only 5 notations - E F M L R – each with a simple magnitude and directional designation.
The classification was validated using a retrospective cohort of 150 knees undergoing robotic-assisted TKA using 3 platforms. Fifty knees each were assessed using Mako (Stryker), Apollo (Corin), and ROSA (Zimmer) robotic platforms. Medial and lateral compartment laxity values were recorded preoperatively and postoperatively in extension and at 90°, and a SEKSE classification of each knee defined. Intra- and Interobserver reliability of the classification correlation was assessed with 2 independent observers
Results:
Mean age was 66.3 ± 8.4 years in the Mako group, 72.0 ± 7.2 years in the Apollo group, and 71.6 ± 7.2 years in the ROSA group, with similar gender distribution in each. Most continuous soft-tissue balance variables were non-normally distributed, except preoperative coronal balance in flexion. SEKSE enabled structured description of both native preoperative laxity patterns and postoperative balance states in all knees across all three robotic workflows. Intra- and Interobserver agreement for the SEKSE classification was excellent, with an intraclass correlation coefficient of 1.00 for both.
Conclusion:
The SEKSE classification provides a nomenclature system for describing knee soft-tissue phenotypes in robotic TKA which is clear, comprehensive, reproducible and system agnostic. By incorporating coronal balance, sagittal balance, terminal extension status, and the magnitude and directionality of laxity, SEKSE provides a structured method to easily describe both the native soft-tissue envelope and surgically achieved balance allowing comparison across platforms, clear communication between surgeons, and application to research, surgical planning and outcome assessment.
