Total Knee Replacement Kinematics and Wear Data Under Varying Surgical Conditions

Data associated with a paper on the effect of surgical alignment and soft tissue conditions on total knee replacement performance. The dataset contains raw data for mean Anterior-Posterior displacement, Tibial Rotation, and Axial Rotation with 95% confidence intervals across alignment and soft tissue conditions, as well as mean wear rates over 2 million cycles. Helena Johnston from the University of Leeds authored the associated research paper.

Use Cases

• Modeling the relationship between surgical alignment and knee implant kinematics based on AP displacement, TR rotation, and AA rotation data.
• Analyzing the effect of soft tissue conditions (stiff knee, preserved PCL, resected PCL) on implant wear rates.
• Comparing implant performance across specific alignment conditions (ideal, 4° varus, 14° rotational mismatch, 10° tibial slope).
• Validating computational biomechanical models using the provided raw data with confidence intervals.

Strengths

• Data includes 95% confidence intervals for key kinematic outputs (AP displacement, TR rotation, AA rotation).
• Covers multiple specific alignment conditions (ideal, 4° varus, 14° rotational mismatch, 10° tibial slope).
• Includes wear rate data quantified over 2 million cycles of simulated use.
• Explicitly compares three distinct soft tissue conditions (stiff knee, preserved PCL, resected PCL).

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Last update date is unknown; freshness unverified.

Provenance

Source

University of Leeds

Collection Method

Data associated with a published research paper; likely from experimental or simulation studies.