An orthopaedic intelligence application successfully integrates data from a smartphone-based care management platform...

Area of Science:

• Orthopedic surgery
• Digital health technologies
• Biomedical data analysis

Background:

• Robotic-assisted total knee arthroplasty (raTKA) offers precision in knee replacement surgery.
• Smartphone-based care management platforms (sbCMP) enable remote patient monitoring and data collection.
• Understanding the relationship between intra-operative surgical parameters and post-operative patient outcomes is crucial for improving TKA results.

Purpose of the Study:

• To assess the feasibility of integrating sbCMP with raTKA for comprehensive episode-of-care data collection.
• To investigate the association between intra-operative soft tissue laxity measurements during raTKA and subsequent patient outcomes.
• To explore the potential of passively collected data in understanding TKA recovery.

Main Methods:

• A secondary analysis of 131 raTKA patients from a commercial database was conducted.
• Patient data, including step counts and KOOS JR scores (from pre-operative to six weeks post-operative), were collected via sbCMP.
• Intra-operative laxity measures were cross-referenced with collected patient outcomes using Kruskal-Wallis or Wilcoxon sign-rank tests.

Main Results:

• Knees with greater lateral compartment laxity in extension and medial compartment laxity in flexion exhibited higher six-week post-operative step counts (p < 0.05).
• Patients with flexion balance within 0.5 mm reported significantly higher KOOS JR scores at six weeks compared to those balanced within 0.5-1.5 mm (p = 0.034).
• The study demonstrated a correlation between specific intra-operative laxity parameters and patient-reported outcomes and functional recovery.

Conclusions:

• Smartphone-based care management platforms can be effectively integrated with robotic-assisted total knee arthroplasty for continuous data acquisition.
• Key intra-operative laxity measurements in raTKA are associated with post-operative functional recovery and patient-reported outcomes.
• Further research with more extensive data analysis is required to validate these associations and inform machine learning applications for personalized TKA care.