Clinical Scorecard: Utilizing Explainable Residual Ensemble Modeling for Quality of Life Evaluation and Stratification Based on EuroQol-5 Dimensions in Knee Osteoarthritis Patients

At a Glance

Key Highlights

• Knee OA is prevalent among older adults, affecting over one-third of those aged 65 and older in South Korea.
• The study utilizes the EQ-5D index score to evaluate health-related quality of life.
• A residual ensemble framework combines logistic regression with Random Forest for improved interpretability and predictive performance.
• The dataset includes 1,102 patients with knee OA and 29 clinical variables.
• Class imbalance was addressed using class weights during model training.

Guideline-Based Recommendations

Diagnosis

• Diagnosis of knee OA confirmed by ICD-10 codes and radiographic evidence.

Management

• Utilization of patient-reported measures like EQ-5D and WOMAC for monitoring rehabilitation outcomes.

Monitoring & Follow-up

• Regular assessment of QoL using the EQ-5D index score.

Risks

• Patients with EQ-5D scores below 0.7 are considered indicative of treatment failure.

Patient & Prescribing Data

1,102 patients diagnosed with knee osteoarthritis.

Focus on personalized care through data-driven tools and frameworks.

Clinical Best Practices

• Incorporate multidimensional assessments in QoL evaluations.
• Utilize explainable AI techniques to enhance model interpretability.
• Apply class weights in model training to address class imbalance.

Related Resources & Content

• EuroQol Group