Identification of Priority Clinical Variables in Rehabilitation of Lower Extremity Amputation

The complexity of clinical follow-up stems from the wide range of variables involved, such as physical performance, mobility, pain, psychological well-being, and prosthetic functionality. Therefore, developing methods to identify the most relevant and interrelated clinical variables is critical for enhancing patient management. To address this need, Hierarchical Cluster Analysis (HCA) offers a powerful multivariate statistical approach for detecting relationships among clinical variables.