Defining subgroups of patients with a stiff and painful shoulder: an analytical model using cluster analysis

The primary purpose of this research was to develop a classification system for patients with stiff and painful shoulders using hierarchical cluster analysis.

Medical charts of 52 patients treated for stiff and painful shoulders were reviewed for descriptive and clinical data after completion of their rehabilitation. A clinician-reported outcome was derived from ratings of three members of the American Society of Shoulder and Elbow Therapists. Data were subjected to cluster analysis using the hierarchical method. Analysis of difference tests was performed to determine if differences between clusters could be found with either initial examination or outcome data.

Two clusters emerged from the clustering process: a healthy, strong, and mobile group of 32 patients, and an unhealthy, weak, and immobile groups consisting of 20 patients. Significant differences in initial examination measures between clusters were found for the presence of co-morbidities, range of motion for shoulder flexion, abduction, external rotation, and internal rotation, and strength of the shoulder external rotators and in the empty can position. Significant differences between clusters were found for shoulder flexion, abduction, and external rotation range of motion, and clinician-reported outcome at the time of patient discharge.

Patients with stiff and painful shoulders in this study were classified into two distinct subgroups using hierarchical cluster analysis based on demographic attributes and initial examination findings. The findings from this study also suggest that patients who may be at risk for a poorer outcome can be identified based on initial examination measures. By identifying these patients early in rehabilitation who have a poorer prognosis, improved patient education, alternative interventions or diagnostic tests may be utilized on their behalf.Implications for rehabilitationPatients with stiff and painful shoulders were classified into two subgroups using hierarchical cluster analysis based on demographic attributes and initial examination findings.Significant differences in mean clinician-reported outcome was also noted between clusters, with the patients who were healthier, stronger, and more mobile having a significantly better outcome than those patients who were more unhealthy, weak, and immobile.The findings from this study suggest that patients can be identified on initial examination who may be at risk for a poorer outcome.By identifying these patients early in rehabilitation who have a poorer prognosis, improved patient education, alternative interventions, or diagnostic tests may be utilized on their behalf sooner in the course of care.