RESUMO
METHODS: Patients with shoulder pain were recruited in an outpatient rehabilitation clinic at the Third Affiliated Hospital of Sun Yat-Sen University from January 1, 2017, to June 30, 2018. These shoulder pain patients with or without limitation in joint movement can be included in the study. All of them received musculoskeletal ultrasound scanning. Demographic and imaging data including age, gender, duration of shoulder pain, pain side, and pathologies found by musculoskeletal ultrasound imaging were collected and analyzed. Patients were divided into three groups: <45 years (young group), between 45 and 60 years (middle-aged group), and >60 years (elderly group). The rates of various shoulder pathologies were evaluated and compared between the groups. RESULTS: This study recruited a total of 346 patients with shoulder pain. There were more female (62.1%) than male patients (37.9%), with the largest number of patients in the 45-60 years of age group (40.5%). Forty-eight percent of patients had shoulder pain within a period of 3 months. A total of 380 shoulders were assessed using musculoskeletal ultrasound imaging. The occurrence rate of subacromial disorder (83.8%) was the highest. The rate of supraspinatus tendinopathy, acromioclavicular joint degeneration, and adhesive shoulder capsulitis varied significantly between age groups (P < 0.05). The rate of acromioclavicular joint degeneration was the highest in the elderly group followed by the middle-aged and young groups (P < 0.0167). The rate of supraspinatus tendinopathy and adhesive capsulitis in the middle-aged and elderly groups was significantly higher than that in the young group (P < 0.0167). CONCLUSIONS: Musculoskeletal ultrasound can be a useful imaging tool in making an accurate diagnosis of shoulder pain. The occurrence rates of different shoulder pain pathologies in all age groups were thoroughly calculated in this study. More female and more subcoracoid disorder patients than western countries are attributed to repetitive lifting in daily life and work in this study. Correlations between these pathologies and their associated images can be a solid foundation for the development of artificial intelligence in diagnosing the cause of shoulder pain.