Department of Spine Surgery, The Second Affiliated Hospital of Dalian Medical University, Dalian 116023, China.
Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Dalian Medical University, Dalian 116023, China.
Comput Intell Neurosci. 2022 Apr 11;2022:8978878. doi: 10.1155/2022/8978878. eCollection 2022.
Symptomatic rotator cuff calcific tendinitis (RCCT) is a common shoulder disorder, and approaches combined with artificial intelligence greatly facilitate the development of clinical practice. Current scarce knowledge of the onset suggests that clinicians may need to explore this disease thoroughly.
Clinical data were retrospectively collected from subjects diagnosed with RCCT at our institution within the period 2008 to 2020. A standardized questionnaire related to shoulder symptoms was completed in all cases, and standardized radiographs of both shoulders were extracted using a human-computer interactive electronic medical system (EMS) to clarify the clinical diagnosis of symptomatic RCCT. Based on the exclusion of asymptomatic subjects, risk factors in the baseline characteristics significantly associated with the onset of symptomatic RCCT were assessed via stepwise logistic regression analysis.
Of the 1,967 consecutive subjects referred to our academic institution for shoulder discomfort, 237 were diagnosed with symptomatic RCCT (12.05%). The proportion of women and the prevalence of clinical comorbidities were significantly higher in the RCCT cohort than those in the non-RCCT cohort. Stepwise logistic regression analysis confirmed that female gender, hyperlipidemia, diabetes mellitus, and hypothyroidism were independent risk factors for the entire cohort. Stratified by gender, the study found a partial overlap of risk factors contributing to morbidity in men and women. Diagnosis of hyperlipidemia, diabetes mellitus, and hypothyroidism in male cases and diabetes mellitus in female cases were significantly associated with symptomatic RCCT.
Independent predictors of symptomatic RCCT are female, hyperlipidemia, diabetes mellitus, and hypothyroidism. Men diagnosed with hyperlipidemia, diabetes mellitus, and hypothyroidism are at high risk for symptomatic RCCT, while more medical attention is required for women with diabetes mellitus. Artificial intelligence offers pioneering innovations in the diagnosis and treatment of musculoskeletal disorders, and careful assessment through individualized risk stratification can help predict onset and targeted early stage treatment.
症状性肩袖钙化性肌腱炎（RCCT）是一种常见的肩部疾病，结合人工智能的方法极大地促进了临床实践的发展。目前对于发病机制的了解甚少，提示临床医生可能需要彻底探索这种疾病。
本研究回顾性收集了 2008 年至 2020 年期间在我院确诊为 RCCT 的患者的临床资料。所有患者均完成了与肩部症状相关的标准化问卷，使用人机交互电子医疗系统（EMS）提取双侧肩部的标准化 X 线片，以明确症状性 RCCT 的临床诊断。通过逐步逻辑回归分析，评估基线特征中与症状性 RCCT 发病显著相关的危险因素，排除无症状患者。
在因肩部不适就诊于我院的 1967 例连续患者中，237 例被诊断为症状性 RCCT（12.05%）。RCCT 组的女性比例和临床合并症患病率显著高于非 RCCT 组。逐步逻辑回归分析证实，女性、高脂血症、糖尿病和甲状腺功能减退是整个队列的独立危险因素。按性别分层后，研究发现男性和女性发病的危险因素存在部分重叠。男性高脂血症、糖尿病和甲状腺功能减退的诊断，以及女性糖尿病的诊断与症状性 RCCT 显著相关。
症状性 RCCT 的独立预测因素是女性、高脂血症、糖尿病和甲状腺功能减退。诊断为高脂血症、糖尿病和甲状腺功能减退的男性发生症状性 RCCT 的风险较高，而女性糖尿病需要更多的医疗关注。人工智能为肌肉骨骼疾病的诊断和治疗提供了开创性的创新，通过个体化风险分层进行仔细评估有助于预测发病并进行针对性的早期治疗。
