ABSTRACT
Objective:To investigate the value of common clinical symptoms and signs of knee joint, elbow joint and lumbar spine in clinical diagnosis of endemic skeletal fluorosis.Methods:From August to October 2020, a cross-sectional survey of skeletal fluorosis was conducted in 8 administrative villages in Gaotai County and 5 administrative villages in Gaolan County, which were serious areas of drinking-water-borne endemic fluorosis in Gansu Province. Individuals aged ≥25 years old, residing for more than 1 year, and exhibiting symptoms and signs of the motor system in the affected villages were selected as the survey subjects. According to the X-ray diagnostic criteria in the "Diagnostic Standard for Endemic Skeletal Fluorosis" (WS/T 192-2021), they were divided into skeletal fluorosis group and non skeletal fluorosis group. The basic information of the two groups was collected, and orthopedic examination and digital radiography (DR) were performed. Multivariate logistic regression model was used to fit the effects of knee joint, elbow joint and lumbar spine related symptoms and signs on the diagnosis of skeletal fluorosis. Receiver operating characteristic (ROC) curve was drawn to evaluate the predictive effectiveness of the model for skeletal fluorosis, and Kappa test was used to evaluate the consistency between the model and X-ray diagnosis (the gold standard for diagnosis of skeletal fluorosis). Results:A total of 970 subjects were included in the investigation, including 501 in the skeletal fluorosis group and 469 in the non skeletal fluorosis group. Multivariate logistic regression analysis showed that elbow joint flexion and extension range of motion (ROM) decreased by ≥45° [odds ratio ( OR) = 2.73, 95% confidence interval ( CI): 2.00 - 3.72], elbow joint rotation ROM decreased by ≥30° ( OR = 3.34, 95% CI: 1.96 - 5.68), ulnar nerve injury symptoms ( OR = 3.77, 95% CI: 3.21 - 4.42), intermittent claudication ( OR = 2.72, 95% CI: 1.48 - 4.99), and positive straight leg elevation test ( OR = 1.69, 95% CI: 1.09 - 2.61) had certain impact on the diagnosis of skeletal fluorosis. The area under the ROC curve was 0.88, and the model had a good predictive ability for the diagnosis of skeletal fluorosis. After Kappa test, the Kappa value was 0.61, which suggested that the prediction of skeletal fluorosis by this model was in good agreement with X-ray diagnosis. Conclusions:Elbow joint flexion and extension limitation, elbow joint rotation limitation, ulnar nerve injury, intermittent claudication, and positive straight leg elevation test have certain diagnostic value for skeletal fluorosis. The combined diagnosis of these signs has good predictive ability for skeletal fluorosis.