Increasing Burden of Osteoarthritis in China: Trends and Projections from the Global Burden of Disease Study 2019.

BACKGROUND This study aimed to evaluate the epidemiology of osteoarthritis in China in a comprehensive and reliable way, to project its future epidemiological patterns, and to mitigate its health hazards. MATERIAL AND METHODS Data were extracted and analyzed from the Global Burden of Diseases Study 2019. Trends in osteoarthritis epidemiology were explored using joinpoint regression analysis. Additionally, we analyzed dynamic trends using the sociodemographic index (SDI) of China. To assess and predict the epidemiology of osteoarthritis from 2020 to 2039, we used both the Bayesian age-period-cohort model and Nordpred model. RESULTS The number of prevalent cases, incident cases, and years lived with disability (YLDs) for osteoarthritis in China increased from 51.8, 4.6, and 1.8 million, respectively, in 1990, to 132.8, 10.7, and 4.7 million, respectively, in 2019, and the average annual percentage changes were 3.286, 2.938, and 3.324, respectively. The prevalence and YLDs peaked in the population aged over 90 years old, while the incidence peaked in the population aged around 50 years old. A significant positive correlation was found between osteoarthritis burden and SDI. Osteoarthritis burden is expected to continue to increase. In the population studied here, it was higher in women than in men, but this may invert by 2039. CONCLUSIONS The prevalence, incidence, and YLDs of osteoarthritis had significantly increased and may continue to increase during the next 2 decades. Prevention and treatment strategies should target women, middle-aged individuals, and the elderly.

A new automatic stitching method for full-length lower limb radiography.

Full-length lower limb x-rays are used to diagnose and plan surgical procedures, such as Total Knee Arthroplasty (TKA) and High Tibial Osteotomy (HTO). Due to the size limitation of digital radiography (DR), panoramic x-ray images cannot be obtained in a single exposure, necessitating multiple exposures and image stitching. In favor of manually constructing full-length x-ray images, we propose a new feature-based automated method for stitching together x-ray images. This new method is based on Canny algorithm, which detects and aligns bone edges before fusing them using a Wavelet form domain. Twenty-eight sets of lower limb x-ray images obtained from our hospital have been stitched and evaluated. The hip, knee, and ankle (HKA) angle was computed in two different ways then compared to manually stitched x-ray images by an expert. The stitching time was only three seconds, and the P-value was P = 0.974, and an accuracy rate of 100% was found. This method demonstrated greater precision and speed than both manually stitched x-ray images and previously published methods.