Clinical prediction model performance in differentiating septic arthritis from transient synovitis: A multi-center study

ObjectiveDifferentiating septic arthritis from transient synovitis in children is challenging. This study aimed to determine the diagnostic value for distinguishing these two conditions and to develop an effective clinical prediction model based on multi-center clinical data. MethodsWe retrospectively analyzed data of children aged under 18 years who were hospitalized in eight specialized childrens hospitals in China from 2013 to 2021. To ensure the prediction models reliability, we established three clinical prediction models. ResultsThis study collected data of 819 children from 8 tertiary childrens hospitals, including 265 patients with septic arthritis and 554 patients with transient synovitis. We established three clinical prediction models. For septic hip arthritis, a retrospective study based on six clinical predictors was a history of prodromal respiratory tract infection (HRTI), temperature>37.5 {degrees}C, ESR>20 mm/h, CRP>10 mg/L, red blood cell distribution width (RDW)>50%, and WBC>11x109 /L. When these six factors were present, the probability of septic hip arthritis was 99.99%. For septic knee arthritis, a retrospective study based on three clinical predictors, the predictors were ESR>20 mm/h, CRP>10 mg/L, and absolute monocyte count (AMONO)>0.74x109/L. When these three factors were present, the probability of having septic knee arthritis was 94.68%. For septic arthritis (septic hip arthritis or septic knee arthritis), a retrospective study based on six clinical predictors, the predictors were male children, history of HRTI), temperature>37.5 {degrees}C, ESR>20 mm/hr, PC > 407 x 109/L and CRP>10 mg/L. When these six factors were present, the probability of septic arthritis was 99.65%. ConclusionThis study used multi-center clinical data to construct a new clinical prediction model for children with septic arthritis. In addition we identified new clinical predictors such as sex, history of HRTI, RDW, PC and AMONO. Translational potentialA clinical prediction model, built on multi-center data, is capable of effectively making high-precision predictions for septic arthritis. Furthermore, based on the microbial characteristics of septic arthritis in children, we aim to develop diagnostic kits that can accurately and quickly detect infections caused by pathogens such as bacteria.