Machine-learning algorithm that can improve the diagnostic accuracy of septic arthritis of the knee.

ABSTRACT:

Purpose

Prompt diagnosis and treatment of septic arthritis of the knee is crucial. Nevertheless, the quality of evidence for the diagnosis of septic arthritis is low. In this study, the authors developed a machine learning-based diagnostic algorithm for septic arthritis of the native knee using clinical data in an emergency department and validated its diagnostic accuracy.

Methods

Patients (n = 326) who underwent synovial fluid analysis at the emergency department for suspected septic arthritis of the knee were enrolled. Septic arthritis was diagnosed in 164 of the patients (50.3%) using modified Newman criteria. Clinical characteristics of septic and inflammatory arthritis were compared. Area under the receiver-operating characteristic (ROC) curve (AUC) statistics was appli

SUBMITTER: Choi ES 

PROVIDER: S-EPMC8458173 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature