Preoperative identification of causal organism(s) is crucial for effective prosthetic joint infection treatment. Herein, we explore the clinical application of a novel metatranscriptomic (MT) workflow, CSI-Dx, to detect pathogens associated with prosthetic joint infection. MT provides insight into transcriptionally active microbes, overcoming limitations of culture-based and available molecular methods. This study included 340 human synovial fluid specimens subjected to CSI-Dx and traditional culture-based methods. Exploratory analyses were conducted to determine sensitivity and specificity of CSI-Dx for detecting clinically-relevant taxa. Our findings provide insights into the active microbial community composition of synovial fluid from arthroplasty patients and demonstrate the potential clinical utility of CSI-Dx for aiding prosthetic joint infection diagnosis. This approach offers potential for improved sensitivity and acceptable specificity compared to synovial fluid culture, enabling detection of culturable and non-culturable microorganisms. Furthermore, CSI-Dx provides valuable information on antimicrobial resistance gene expression. While further optimization is needed, integrating metatranscriptomic technologies like CSI-Dx into routine clinical practice can revolutionize prosthetic joint infection diagnosis by offering a comprehensive and active snapshot of associated pathogens.