ArticleInfection and drug resistance2024
Diagnostic Role of Metagenomic Next-Generation Sequencing in Tubercular Orthopedic Implant-Associated Infection.
Article in Infection and drug resistance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: The diagnosis of tubercular orthopedic implant-associated infection (TB-IAI) is challenging. This study evaluated the value of metagenomic next-generation sequencing (mNGS) for the diagnosis of TB-IAI and developed a standardized diagnostic procedure for TB-IAI. Methods: The records of all patients with TB-IAI diagnosed and treated at our institution between December 2018 and September 2022 were retrospectively reviewed. Patient demographic characteristics, medical history, laboratory test, microbial culture, histopathology, and mNGS results, and time to diagnosis were recorded. The diagnostic efficiency of mNGS for TB-IAI was assessed by comparing the results and diagnostic time with that of other diagnostic modalities. Results: Ten patients were included in the analysis, including eight with prosthetic joint infections and two with fracture-related infections. The mNGS positivity rate was 100% (10/10), which was higher than that of TB-antibody (11%, 1/9), real-time quantitative polymerase chain reaction (22%, 2/9), T-SPOT.TB (25%, 2/8), purified protein derivative (50%, 4/8), microbial culture (50%, 5/10), and histopathology (20%, 2/10). mNGS shortened the time to diagnosis of TB-IAI. A standardized diagnostic procedure for TB-IAI was developed based on the findings. Conclusion: mNGS is useful for the diagnosis of TB-IAI. mNGS is recommended in cases where it is difficult to identify a pathogen using routine diagnostic tests. The standardized diagnostic procedure might improve TB-IAI diagnosis. Importance: TB-IAI is a rare infection, which occurs after orthopedic surgery and hard to diagnose microbiologically. mNGS is a new detection technique not yet discussed in current literature as a means for TB-IAI diagnostics. Here we describe a cohort of patients with TB-IAI diagnosed by mNGS show high efficiency of mNGS for detection of this pathology and present a clinical algorithm supplementing conventional methods for TB-IAI assessment.
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