NDLI: Meta-analysis of synovial fluid polymerase chain reaction for diagnosing periprosthetic hip and knee infection

Content Provider	Springer Nature : BioMed Central
Author	Li, Cheng Li, Hao Yang, Xue Zhu, Fang-Zheng Xu, Chi Trampuz, Andrej
Abstract	Background and objective The purpose of this study was to estimate the diagnostic performance of synovial fluid polymerase chain reaction (PCR) in periprosthetic hip and knee infection, and whether synovial fluid PCR has greater diagnostic significance than conventional methods. Methods The literature databases PubMed, Scopus, and the Web of Science were searched for English articles describing periprosthetic joint infection (PJI) diagnosis by synovial fluid PCR. Articles were limited to the period between January 1990 and December 2019. Subsequently, conventional methods that were used on at least two occasions were included for further analysis. Data analysis was performed using the Meta-DiSc and Stata software. Results Eleven studies with 1360 cases were included in the meta-analysis. The pooled sensitivity, specificity, and diagnostic odds ratio (DOR) of synovial fluid PCR were 0.70 (95% CI 0.66–0.74), 0.92 (95% CI 0.90–0.93), and 37.4 (95% CI 17.77–78.74), respectively. Conclusions Synovial fluid PCR provides an effective tool for rapid diagnosis of PJI, and also in the early stages of culture-negative bacterial infections.
Related Links	https://josr-online.biomedcentral.com/counter/pdf/10.1186/s13018-021-02813-8.pdf
Ending Page	13
Page Count	13
Starting Page	1
File Format	HTM / HTML
DOI	10.1186/s13018-021-02813-8
Journal	Journal of Orthopaedic Surgery and Research
Issue Number	1
Volume Number	17
Language	English
Publisher	BioMed Central
Publisher Date	2022-01-04
Access Restriction	Open
Subject Keyword	Orthopedics Surgical Orthopedics Meta-analysis Diagnosis Arthroplasty Periprosthetic joint infection Synovial fluid Polymerase chain reaction
Content Type	Text
Resource Type	Article
Subject	Surgery Orthopedics and Sports Medicine
Journal Impact Factor	2.8/2023
5-Year Journal Impact Factor	3/2023

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