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Chinese Journal of Joint Surgery(Electronic Edition) ›› 2021, Vol. 15 ›› Issue (02): 185-191. doi: 10.3877/cma.j.issn.1674-134X.2021.02.009

Special Issue:

• Clinical Research • Previous Articles     Next Articles

Application of metagenomic next-generation sequencing in pathogen detection of periprosthetic joint infection

Linjie Hao1, Yumin Zhang1, Pengfei Wen1, Wei Song1, Jun Wang1, Tao Ma1,()   

  1. 1. Department of Hip Jiont, Hong-Hui Hospital, Xi’an Jiaotong University, Xi’an 710000, China
  • Received:2020-03-10 Online:2021-04-01 Published:2021-06-10
  • Contact: Tao Ma

Abstract:

Objective

To explore the value of metagenomic next-generation sequencing in pathogen detection of periprosthetic joint infection.

Methods

From January 2018 to October 2019, the data of patients who were diagnosed as periprosthetic joint infection in Hong-Hui Hospital of Xi’an Jiaotong University were analyzed retrospectively. The patients who received antibiotics within two weeks before sampling and failed to do mNGS detection due to substandard samples were excluded, and 34 patients were eventually included. All the patients were detected using the metagenomicnext-generation sequencing and bacterial culture simultaneously with recording the positive numbers anddetectiontime, as well as identifying bacterial species. The detection rates of metagenomic next-generation sequencing and bacterial culture in PJI patients were calculated and statistically analyzed by paired chi-square test.The detection time was analyzed by student's t test.

Results

Among the 34 patients with periprosthetic joint infection, there were 14 males and 20 females and involving 23 knees and 11 hips with an average age of (67.9±11.7) years. The positive rate of bacterial culture was 58.8%, whereas the positive rate of metagenomic next-generation sequencing was 88.2% and the difference was statistically significant (χ2=7.556, P < 0.05). The detection time of bacterial culture was (5.2±2.1) d, whereas the detection time of metagenomic next-generation sequencing was (1.6±0.6) d and the difference was statistically significant (t =9.678, P <0.05). Gram-positive bacteria was the main pathogen for periprosthetic joint infection and the most common bacteria were staphylococcus aureus, staphylococcus epidermidis and escherichia coli for both two methods.

Conclusion

Compared with bacterial culture, the metagenomic next-generation sequencing technology has a higher positive rate and shorter detection time, which might be greater valuable in prosthetic joint infection after joint replacement.

Key words: Arthroplasty, replacement, Prosthesis related infection, Metagenomics, High-throughput nucleotide sequencing

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