Background

Traditional culture methods have long been used to identify the presence of organisms in periprosthetic joint infections (PJI). However, increased false negative rates have decreased the clinical applicability of traditional culture methods. In cases where joints present with acute inflammation, clinicians will often treat with antibiotics and surgical debridement despite negative cultures. Prosthetic joints can also be infected despite cultures from aspirates and intraoperative samples showing negative results. Retrieval rates of less than 15% are seen at the time of surgery in patients with open draining sinus tracts, even for one organism. Furthermore, current literature has found a stark difference in accuracy between culture data and modern molecular diagnostic methods. To overcome deficiencies in traditional culture, more and more clinicians are looking for more robust organism identification methods such as Next Generation 16S DNA deep sequencing technologies.

Methods

29 patients were identified with open draining sinus tracts around an infected prosthesis, including 18 knees, 6 hips, 1 humerus, 1 shoulder, 1 sacrum, 1 femur and 1 tibia. All patients had several operations prior to referral to our clinic. All wounds were open and were culture negative. Each open wound was swabbed and underwent PCR and 16S deep sequencing on an orthopedic platform by Microgen. Upon receipt of the sample, Microgen extracts the microbial DNA and runs it through the Roche Light Cycler for PCR sequencing and the Illumina MiSeq for clonal amplification in order to gather data for analysis. The platform consists of 50,000 species of bacteria in their library with a readout from Illumina.

Results

None of this patient population had a positive culture of their draining sinus wound. Of these 29 patients, 8 of the open wounds were monomicrobial and the other 21 were found to be polymicrobial PJI, with an average of 2.97 bacterial species per culture. One patient also had a fungal species detected. Of the patients with polymicrobial infections, 10 grew both gram-positive and gram-negative bacteria.

Conclusion

Our findings indicate that in our entire patient population, culture was not sufficient to detect bacterial infection in patients following joint replacement arthroplasty. Next-generation 16S deep sequencing is shown to be more accurate, reliable and provide more in-depth analysis for the detection of microbial and fungal growth. Additionally, it has utility in identifying antibiotic resistance and guiding more suitable treatment utilizing antibiotic local carriers and systemic antibiotics.