Aims. The preoperative diagnosis of periprosthetic joint infection (PJI) remains a challenge due to a lack of biomarkers that are both sensitive and specific. We investigated the performance characteristics of polymerase chain reaction (PCR), interleukin-6 (IL6), and calprotectin of synovial fluid in the diagnosis of PJI. Methods. We performed systematic search of PubMed, Embase, The Cochrane Library, Web of Science, and Science Direct from the date of inception of each database through to 31 May 2021. Studies which described the diagnostic accuracy of synovial fluid PCR, IL6, and calprotectin using the Musculoskeletal Infection Society criteria as the reference standard were identified. Results. Overall, 31 studies were identified: 20 described PCR, six described IL6, and five calprotectin. The sensitivity and specificity were 0.78 (95% confidence interval (CI) 0.67 to 0.86) and 0.97 (95% CI 0.94 to 0.99), respectively, for synovial PCR;, 0.86 (95% CI 0.74 to 0.92), and 0.94 (95% CI 0.90 to 0.96), respectively, for synovial IL6; and 0.94 (95% CI 0.82 to 0.98) and 0.93 (95% CI 0.85 to 0.97), respectively, for synovial calprotectin. Likelihood ratio scattergram analyses recommended clinical utility of synovial fluid PCR and IL6 as a confirmatory test only. Synovial calprotectin had utility in the exclusion and confirmation of PJI. Conclusion. Synovial fluid PCR and IL6 had low sensitivity and high specificity in the diagnosis of PJI, and is recommended to be used as confirmatory test. In contrast, synovial fluid calprotectin had both high sensitivity and specificity with utility in both the exclusion and confirmation of PJI. We recommend use of synovial fluid calprotectin studies in the preoperative workup of PJI. Cite this article: Bone Joint J 2022;104-B(3):311–320

Aims. This study aimed to compare the effect of antibiotic-loaded bone cement (ALBC) versus plain bone cement (PBC) on revision rates for periprosthetic joint infection (PJI) and all-cause revisions following primary elective total hip arthroplasty (THA) and total knee arthroplasty (TKA). Methods. MEDLINE, Embase, Web of Science, and Cochrane databases were systematically searched for studies comparing ALBC versus PBC, reporting on revision rates for PJI or all-cause revision following primary elective THA or TKA. A random-effects meta-analysis was performed. The study was registered in the International Prospective Register of Systematic Reviews (PROSPERO ID CRD42018107691). Results. Nine studies and one registry report were identified, enabling the inclusion of 371,977 THA and 671,246 TKA. Pooled analysis for THA demonstrated ALBC was protective against revision for PJI compared with PBC (relative risk (RR) 0.66, 95% confidence interval (CI) 0.56 to 0.77; p < 0.001), however, no differences were seen for all-cause revision rate (RR 0.62, 95% CI 0.35 to 1.09; p = 0.100). For TKA, there were no significant differences in revision rates for PJI or all causes between ALBC and PBC (RR 0.92, 95% CI 0.59 to 1.45; p = 0.730, and RR 0.73, 95% CI 0.53 to 1.02; p = 0.060, respectively). Conclusion. ALBC demonstrated a protective effect against revision for PJI compared with PBC in THA with no difference in all-cause revisions. No differences in revision rates for PJI and all-cause revision between ALBC and PBC for TKA were observed. Cite this article: Bone Joint J 2021;103-B(1):7–15

Aims. Periprosthetic joint infection (PJI) is a serious complication of total hip arthroplasty (THA). Different bearing surface materials have different surface properties and it has been suggested that the choice of bearing surface may influence the risk of PJI after THA. The objective of this meta-analysis was to compare the rate of PJI between metal-on-polyethylene (MoP), ceramic-on-polyethylene (CoP), and ceramic-on-ceramic (CoC) bearings. Patients and Methods. Electronic databases (Medline, Embase, Cochrane library, Web of Science, and Cumulative Index of Nursing and Allied Health Literature) were searched for comparative randomized and observational studies that reported the incidence of PJI for different bearing surfaces. Two investigators independently reviewed studies for eligibility, evaluated risk of bias, and performed data extraction. Meta-analysis was performed using the Mantel–Haenzel method and random-effects model in accordance with methods of the Cochrane group. Results. Our search strategy revealed 2272 studies, of which 17 met the inclusion criteria and were analyzed. These comprised 11 randomized controlled trials and six observational studies. The overall quality of included studies was high but the observational studies were at high risk of bias due to inadequate adjustment for confounding factors. The overall cumulative incidence of PJI across all studies was 0.78% (1514/193 378). For each bearing combination, the overall incidence was as follows: MoP 0.85% (1353/158 430); CoP 0.38% (67/17 489); and CoC 0.53% (94/17 459). The meta-analysis showed no significant difference between the three bearing combinations in terms of risk of PJI. Conclusion. On the basis of the clinical studies available, there is no evidence that bearing choice influences the risk of PJI. Future research, including basic science studies and large, adequately controlled registry studies, may be helpful in determining whether implant materials play a role in determining the risk of PJI following arthroplasty surgery. Cite this article: Bone Joint J 2018;100-B:134–42

Literature surrounding artificial intelligence (AI)-related applications for hip and knee arthroplasty has proliferated. However, meaningful advances that fundamentally transform the practice and delivery of joint arthroplasty are yet to be realized, despite the broad range of applications as we continue to search for meaningful and appropriate use of AI. AI literature in hip and knee arthroplasty between 2018 and 2021 regarding image-based analyses, value-based care, remote patient monitoring, and augmented reality was reviewed. Concerns surrounding meaningful use and appropriate methodological approaches of AI in joint arthroplasty research are summarized. Of the 233 AI-related orthopaedics articles published, 178 (76%) constituted original research, while the rest consisted of editorials or reviews. A total of 52% of original AI-related research concerns hip and knee arthroplasty (n = 92), and a narrative review is described. Three studies were externally validated. Pitfalls surrounding present-day research include conflating vernacular (“AI/machine learning”), repackaging limited registry data, prematurely releasing internally validated prediction models, appraising model architecture instead of inputted data, withholding code, and evaluating studies using antiquated regression-based guidelines. While AI has been applied to a variety of hip and knee arthroplasty applications with limited clinical impact, the future remains promising if the question is meaningful, the methodology is rigorous and transparent, the data are rich, and the model is externally validated. Simple checkpoints for meaningful AI adoption include ensuring applications focus on: administrative support over clinical evaluation and management; necessity of the advanced model; and the novelty of the question being answered.

Cite this article: Bone Joint J 2022;104-B(12):1292–1303.

Aims

The principle strategies of fracture-related infection (FRI) treatment are debridement, antimicrobial therapy, and implant retention (DAIR) or debridement, antimicrobial therapy, and implant removal/exchange. Increasing the period between fracture fixation and FRI revision surgery is believed to be associated with higher failure rates after DAIR. However, a clear time-related cut-off has never been scientifically defined. This systematic review analyzed the influence of the interval between fracture fixation and FRI revision surgery on success rates after DAIR.