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Updated: May 5, 2026
Novel Diagnostics in Revision Arthroplasty: Implant Sonication and Multiplex Polymerase Chain Reaction
Published on: December 3, 2017
Blood Cell Ratio Combinations for Diagnosing Periprosthetic Joint Infections: A Preliminary Study
Yali Yu1, Yanan Wen2, Jiaxuan Xia3
1Department of Clinical Laboratory, Zhengzhou Orthopaedic Hospital, Zhengzhou, People's Republic of China.
Background:
Periprosthetic joint infection (PJI) is a serious complication following total joint arthroplasty (TJA), which requires prompt and accurate diagnosis for effective management. Many biomarkers have been used for PJI diagnosis; however, the identification of the most effective inflammatory biomarker combination for optimal diagnostic accuracy may be poorly reported.
Methods:
In this prospective, multi-center study, a total of 269 individuals undergoing knee or hip revision arthroplasty were recruited and subsequently categorized based on 2018 ICM PJI criteria into two groups: 93 with periprosthetic joint infection (PJI) and 176 with aseptic failure (AF). Various preoperative biomarkers were analyzed and compared, including C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), neutrophil-to-lymphocyte ratio (NLR), CRP-to-albumin ratio (CAR), CRP-Albumin-lymphocyte ratio (CALLR), platelet-to-lymphocyte ratio (PLR), platelet-to-albumin ratio (PAR), and neutrophil-to-albumin ratio (NAR). The diagnostic performance of these biomarkers was evaluated using ROC curve analysis and the area under the curve (AUC). Additionally, the Youden index was used to determine optimal threshold values, and positive predictive value (PPV) and negative predictive value (NPV) were calculated to evaluate diagnostic precision.
Results:
In the PJI group, levels of PAR, CAR, and CALLY were notably higher compared to the AF group, reaching statistical significance (P < 0.05). PAR and CAR were confirmed to have high diagnostic values, with AUC values of 0.779 and 0.718, respectively. CALLY exhibited moderate diagnostic effectiveness, with an AUC of 0.647. When PAR was combined with CRP and ESR, sensitivity and specificity notably improved to 93.8% and 92.5%, respectively. However, subgroup analysis revealed no significant differences in combined inflammatory biomarker levels between the two groups.
Conclusion:
PAR and CAR prove to be effective combined inflammatory biomarkers for PJI diagnosis, whereas other markers exhibited limited diagnostic utility for PJI.
Insights
Platelet-to-albumin ratio (PAR) and CRP-to-albumin ratio (CAR) show promise as effective biomarkers for diagnosing periprosthetic joint infection (PJI). Combining PAR with CRP and ESR significantly improved diagnostic accuracy in this study.
Area of Science:
- Orthopedics
- Infectious Diseases
- Biomarkers
Background:
- Periprosthetic joint infection (PJI) is a severe complication of total joint arthroplasty (TJA).
- Accurate diagnosis of PJI is crucial for effective management.
- Optimal combinations of inflammatory biomarkers for PJI diagnosis are not well-established.
Purpose of the Study:
- To evaluate the diagnostic performance of various preoperative inflammatory biomarkers for PJI.
- To identify the most effective biomarker combination for improving PJI diagnostic accuracy.
Main Methods:
- A prospective, multi-center study involving 269 patients undergoing revision arthroplasty.
- Patients were classified into PJI (n=93) and aseptic failure (AF) (n=176) groups using 2018 ICM PJI criteria.
- Analysis of biomarkers including CRP, ESR, NLR, CAR, CALLR, PLR, PAR, and NAR, with evaluation by ROC analysis and Youden index.
Main Results:
- Platelet-to-albumin ratio (PAR) and CRP-to-albumin ratio (CAR) were significantly higher in the PJI group (P < 0.05).
- PAR (AUC=0.779) and CAR (AUC=0.718) demonstrated high diagnostic values.
- Combining PAR with CRP and ESR improved sensitivity to 93.8% and specificity to 92.5%.
Conclusions:
- PAR and CAR are effective combined inflammatory biomarkers for PJI diagnosis.
- Other analyzed markers showed limited diagnostic utility for PJI.
- Further research may explore optimal biomarker combinations for PJI.
