ArticleInfection and drug resistance2023
Can Platelets/Mean Platelet Volume Accurately Diagnose Periprosthetic Joint Infection? Revealing Their Actual Diagnostic Efficacy.
Article in Infection and drug resistance, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 4 citations in OpenAlex.
- The Utility of Synovial Fluid Interleukin-10 in Diagnosing Chronic Periprosthetic Joint Infection: A Prospective Cohort Study.Infection and drug resistance · 2025Article
- Serum inflammatory markers for the screening and diagnosis of periprosthetic joint infection: a systematic review and meta-analysis.Journal of bone and joint infection · 2025Review
- Role of Serum Biomarkers in Differentiating Periprosthetic Joint Infections from Aseptic Failures after Total Hip Arthroplasties.Journal of clinical medicine · 2024Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Currently, there is no single test indicator for diagnosing periprosthetic joint infection (PJI) with an acceptable level of sensitivity. Therefore, ratio indicators have been introduced to improve the accuracy of diagnostic algorithms. Platelet count /mean platelet volume (PMR) is reported to be a potential PJI diagnostic biomarker, but its clinical value for diagnosing PJI is still uncertain. This study aims to provide additional evidence to support the effectiveness of PMR in accurately diagnosing PJI. Methods: This study recruited 116 patients with PJI and 137 patients with aseptic loosening, divided them into PJI group and AL group. Collect subjects' preoperative laboratory indicators such as ESR, CRP, PLT, MPV, etc. The area under the curve (AUC) was calculated by plotting the receiver operating characteristic (ROC) curve to determine the diagnostic efficacy of PMR. Results: ESR, CRP, PLT, and PLT/MPV were significantly increased in the PJI group, while MPV levels were decreased (both P< 0.001). The AUC of the PMR was 0.752, and the optimal cut-off value for diagnosing chronic PJI was determined to be 27.8 based on the Youden index. The sensitivity and specificity for diagnosing PJI were 79.3% and 47.9%, respectively, with a positive predictive value of 68.27%, a negative predictive value of 69.80%, and a diagnostic odds ratio of 4.97. The AUC (0.752) of the ratio biomarker was lower than that of ESR (0.825) and CRP (0.900). After predictive model calculation, the combination of PMR, CRP, and ESR had an AUC value of 0.910, with a sensitivity of 84.5% and a specificity of 84.7%, showing good discriminative ability. Conclusion: Compared with traditional biomarkers ESR and CRP, the value of the PMR for diagnosing PJI is not significant, but it can be used as an auxiliary indicator for PJI diagnosis in combination with other indicators (P<0.001).
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