Trial reportInfection and drug resistance2024
Quantifying the Long and Short Axes of the External Iliac Lymph Nodes Using Dual-Energy Computed Tomography: A Potential Diagnostic Approach for Periprosthetic Joint Infection - A Prospective Study.
Trial report in Infection and drug resistance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Machine Learning Strategies for Preoperative PJI Diagnosis: Integrative Analysis of Serum and Synovial Fluid Markers.Journal of inflammation research · 2025Article
- Evaluation of Heparin-Binding Protein as a novel biomarker for the detection of periprosthetic joint infection.Frontiers in cellular and infection microbiology · 2025Article
Corrections and comments
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Periprosthetic joint infection (PJI) is a severe complication following joint replacement surgery, and there is a current lack of rapid, accurate, and non-invasive diagnostic methods. This study aims to assess the effectiveness of using dual-energy computed tomography (DECT) to quantify the maximum long and short axes of the external iliac lymph nodes (LNs) as a diagnostic tool for PJI. Patients and Methods: In this prospective controlled study, 112 patients undergoing total hip or total knee revision surgery were enrolled. All patients underwent preoperative DECT scanning to measure the maximum long and short axes of the external iliac LNs on the affected side. The diagnostic value of lymph node size for PJI was assessed using receiver operating characteristic curves. Results: The AUC (Area Under the Curve) quantifies the diagnostic method's ability to distinguish between positive and negative outcomes in this study. A value closer to 1.0 indicates better discriminatory performance. Compared to erythrocyte sedimentation rate (Area Under the Curve (AUC) = 0.834), percentage of polymorphonuclear leukocytes (AUC = 0.621), and C-reactive protein (AUC = 0.765), the maximum long axis (AUC =0.895) and maximum short axis (AUC = 0.858) of the external iliac LNs better differentiated PJI from aseptic failure. For diagnosing PJI, the threshold for the maximum long axis of the LNs was 20.5 mm, with a sensitivity of 84.21% and a specificity of 87.84%. For the maximum short axis, the threshold was 8.5 mm, with a sensitivity of 89.47% and a specificity of 82.43%. Combining the maximum long and short axes of the external iliac LNs enhanced the diagnostic accuracy for PJI. Conclusion: Measuring the long and short axes of external iliac LNs using DECT is an effective diagnostic approach for PJI, aiding in the differentiation between PJI and aseptic failure following joint replacement surgery.
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