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Optimizing multimodal diagnostic strategies for periprosthetic joint infection: Current advances and integration
Jianhui Zhai1, Yumei Zhang2, Jinwang Dong3
1Department of Joint Surgery, Honghui Hospital, Xi'an Jiaotong University, Xi'an, China.
Abstract:
Periprosthetic Joint Infection (PJI) represents a significant complication following joint arthroplasty, highlighting the necessity for accurate diagnostic strategies to guide clinical decision-making. This review highlights advancements in PJI diagnostic techniques, including pathogen identification, biomarker profiling, imaging, and molecular biology techniques. Diagnostic accuracy in culture-based pathogen identification is influenced by factors such as sampling method, antibiotic administration, specimen type, incubation period, and type of culture media. Methods such as ultrasonic agitation and chemical dissolution (e.g., dithiothreitol, DTT) have demonstrated potential in improving pathogen identification in biofilms. Moreover, commonly employed biomarkers include C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), α-defensin, D-dimer, and interleukin-6 (IL-6), though each exhibits variable specificity and sensitivity. Imaging techniques such as X-ray, computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography/computed tomography (PET/CT) offer diverse diagnostic capabilities, with PET/CT demonstrating high sensitivity and specificity despite higher costs. Furthermore, molecular biology methods such as Polymerase Chain Reaction (PCR) and next-generation sequencing (NGS) provide rapid and sensitive detection, which is especially valuable in culture-negative and polymicrobial infections. However, financial constraints limit their routine clinical use. Future research should focus on further optimizing diagnostic modality, exploring novel diagnostic techniques (such as machine learning, (ML) analysis and point-of-care, (POC) diagnostics), while integrating multimodal strategies to enhance the accuracy and efficiency of PJI identification.
Insights
Accurate diagnosis of periprosthetic joint infection (PJI) is crucial. This review explores advanced techniques like molecular biology and imaging, aiming to improve pathogen identification and patient outcomes in joint arthroplasty infections.
Area of Science:
- Orthopedics
- Infectious Diseases
- Medical Diagnostics
Background:
- Periprosthetic Joint Infection (PJI) is a major complication of joint arthroplasty.
- Accurate diagnosis is essential for effective clinical management and treatment.
- Current diagnostic methods face challenges in sensitivity and specificity.
Purpose of the Study:
- To review and highlight advancements in Periprosthetic Joint Infection (PJI) diagnostic techniques.
- To discuss the strengths and limitations of various diagnostic modalities.
- To identify future research directions for improved PJI detection.
Main Methods:
- Review of pathogen identification methods (culture-based, biofilm disruption).
- Analysis of biomarker profiling (CRP, ESR, α-defensin, D-dimer, IL-6).
- Evaluation of imaging modalities (X-ray, CT, MRI, PET/CT) and molecular techniques (PCR, NGS).
Main Results:
- Culture-based methods are affected by pre-analytical factors; biofilm disruption techniques show promise.
- Biomarkers have variable diagnostic utility; PET/CT offers high accuracy but is costly.
- Molecular methods (PCR, NGS) provide rapid, sensitive detection, especially for challenging cases, but face cost barriers.
Conclusions:
- Multimodal diagnostic strategies are needed to enhance Periprosthetic Joint Infection (PJI) accuracy.
- Further research into novel techniques like machine learning and point-of-care diagnostics is warranted.
- Optimizing existing methods and integrating new technologies will improve PJI identification and patient care.
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