ArticleCureus2022
Physician Use of Multiple Criteria to Diagnose Periprosthetic Joint Infection May Be Less Accurate Than the Use of an Individual Test.
Article in Cureus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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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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Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- Machine Learning-Driven Probability Scoring Enhances Diagnostic Certainty and Reduces Costs in Suspected Periprosthetic Joint Infection.Diagnostics (Basel, Switzerland) · 2026Article
- The Application of artificial intelligence in periprosthetic joint infection.Journal of advanced research · 2026Review
- Criteria-Based Periprosthetic Joint Infection Definitions: Understanding the Disconnect Between Research and Practice.Arthroplasty today · 2025Article
- Article
- Discrepancies in Periprosthetic Joint Infection Diagnostic Criteria Reporting and Use: A Scoping Review and Call for a Standard Reporting Framework.Clinical orthopaedics and related research · 2025Article
- Profiling the Immune Response to Periprosthetic Joint Infection and Non-Infectious Arthroplasty Failure.Antibiotics (Basel, Switzerland) · 2023Review
Corrections and comments
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction Multiple-criterion scoring systems for periprosthetic joint infection (PJI) can be algorithmically implemented in research, diagnostically outperforming individual tests. This improved performance may be lost in the practice setting, where clinicians rarely utilize strict algorithms. The ability of physicians to interpret multiple criteria for PJI and confront the complexity of combining them into a final diagnosis has never been studied. This study assessed the diagnostic characteristics of physicians using multiple criteria to diagnose PJI and compared the physicians' diagnostic accuracy to that of individual tests. Methods A total of 12 physicians, including academic arthroplasty surgeons (N=4), community arthroplasty surgeons (N=4), and infectious disease (ID) specialists (N=4) were asked to use their routine clinical diagnostic practice to assign a diagnosis to 277 clinical vignettes using multiple preoperative laboratory criteria for PJI. The undecided rate, interobserver agreement, and accuracy of physicians were characterized relative to the 2013 Musculoskeletal Infection Society (MSIS) gold standard and compared to the accuracy of each individual laboratory test for PJI. Results Physicians interpreting multiple criteria for PJI demonstrated high undecided diagnosis rates (mean=23.5%), poor interobserver agreement (kappa range=0.49-0.63), and mean accuracy of 90.8% (range:85.8%-97.4%) compared to the 2013 MSIS gold standard. The group of academic arthroplasty surgeons had a lower rate of undecided diagnoses than community arthroplasty surgeons (16.2% vs. 29.1%; p<0.0001) or ID specialists (16.2% vs. 25.1%; p<0.0001). Academic arthroplasty surgeons also exhibited a higher interobserver agreement than community arthroplasty surgeons (kappa = 0.63 (95%CI:0.59-0.68) vs. 0.49 (95%CI:0.44-0.54)). Mean physician accuracy (90.8%) was inferior to the alpha-defensin laboratory test (96.0%;p=0.0034) and the alpha-defensin lateral-flow test (94.6%;p=0.036), comparable to synovial fluid white blood cells (SF-WBC) (93.3%;p=0.17) and synovial fluid polymorphonuclear cell % (SF-PMN%) (94.0%;p=0.11), and superior to the erythrocyte sedimentation rate (ESR) (86.2%;p<0.0001) and C-reactive protein (CRP) (84.6%;p<0.0001). Only two academic arthroplasty surgeons in this study were able to outperform every individual test for PJI by combining multiple criteria to make a diagnosis. Conclusion Although multiple-criterion scoring systems may outperform individual tests for diagnosing PJI in the research setting, it appears that the complexity of using multiple tests to diagnose PJI causes indecision and variability among physicians. Physician use of multiple preoperative criteria to diagnose PJI is less accurate than the strict algorithmic calculation of the diagnosis as achieved in research. In fact, most physicians in this study would have improved their diagnostic accuracy for PJI by simply utilizing a single good test to make the diagnosis, instead of trying to combine multiple tests into a decision. We propose that less complex diagnostic criteria should be explored for routine clinical utilization.
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