A protocol for a systematic review of the diagnostic accuracy of blood markers, synovial fluid, and tissue testing in periprosthetic joint infections (PJI)
Bibliographic record
Abstract
BACKGROUND: Total joint replacement (TJR) procedures have been one of the most rewarding interventions for treating patients suffering from joint disease. However, developing a periprosthetic joint infection (PJI) is a serious complication that is associated with the highest burden of cost and reduction in patients' quality of life compared to other complications following TJRs. One of the main challenges facing clinicians who are treating PJIs is accurately diagnosing infection in a timely fashion. Multiple orthopedic associations have published clinical guidelines for diagnosing PJI which are based solely on consensus approaches, expert opinions, and narrative reviews. We believe that a higher quality of scientific rigor is necessary to establish a diagnostic guideline that represents current evidence more accurately and that identifies important knowledge gaps in PJI diagnosis. Therefore, we will conduct a systematic review on diagnostic performance of blood markers, synovial fluids, and tissue tests for diagnosing PJI. METHODS/DESIGN: Electronic search strategies will be developed and tested by an experienced medical information specialist in consultation with the review team, and gray literature will be searched using the checklist from CADTH's Grey Matters Light. Two reviewers will independently screen the literature for inclusion using the prespecified eligibility criteria. Non-English language and animal-only studies will be excluded. Quality assessment and data extractions by reviewers will be verified, and disagreements will be resolved through consensus or third party adjudication. We will assess the quality of individual studies using the QUADAS-2 tool and use GRADE to summarize the strength of body of evidence. Analyses of evidence will be conducted in accordance with the Cochrane Handbook for Diagnostic Test Accuracy Reviews. DISCUSSION: We will conduct a systemic review of tests (blood markers, synovial fluids, and tissue testing) for diagnosing PJI in patients' knee, hip, and shoulder joint replacements. This will be the first scientifically rigorous and comprehensive systematic review in the field and may feed into an evidence-based clinical practice guideline. We will compare the findings of this review with the consensus-based guides and discuss the differences, similarities, and knowledge gaps. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42015023768.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.133 | 0.196 |
| Meta-epidemiology (narrow) | 0.005 | 0.005 |
| Meta-epidemiology (broad) | 0.013 | 0.012 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.110 | 0.016 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".