Genomic Insights into Host Susceptibility to Periprosthetic Joint Infections: A Comprehensive Literature Review
Bibliographic record
Abstract
Periprosthetic joint infection (PJI) is a multifactorial disease, and the risk of contracting infection is determined by the complex interplays between environmental and host-related factors. While research has shown that certain individuals may have a genetic predisposition for PJI, the existing literature is scarce, and the heterogeneity in the assessed genes limits its clinical applicability. Our review on genetic susceptibility for PJI has the following two objectives: (1) Explore the potential risk of developing PJI based on specific genetic polymorphisms or allelic variations; and (2) Characterize the regulatory cascades involved in the risk of developing PJI. This review focused on clinical studies investigating the association between genetic mutations or variations with the development of PJI. The genes investigated in these studies included toll-like receptors and humoral pattern recognition molecules, cytokines, chemokines, mannose-binding lectin (MBL), bone metabolism molecules, and human leukocyte antigen. Among these genes, polymorphisms in IL-1, MBL, vitamin D receptors, HLA-C, and HLA-DQ might have a relevant impact on the development of PJI. The literature surrounding this topic is limited, but emerging transcriptomic and genome-wide association studies hold promise for identifying at-risk genes. This advancement could pave the way for incorporating genetic testing into preoperative risk stratification, enhancing personalized patient care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.006 |
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 teacher head, 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".