Periprosthetic joint infections after total hip replacement: an algorithmic approach
Why this work is in the frame
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Bibliographic record
Abstract
An algorithm for managing periprosthetic joint infections (PJIs) after total hip replacement (THR) surgery using a multidisciplinary approach and a clearly defined protocol may improve infection eradication rates. In this article, we present an algorithm for the management of different types of PJIs including the acutely infected cemented and cementless THRs where the components are well-fixed postoperatively and when the infection is secondary to haematogenous spread in previously well-functioning and well-fixed implants. For chronic PJIs where the components are often loose, the standard treatment includes a two-stage revision procedure. However, in a highly selected subset of patients, a single-stage approach has been utilised with high rates of eradicating infections.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 it