Patient-Reported Outcome on Quality of Life and Pain after Revision Arthroplasty for Periprosthetic Joint Infection: A Cross-Sectional Study
Bibliographic record
Abstract
This study aims to explore the quality of life (QOL) and pain after revision surgery for periprosthetic joint infection (PJI) based on patients’ reported outcomes. A cross-sectional questionnaire survey was conducted and 137 valid responses were included (response rate 64.0%). A total of 42 patients underwent debridement with implant retention (DAIR), 31 underwent one-stage revision, and 64 underwent two-stage revision. The average overall SF-36 score was 70.3. The DAIR group had significantly higher SF-36 than the two-stage revision group (p = 0.01). There was no significant difference between the one-stage revision group and the other two groups. A total of 74.5% of patients reported pain with an average McGill Pain Questionnaire (MPQ) score of 8.6. There was no significant difference in the MPQ scores among the three groups. Simple linear regression analyses demonstrated that higher preoperative PMN%, VAS, and shorter hospital stay were associated with pain (adjusted R2 = 4%, p = 0.020; adjusted R2 = 2.1%, p = 0.048; adjusted R2 = 2.1%, p = 0.049; respectively). We concluded that the overall QOL of patients after revision surgery for PJI is generally satisfactory. Persistent pain is prevalent, but the severity was mostly mild. Preoperative PMN%, VAS, and hospital stay were associated with postoperative pain.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".