The AO Trauma CPP Bone Infection Registry: epidemiology and outcomes on Staphylococcus aureus infection in long bones and joints
Bibliographic record
Abstract
Abstract Background Bone infection is a serious complication associated with orthopedic surgery, and Staphylococcus aureus (S. aureus) is a common pathogen. As the optimal treatment requires an understanding of the patient-specific host-pathogen interaction, we developed a biospecimen registry (the AO Trauma CPP Bone Infection Registry) to collect clinical data, bacterial isolates, and serum from patients treated for bone infection caused by S. aureus. MethodsA prospective multicenter multicontinental registry with a follow-up period of 12 months was set up to include adult patients (18 years or older) with culture-confirmed S. aureus infection in long bones after fracture fixation or arthroplasty. Baseline patient attributes and details on infections and treatments were recorded. Blood and serum samples were taken at baseline, 6, and 12 months. Patient outcomes were assessed with the Short Form-36, Parker Mobility Score, and Katz Activities of Daily Living at baseline, 1, 6, and 12 months. Complications, re-hospitalization, and outcomes were recorded. Aside from descriptive summary analyses, changes from baseline were analyzed using the mixed-effects model and Wilcoxon sign rank test. Analyses using full analysis population and per protocol population were performed, and when appropriate, additional sensitivity analyses. This study was registered in ClinicalTrials.gov: NCT01677000.ResultsTwo hundred and ninety-two patients with infections originating from fracture fixation (n=157, 53.8%), prosthetic joint infection (n=86, 29.5%), and osteomyelitis (n= 49, 16.8%) were enrolled (Table 1). Methicillin resistant S. aureus was detected in 82 patients (28.4%), with the highest proportion found among patients from North American sites (n=39, 48.8%) and the lowest from Central European sites (n=18, 12.2%). Patient outcomes had improved statistically significant at 6 and 12 months in comparison to baseline. The SF-36 Physical Component Summary mean (95% CI) score, however, did not reach 50, at 12 months. The cure rate at the end of the study period was 62.1%.ConclusionThe AO Trauma CPP Bone Infection Registry provides unique insights into the epidemiology and outcomes of S. aureus long-bone infections. It also contains annotated biospecimens for future research.Although patients' health status improved after treatment, less than two-thirds were cured at one year.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".