CLINICAL OUTCOME AFTER INFECTED TOTAL KNEE AND TOTAL HIP ARTHROPLASTY
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Infection after total hip (THA) and knee arthroplasty (TKA) is a serious complication which typically leads to a long lasting and intensive surgical and medicamentous treatment. The aim of this study was to identify factors that influence outcome after revision surgery caused by prosthetic infection. METHODS: We retrospectively analyzed 64 patients who had revision surgery between 1989 and 2009 due to periprosthetic infection. We examined a total of 69 joints (TKA: 36%, THA: 64%), follow-up 5.1 years (0.5-21 years) after the initial surgical intervention. The mean patient age at time of surgery was 67 years old (43-79 years old). Clinical data and scores including the Western Ontario and McMaster Universities (WOMAC)-Index, the Harris Hip Score (HHS) and the Hospital for Special Surgery Score (HSS) were surveyed. RESULTS: There was no difference in clinical scores regarding treatment between a single and a multiple stage treatment regime. Infections with multiple microorganisms and Enterococcus spp. lead to a significantly higher number of interventions. Using a modified Tsukayama system we classified 24% as type I, 34% type II and 42% type III- infections, with no differences in clinical outcome. Overweight patients had a significantly lower HHS and WOMAC-score. Immunosuppression leads to a worse WOMAC and HSS-Score. An increased number of procedures was associated to a limping gait. CONCLUSION: Thorough surgical technique leads to good clinical results independent of infection-type and treatment philosophy. Level of Evidence III, Case Control Study.
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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 | 0.000 |
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 it