Functional Outcomes of Infected Hip Arthroplasty: A Comparison of Different Surgical Treatment Options
Bibliographic record
Abstract
BACKGROUND: Periprosthetic joint infection (PJI) following total hip arthroplasty (THA) can be treated with irrigation and debridement with head and polyethylene exchange (IDHPE) or 2-stage revision (2SR). Few studies have compared patient-reported outcome measures (PROMs) in patients managed with these treatments. METHODS: A retrospective review identified 137 patients who had an infected primary THA between 1986-2013. Control cohorts were matched according to age and Charlton Comorbidity Index (CCI). Harris Hip Scores (HHS), Short Form 12 (SF12), and Western Ontario and McMaster Universities Arthritis Index (WOMAC) scores were compared between the control and infected cohorts. RESULTS: 68 patients underwent a 2SR and 69 patients underwent an IDHPE. IDHPE had a 59% success rate in eradicating infection. PROMs for the 2SR cohort were significantly worse than the noninfected controls (SF12-PCS [34.0 vs. 38.3, p = 0.03]; HHS [76.6 vs. 91.7, p<0.001]; and WOMAC [67.3 vs. 79.3, p = 0.005]). There were no significant differences between the noninfected cohort and the successful IDHPE. Significant differences were found between failed IDHPE and noninfected controls (SF12-PCS [42.5 vs. 34.0, p = 0.011]; HHS [92.3 vs. 79.6, p = 0.004]). There was only difference in SF12-MCS scores (50.3 vs. 57.3, p = 0.012) between the 2SR and failed IDHPE cohorts. CONCLUSIONS: Patients treated with a successful IDHPE had similar outcomes to noninfected patients. Patients that failed IDHPE and went onto 2SR had similar outcomes to those that had a 2SR alone. IDHPE demonstrated a 59% success rate with PROMs equivalent to a noninfected cohort and should be considered in the treatment algorithm of infected THA.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".