Are Preformed Articulating Spacers Superior To Surgeon-Made Articulating Spacers in the Treatment Of PJI in THA? A Literature Review
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Antibiotic-loaded cement spacers are typically manufactured by surgeons in the operating room. However, if the infecting organism is known preoperatively, the cement spacer can be fabricated (Spacer-G(®) or the InterSpace(®) Hip) in advance. It is unclear if preformed hip spacers are superior to surgeon-made hip spacers in the treatment of periprosthetic joint infection following primary THA. METHODS: A literature review of the peer-reviewed literature indexed by MEDLINE and Embase was performed to identify studies reporting the outcomes of preformed and surgeon-made hip spacers in the treatment of infection following primary total hip arthroplasty (THA). A total of 43 articles met the inclusion criteria and were included in the analysis to compare the reinfection rate, Harris Hip Score (HHS) and spacer complication rates between surgeon-made and preformed hip spacers. RESULTS AND INTERPRETATION: The analyzed studies included a total number of 1631 infected THA cases (n=1027 surgeonmade; n=604 preformed spacers). We found similar reinfection rates (6.0% surgeon-made, and 5.5% preformed spacers) and similar mean HHS at latest follow-up after reimplantation (HHS=84.3 surgeon-made, and HHS=81.8 preformed spacers) between both groups. However, patients treated with a surgeon-made articulating spacer had a higher spacer fracture rate compared to preformed articulating spacer. The use of preformed articulating spacers in the treatment of infected THA is not superior to surgeon-made articulating spacers regarding infection control and functional outcomes. However, the use of surgeon-made antibiotic spacers increased the risk of spacer fracture.
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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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.010 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".