304. Comparison of Short and Long Courses of Antibiotics in Patients with Prosthetic Joint Infection: A Systemic Review and Meta-analysis
Bibliographic record
Abstract
Current guidelines for treatment of prosthetic joint infection (PJI) suggest a combination of intravenous (IV) antibiotics for 2–6 weeks and oral antibiotics for 3–6 months. However, recent studies did not find significant benefits from prolonged use of antibiotics for patients with PJI. We conducted a systemic review and meta-analysis to assess the outcomes of short- and long-term antibiotics in patients with PJI. We designed three queries to retrieve literature of PJI from PubMed and Embase databases until December 2017. Each query comprised medical subject headings, title/abstract keywords, and exclusion terms. Two reviewers independently screened literature for three rounds and disagreements were resolved by a third reviewer. Quality of a cohort study and that of a randomized control trial (RCT) were assessed by Newcastle-Ottawa Quality Assessment Form and a modified Jadad scale respectively. A total of 3,309 studies were retrieved, and nine observation studies and one RCT were included for final analysis (Figure 1). Nine of the 10 studies investigated total hip arthroplasty and/or total knee arthropathy, while one study further included shoulder, elbow, and ankle arthroplasty. Five studies focused on patients receiving debridement and implant retention (DAIR) procedure, three studies on staged exchange arthroplasty (SEA), and two studies on mixed procedures. Eight of the 10 studies were graded as good or fair quality. All of the 10 studies found equivalent outcomes in patients prescribed with short- and long-term antibiotics, regardless of IV or oral form of antibiotics. The aggregate odds ratio (OR) in our meta-analysis was 1.04 (95% CI, 0.70, 1.55), showing no significant difference in outcomes between short-term and long-term antibiotics (Figure 2). Our meta-analysis demonstrated that patients prescribed with short-term antibiotics for PJI had similar outcomes when compared with those prescribed with long-term antibiotics. All authors: No reported disclosures.
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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 | 0.019 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.044 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".