Dual‐ vs. Single‐Antibiotic Loaded Cement for Hip Hemiarthroplasty: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
ABSTRACT Background Antibiotic‐loaded cement (ALC) is often used to reduce the risk of surgical site infections (SSIs) in hip hemiarthroplasty; however, controversy exists regarding the use of dual antibiotic‐loaded cement (DALC) and single antibiotic‐loaded cement (SALC). Objective This systematic review and meta‐analysis compare the efficacy of DALC and SALC for hip hemiarthroplasty. Methods For this systematic review, a search was undertaken in the Cochrane Central Register of Controlled Trials, MEDLINE, Embase, and ClinicalTrials.gov. Grey literature such as ProQuest Dissertations and Theses Global (PQDT) was also explored. The inclusion criteria comprised randomized controlled trials (RCTs) or comparative observational studies, and patients undergoing hip hemiarthroplasty with DALC or SALC. Newcastle–Ottawa Scale (NOS) and RoB 2.0 tools were used for risk of bias assessment in observational and RCTs, respectively. Review Manager (RevMan, version 5.4.1; The Cochrane Collaboration, Copenhagen, Denmark) was used for statistical analysis. The primary outcome was the incidence of deep SSIs. Results A total of five articles, including 28,418 participants, met the inclusion criteria. Three of the included studies were retrospective studies, one quasi‐randomized study, and one RCT. The primary outcome revealed that DALC was associated with a statistically significant reduction in deep SSIs compared to SALC (RR, 0.47; 95% CI, 0.29–0.76; p = 0.002; I 2 = 27%). Subgroup analysis based on the study design did not show a significant difference for deep SSIs (p = 0.29). The majority of the secondary outcomes, such as superficial SSIs, mortality, participants with ≥ 1 complication, or antibiotic use, did not show any significant difference. However, DALC significantly lowered the risk of any infection (RR, 0.55; 95% CI, 0.38–0.79; p = 0.001; I 2 = 27%). Conclusion In conclusion, DALC can significantly reduce the risk of SSIs and the overall rate of any infection in hip hemiarthroplasty. A limitation of this study is that RCTs were pooled with observational studies, which decreased the power of analysis. Therefore, further research, including large RCTs, is needed to validate these findings.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.034 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".