¿Es menor el riesgo de falla aséptica en reemplazos primarios de cadera cuando se utiliza cemento con antibiótico? Revisión sistemática de la bibliografía
Bibliographic record
Abstract
Background: The use of antibiotic cement has been shown to decrease the risk of periprosthetic hip infection. However, the long term effect of adding antibiotic to the bone cement continues being a controversial issue because of the possible change in its mechanical properties. The objective of this study is to identify the risk of long-term aseptic failure, with the use of antibiotic cement in primary hip arthroplasties.Materials and methods: A systematic literature search in Medline, Embase and Cochrane data was performed studies evaluating long-term (≥10 years) risk of aseptic failure total primary hip replacement cemented with or without antibiotic were included. The methodological study assessment was performed using the Newcastle-Ottawa scale and Jadad.Results: 5286 titles were identified. Four items were included in the analysis: 1 clinical trial of low quality and 3 prospective cohort of high quality. In the clinical trial, no differences in the risk of aseptical failure using antibiotic cement and regular cement (p = 0.14) were found. Unlike, the three cohorts consistently demonstrated a statistically significant reduction (p < 0.001) relative risk of aseptic failure at 10 years, with the use of antibiotic cement.Discussion: The use of antibiotic cementfor hip arthroplasties fixation exerts a protective effect and reduces the relative risk of long-term aseptic failure.Level of clinical evidence: II.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.021 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.008 |
| Bibliometrics | 0.031 | 0.024 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".