Clinical use of linezolid in periprosthetic joint infections – a systematic review
Bibliographic record
Abstract
Abstract. Introduction: The most common causative organism in periprosthetic joint infections (PJIs) is Gram-positive bacteria that are increasingly drug resistant. In these cases the use of linezolid may be warranted. However, there are conflicting reports regarding its role in antibiotic treatment of PJIs. The aim of this review is to gather and analyze clinical results and treatment details on linezolid in patients with PJIs. Methods: In August 2019, a comprehensive literature search using MEDLINE (Pubmed and Ovid) and Cochrane Library was performed. A total of 504 records were screened, and a total of 16 studies including 372 patients treated with linezolid for a PJI were included in this review based on the PRISMA criteria and after quality analysis using the MINOR score and Newcastle–Ottawa scale, as well as assessing level of evidence. Pooling analysis as well as descriptive analysis was performed. Results: Based on the results from the studies included, infection control was achieved in 80 % (range 30 %–100 %) of patients after a mean follow-up period of 25 (range 2–66) months. The mean duration of treatment was 58 d intravenous and orally at a median dose of 600 mg bis in die (b.i.d.) (range 400–900 b.i.d.). A combination therapy with rifampicin was used in 53 % of patients. MRSA (methicillin-resistant Staphylococcus aureus) infections were present in 29 % and resistant CoNS (coagulase-negative Staphylococcus) in 46 %. Adverse effects occurred in 33 % of cases, mostly anemia, thrombocytopenia and gastrointestinal complaints leading to treatment discontinuation in 9 %. However, great heterogeneity was found with respect to surgical treatment, diagnosis of infection and indication for linezolid. Discussion: Linezolid is an appropriate option for treatment of resistant Gram-positive organisms in PJIs. Most commonly 600 mg b.i.d. is used, and a combination with rifampicin appears feasible although one must consider individual increases in doses in these cases. However, adverse effects are common and there are limited data for long-term use and optimal antibiotic combinations or individual doses.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".