Real-life experience with IV fosfomycin in Canada: Results from the Canadian LEadership on Antimicrobial Real-life usage (CLEAR) registry
Bibliographic record
Abstract
OBJECTIVES: Data on the use of intravenous (IV) fosfomycin in Canada are limited. Using data captured by the Canadian LEadership on Antimicrobial Real-life usage (CLEAR) registry, we report the use of IV fosfomycin in Canadian patients. METHODS: (https://rcsurvey.radyfhs.umanitoba.ca/surveys/?s=F7JXNDFXEF) to facilitate clinicians' entering of details associated with their clinical experiences using IV fosfomycin. RESULTS: Data were available for 59 patients treated with IV fosfomycin. The most common infections treated were: bacteraemia or sepsis (25.4% of patients), complicated urinary tract infection (20.3%), ventilator-associated bacterial pneumonia (18.6%), and hospital-acquired pneumonia (13.6%). IV fosfomycin was used to treat Gram-negative (88.1%) and Gram-positive (10.2%) infections. The most common pathogens treated were carbapenem-resistant Enterobacterales (44.1%), multidrug-resistant Pseudomonas aeruginosa (18.6%), vancomycin-resistant Enterococcus faecium (5.1%), and methicillin-resistant Staphylococcus aureus (3.4%). IV fosfomycin was primarily used due to resistance to initially prescribed therapies (69.5%), frequently in combination with other agents (86.4%). Microbiological success (eradication/presumed eradication) occurred in 77.4% of patients, and clinical success (clinical cure/improvement) occurred in 62.5%. Overall, 15.3% of patients died because of their infection. Adverse effects were not documented in 73.1% of patients, and no patient discontinued therapy because of an adverse effect. CONCLUSIONS: In Canada, IV fosfomycin is used primarily as directed therapy to treat a variety of severe infections caused by Gram-negative and Gram-positive bacteria. It is primarily used in patients infected with bacteria resistant to other agents and as part of combination therapy. Its use is associated with relatively high microbiological and clinical cure rates, and it has an excellent safety profile.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".