Phage therapy: An international survey of attitudes and experiences amongst clinicians
Bibliographic record
Abstract
OBJECTIVE: Phage therapy is a promising tool to combat the global threat of antimicrobial resistance. Clinicians, as part of interdisciplinary teams, play an integral role in identifying patients for therapy, delivering phages, and monitoring treatment outcomes and safety. As such, in the context of rapidly evolving regulatory landscapes, clinician insight is crucial for advancement of phage therapy. In this study, we describe the first published international anonymized survey aimed at identifying attitudes and experiences of clinicians and healthcare professionals towards phage therapy. METHODS: We distributed the survey to participants in the Global Clinical Phage Rounds, a network of >300 phage clinicians, health professionals, and scientists, from October 15, 2024 - January 30, 2025. RESULTS: Thirty respondents representing North America, Europe, Oceania, Africa, and Asia completed the survey (response rate 9.6%). The majority of respondents were very well-informed about phage therapy and 93% would consider enrolling their patients in phage therapy randomized controlled trials. Respondents identified Pseudomonas aeruginosa, Klebsiella species, and Staphylococcus aureus as priority organisms and bone/joint, respiratory, and urinary tract infections as priority syndromes. Respondents had concerns about clinical use evidence, regulatory barriers, and accessing phage. Twenty respondents reported experience with phage therapy, so answered additional questions. These respondents acquired phages from sources like phage banks, industry, and importation from other countries. Respondents delivered phage therapy primarily in single-use cases via parenteral/intravenous, topical, or inhalation routes. Experienced respondents endorsed combinations of monitoring before, during, and/or after phage therapy. CONCLUSIONS: These results serve as a guiding initiative to improve phage therapy integration in healthcare.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".