Are infection specialists recommending short antibiotic treatment durations? An ESCMID international cross-sectional survey
Bibliographic record
Abstract
Objectives: To evaluate the current practice and the willingness to shorten the duration of antibiotic therapy among infection specialists. Methods: Infection specialists giving at least weekly advice on antibiotic prescriptions were invited to participate in an online cross-sectional survey between September and December 2016. The questionnaire included 15 clinical vignettes corresponding to common clinical cases with favourable outcomes; part A asked about the antibiotic treatment duration they would usually advise to prescribers and part B asked about the shortest duration they were willing to recommend. Results: We included 866 participants, mostly clinical microbiologists (22.8%, 197/863) or infectious diseases specialists (58.7%, 507/863), members of an antibiotic stewardship team in 73% (624/854) of the cases, coming from 58 countries on all continents. Thirty-six percent of participants (271/749) already advised short durations of antibiotic therapy (compared with the literature) to prescribers for more than half of the vignettes and 47% (312/662) chose shorter durations in part B compared with part A for more than half of the vignettes. Twenty-two percent (192/861) of the participants declared that their regional/national guidelines expressed durations of antibiotic therapy for a specific clinical situation as a fixed duration as opposed to a range and in the multivariable analysis this was associated with respondents advising short durations for more than half of the vignettes (adjusted OR 1.5, P = 0.02). Conclusions: The majority of infection specialists currently do not advise the shortest possible duration of antibiotic therapy to prescribers. Promoting short durations among these experts is urgently needed.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".