Use of dalbavancin in treatment of acute bacterial skin and skin structure infections: Case series from a Canadian perspective
Bibliographic record
Abstract
Introduction: Treatment of acute bacterial skin and skin structure infections (ABSSSIs) with intravenous (IV) antibiotics is difficult in marginalized populations, such as people who inject drugs, due to issues such as unstable housing or mental health conditions. These factors often require extended hospital admissions for IV antibiotics. Dalbavancin, a novel lipoglycopeptide antibiotic effective against gram-positive bacteria, lasts over 14 days and may be suitable for patients who struggle with traditional IV antibiotic administration. Methods: This was a case series in which we reviewed 19 patients referred to our cellulitis clinic in London, Ontario, Canada, between February 1 and July 30, 2023, who received a single dose of IV dalbavancin for ABSSSIs as out-patients. Those who were enrolled had severe infections requiring IV antibiotics, with psychosocial factors pre-cluding out-patient IV therapy, or were at high risk of non-adherence to oral antibiotics. Results: The median age of patients was 43 (range 36-56 years); they were mostly male (74%), unemployed (89%), and with unstable housing (58%). Positive outcomes were observed in 13 out of 19 (68%) patients; 3 out of 19 had indeterminate outcomes (could not be reached for follow-up but were not admitted to any institution within our catchment area) and 3 out of 19 had negative outcomes (needed further antibiotics following dalbavancin). Conclusion: Our experience shows that a single IV dose of dalbavancin is effective in treating ABSSSIs in patients with complex psychosocial factors, as positive outcomes were observed in most patients. Dalbavancin eliminates the need for indwelling IV access and may reduce hospital admissions for patients for whom traditional antibiotic regimens may be challenging.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".