Cost-Utility of Dalbavancin as a Treatment Option for Adult Patients with Acute Bacterial Skin and Skin Structure Infections (ABSSSI) in Canada
Bibliographic record
Abstract
Background/Objectives: The standard of care for acute bacterial skin and skin structure infections (ABSSSIs) requiring intravenous (IV) antibiotics includes vancomycin, administered over several days, in a hospital or outpatient setting resulting in significant costs. Dalbavancin, a long-acting single-dose lipoglycopeptide IV therapy may offer a cost-effective option for adult patients with ABSSSIs in Canada. Methods: A cost-utility analysis (CUA) was performed to evaluate the potential benefits of dalbavancin compared to other IV antibiotics for the treatment of adult patients with ABSSSIs who require IV antibiotics but whose hospitalization, if necessary, is anticipated to be £ 72 hours. Results: This analysis utilized a decision-analytic model showing that dalbavancin was dominant against all IV antibiotic comparators when considering the healthcare system or societal perspective and was associated with lower costs and improved patient adherence. For the sub-population analysis against PWID (people who inject drugs) and the homeless, dalbavancin generated even greater cost savings. Conclusions: We report that dalbavancin when used to treat ABSSSI requiring IV antibiotics may offer cost savings for Canadian healthcare providers through reduced hospitalization time, lower administration and labor costs, minimized risk of healthcare-acquired infections (HAIs), improved patient compliance and optimized resource allocation particularly in patients at risk of non-compliance (First Nations, the homeless and PWID).
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| 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".