Off-label use of dalbavancin to improve treatment outcomes and reduce health care costs in people who use drugs: A Canadian single-centre quality improvement initiative
Bibliographic record
Abstract
Background: Dalbavancin is approved in Canada for the treatment of acute bacterial skin and skin structure infections (ABSSSIs). We present a single-centre quality improvement case series of dalbavancin use in serious bacterial infections in people who use drugs (PWUD). Our goal was to facilitate access to dalbavancin to improve treatment outcomes and identify potential health system savings. Methods: We established an unrestricted, hospital-specific, rapid-access compassionate provision program for dalbavancin. Patients were considered for treatment with dalbavancin at the discretion of an infectious diseases physician if they had serious gram-positive infections. Patients provided informed verbal consent. Data were collected via retrospective chart review. We compared costs savings using a practitioner modifiable cost calculator developed by Paladin Labs Inc. Results: Between September 2022 and November 2023, seven patients received dalbavancin. The most common indications for use included early discharge from hospital and improved treatment adherence. Three patients were considered to have infection cure at last follow-up, three patients were presumed to have infection cure but were lost to follow-up, and one patient had infection relapse. Two patients died from causes unrelated to the dalbavancin-treated condition. There were no reported adverse events. Dalbavancin resulted in cost savings compared with standard-of-care (SoC) treatment, and this was primarily driven by reduced inpatient hospital days. Conclusions: Dalbavancin may improve treatment adherence and outcomes for PWUD with serious gram-positive infections while saving health care costs by facilitating earlier discharge from hospital. Our preliminary experience highlights the need for additional controlled studies to evaluate expanded indications for dalbavancin as well as innovative approaches to increase access to novel antimicrobial agents in a single-payer health care system such as Canada.
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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 | 0.015 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".