An outbreak of hepatitis C virus attributed to the use of multi-dose vials at a colonoscopy clinic, Waterloo Region, Ontario
Bibliographic record
Abstract
BACKGROUND: Hepatitis C virus (HCV) transmission has been epidemiologically linked to healthcare settings, particularly out-of-hospital settings such as endoscopy clinics and hemodialysis clinics. These have been largely attributed to lapses in infection prevention and control practices (IPAC). OBJECTIVE: To describe the public health response to an outbreak of HCV that was detected among patients of a colonoscopy clinic in Ontario, and to highlight the risks of using multi-dose vials and the need for improved IPAC practices in out-of-hospital settings. METHODS: Screening for HCV was conducted on patients and staff who attended or worked at the clinic within the same timeframe as the index case's procedure. Blood samples from positive cases underwent viral sequencing. Inspections of the clinic assessed IPAC practices, and a chart review was done to identify plausible mechanisms for transmission. OUTCOME: A total of 38% of patients who underwent procedures at the clinic on the same day as the index case tested positive for HCV. Genetic sequencing showed a high degree of similarity in the HCV genetic sequence among the samples positive for HCV. Chart review and clinic inspection identified use of multi-dose vials of anesthesia medication across multiple patients as the plausible mechanism for transmission. CONCLUSION: Healthcare workers, especially those in out-of-hospital procedural/surgical premises, should be vigilant in following IPAC best practices, including those related to the use of multi-dose vials, to prevent the transmission of bloodborne infections in healthcare settings.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".