Hepatitis C Contamination of Medication Vials Accessed with Sterile Needles and Syringes
Bibliographic record
Abstract
BACKGROUND: Health care-associated hepatitis C virus outbreaks from contaminated medication vials continue to be reported even though most practitioners deny reusing needles or syringes. The hypothesis was that when caring for hepatitis C virus-infected patients, healthcare providers may inadvertently contaminate the medication vial diaphragm and that subsequent access with sterile needles and syringes can transfer hepatitis C virus into the medication, where it remains stable in sufficient quantities to infect subsequent patients. METHODS: A parallel-arm lab study (n = 9) was performed in which contamination of medication vials in healthcare settings was simulated using cell culture-derived hepatitis C virus. First, surface-contaminated vials were accessed with sterile needles and syringes, and then hepatitis C virus contamination was assessed in cell culture. Second, after contaminating several medications with hepatitis C virus, viral infectivity over time was assessed. Last, surface-contaminated vial diaphragms were disinfected with 70% isopropyl alcohol to determine whether disinfection of the vial surface was sufficient to eliminate hepatitis C virus infectivity. RESULTS: Contamination of medication vials with hepatitis C virus and subsequent access with sterile needles and syringes resulted in contamination of the vial contents in sufficient quantities to initiate an infection in cell culture. Hepatitis C virus remained viable for several days in several commonly used medications. Finally, a single or 2- to 3-s wipe of the vial diaphragm with 70% isopropyl alcohol was not sufficient to eliminate hepatitis C virus infectivity. CONCLUSIONS: Hepatitis C virus can be transferred into commonly used medications when using sterile single-use needles and syringes where it remains viable for several days. Furthermore, cleaning the vial diaphragm with 70% isopropyl alcohol is not sufficient to eliminate the risk of hepatitis C virus infectivity. This highlights the potential risks associated with sharing medications between patients.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".