Prevalence and Incidence of Hepatitis C Virus in Hemodialysis Patients in British Columbia: Follow‐up after a Possible Breach in Hemodialysis Machines
Bibliographic record
Abstract
BACKGROUND: A possible breach of the transducer protector in specific dialysis machines was reported in June 2004 in British Columbia (BC), which led to testing of hemodialysis patients for hepatitis C virus (HCV), hepatitis B virus (HBV) and HIV. This testing provided an opportunity to examine HCV incidence, prevalence and coinfection with HBV and HIV, and to compare anti-HCV and HCV polymerase chain reaction (PCR). METHODS: The results of hemodialysis patients who were dialyzed on the implicated machines (65% of BC dialysis patients), and tested for HCV, HBV and HIV, between June 1, 2004, and December 31, 2004, were reviewed and compared with available previous results. RESULTS: Of 1286 hemodialysis patients with anti-HCV and/or HCV-PCR testing, 69 (5.4%) tested positive. Two HCV genotype 4 seroconversions were identified. HCV incidence rate on dialysis was 78.8 cases per 100,000 person-years. Younger age, history of renal transplant and past HBV infection were associated with HCV infection. No occult infection was identified using HCV-PCR. INTERPRETATION: Hemodialysis patients had three times the HCV prevalence rate of the general BC population, and more than 20 times the incident rate of the general Canadian population. One of the two seroconversions occurred before the testing campaign; the patient was likely infected during hemodialysis in South Asia. The other was plausibly a late seroconversion following renal transplant in South Asia. Nosocomial transmission cannot be ruled out because both patients were dialyzed in the same centre. Baseline and annual anti-HCV testing is recommended. HCV-PCR should be considered at baseline for persons with HCV risk factors, and for returning travellers who received dialysis in HCV-endemic countries to identify HCV infection occurring outside the hemodialysis unit.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".