Retinal vein thrombosis associated with pegylated-interferon and ribavirin combination therapy for chronic hepatitis C
Bibliographic record
Abstract
An estimated 300 million people worldwide suffer from chronic hepatitis C with a prevalence of 0.8%-1.0% of the general population in Canada. An increasing pool of evidence exists supporting the use of pegylated- interferon (pegIFN) and ribavirin combination therapy for hepatitis C. We report a 49-year old male of North American aboriginal descent with chronic hepatitis C (genotype 2b). Biopsy confirmed that he had cirrhosis with a 2-wk history of left eye pain and decreased visual acuity. He developed retinal vein thrombosis after 16 of 24 wk of pegIFN-alpha 2a and ribavirin combination therapy. He was urgently referred to a retinal specialist and diagnosed with non-ischemic central retinal vein occlusion of the left eye. PegIFN and ribavirin combination therapy was discontinued and HCV RNA was undetectable after 16 wk of treatment. Hematologic investigations revealed that the patient was a factor V Leiden heterozygote with mildly decreased protein C activity. Our patient had a number of hypercoagulable risk factors, including factor V Leiden heterozygosity, cirrhosis, and hepatitis C that alone would have most likely remained clinically silent. We speculate that in the setting of pegIFN treatment, these risk factors may coalesce and cause the retinal vein thrombosis.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".