Retrospective Study of Hepatitis C Virus Genotypes and its Association with Lymphoma
Bibliographic record
Abstract
Hepatitis C virus (HCV) involves both the liver and extra hepatic organs. The aim of this study was to retrospectively evaluate the association between HCV genotypes and lymphomas. Lymphoma cases were retrieved from our surgical pathology and hematopathology archives from January 2005 to April 2012. Patients who had positive HCV serology with subsequent viral genotyping were selected. Patients with positive Human immunodeficiency virus (HIV)serology were excluded. We identified 17 lymphoma cases with associated HCV infection. Eleven out of 14 (79%) patients had genotype 1 HCV. Diffuse large B cell lymphoma (DLBCL) was the most common lymphoma (6 out of 17 cases) and all cases of DLBCL had genotype 1. Genotype 2 was detected in only three patients (21%) with the diagnoses of follicular lymphoma, splenic marginal zone lymphoma, and classical Hodgkin lymphoma (CHL). CHL was diagnosed in three cases and peripheral T-cell lymphoma in one case.Twelve of 17 (71%) patients were incarcerated in the Texas Department of Criminal Justice system. All 11 genotype 1 patients were male, 4 of 11 (36%) were African American, 4 of 11 (36%) were Caucasian and 3 of 11 (27%) were Hispanic.We concluded that HCV genotype 1 was more common than genotype 2 while no other genotype was detected.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".