The Prevalence of Hepatitis C Virus (HCV) among Lichen Planus Patients and Its Clinical Pattern at the University of Abuja Teaching Hospital (U.A.T.H), Gwagwalada, Abuja, Nigeria
Bibliographic record
Abstract
OBJECTIVE: The relationship between hepatitis C virus and Lichen Planus have been widely reported in the literature; although there are wide geographical variations in the reported prevalence of hepatitis C virus infection in patients with lichen planus. This study seeks to determine the prevalence of hepatitis C virus among lichen planus patients and its clinical morphological type in the University of Abuja Teaching Hospital, Gwagwalada Abuja, Nigeria. MATERIALS/METHODS: This study was conducted between January 2010 and December, 2011 at the out patients Dermatological unit of the department of medicine at the University of Abuja Teaching Hospital Gwagwalada Abuja, Nigeria. Consecutive patients who had body eruptions suspected to be lichen planus were recruited and histology done for confirmation. The control group included patients' relations and some dermatology patients known to have low risk of hepatitis C virus infection and liver function tests done for both subjects and control after obtaining oral consent from them to participate in the study. RESULT: Anti- HCV antibodies were detected in nine cases (21.4%) and one case (3.3%) in the control group. This was statistically significant difference between the HCV antibody among the subject and control group (P<0.038). Hypertrophic lichen planus was the most frequent clinical type. Liver function test was not statistically significant among the subject and control group. CONCLUSION: Lichen planus and Hepatitis C virus appear to have a relationship and the prevalence rate was higher among the subject as compared to the control group in our environment.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".