Awareness and prevalence of hepatitis C virus infection among pregnant women in Nigeria: A national pilot cross-sectional study
Bibliographic record
Abstract
BACKGROUND: There are no national data on hepatitis C virus awareness and burden among pregnant women to justify its routine screening. OBJECTIVES: To investigate awareness, seroprevalence and risk factors for hepatitis C virus infection among pregnant women in Nigeria. METHODS: A total of 159 pregnant women from antenatal clinics across six geopolitical zones in Nigeria consented to anti-hepatitis C virus testing which was confirmed using polymerase chain reaction technique. Confirmed hepatitis C virus positive women were further tested for hepatitis B and HIV. Participants were evaluated for risk factors for hepatitis C virus. Odds ratios, adjusted odds ratios, and their 95% confidence intervals (CIs) were determined, and p-values of <0.05 were considered significant. RESULTS: Of 159 participants, 77 (48.4%; 95% confidence interval = 38.2%-60.5%) were aware of hepatitis C virus infection and awareness of hepatitis C virus was associated with young age (odds ratio = 2.21; 95% confidence interval = 1.16-4.21), high educational level (odds ratio = 3.29; 95% confidence interval = 1.63-6.64), and participants' occupation (odds ratio = 0.51; 95% confidence interval = 0.26-0.99). In multivariable logistic regression, adjusted for confounders, the association between awareness of hepatitis C virus and participants' young age (adjusted odds ratio = 1.60; 95% confidence interval = 1.09-2.35; p = 0.018) and high educational level (adjusted odds ratio = 1.48; 95% confidence interval = 1.17-1.86; p = 0.001) remained significant. Hepatitis C virus seroprevalence was found to be 1.3% (95% confidence interval = 0.2%-4.5%). All (100.0%, 95% confidence interval = 12.1%-100.0%) the hepatitis C virus-positive participants and 99 (63.1%, 95% confidence interval = 51.3%-76.8%) hepatitis C virus-negative participants had identifiable hepatitis C virus risk factors. Dual seropositivity of anti-hepatitis C virus/anti-HIV and anti-hepatitis C virus/hepatitis B surface antigen each accounted for 0.6%. The most identified risk factors were multiple sexual partners (15.7%), shared needles (13.8%), and blood transfusion (11.3%). There was no significant association between the risk factors and hepatitis C virus positive status. CONCLUSION: Awareness of hepatitis C virus infection among pregnant women in Nigeria is low and those aware are positively influenced by young age and high educational level. The prevalence of hepatitis C virus infection is high and provides preliminary evidence to justify antenatal routine screening.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".