Prevalence and Determinants of High-Risk Human Papillomavirus Infection in Women From a Sub-Saharan African Community
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Human papillomavirus infection with high-risk types (HR-HPV) is a necessary cause of cervical cancer, the most common malignancy among sub-Saharan African women. Little is known about prevalence of cervical HR-HPV infection in this region. METHODS: A cross-sectional study of 1528 women examined the determinants of HR-HPV infection among women in Kinshasa, Democratic Republic of Congo. Information was collected on sociodemographic, reproductive, lifestyle characteristics, and health-seeking behaviors. Cervical samples were tested for HPV-DNA by Hybrid Capture 2. Unconditional logistic regression identified predictors of HPV positivity. RESULTS: HR-HPV prevalence was 12.5% in all women and 8.7% in women with normal cytology. Prevalence was highest (18.3%) in individuals <35 years of age and gradually decreased with age. Excess HR-HPV infection risk was observed in women who were smokers (odds ratio [OR] = 1.60; 95% confidence interval [CI]: 1.11-2.31), divorced/separated (OR = 1.60; 95% CI: 1.11-2.32), in polygamous marriages (OR = 1.28; 95% CI: 0.90-1.82), using medical contraceptives (OR = 2.40; 95% CI: 1.20-4.80), and who preferred male physicians (OR = 1.90; 95% CI: 1.20-3.05). A statistically marginal increase was found in women whose partners had sex with prostitutes (OR = 2.40; 95% CI: 0.72-8.01). A higher standard of living was associated with reduced risk. CONCLUSION: HR-HPV positivity was associated with behavioral and sexual characteristics thought to affect risk of new infections and immune function. However, HPV prevalence did not correlate with numbers of sex partners, possibly because of a high HPV infection rate per sexual contact or because subjects were older than 30 years. Our study should assist in designing strategies for control of cervical cancer in this low-resource, high cervical cancer risk setting in sub-Saharan Africa.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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 it