Prevalence of Oncogenic Human Papillomavirus Genotypes Among Sexually Active Women in Parakou (Benin, West Africa)
Bibliographic record
Abstract
Background: The genital infection due to Human papillomavirus (HPV) is considered as the most common sexually transmitted infection across the world, including high-risk oncogenic HPV (HR/HPV). Objective: This study aimed to determine the prevalence of HR/HPV genotypes among sexually active women in Parakou (Benin) in 2017. Methods: This research work was a cross-sectional descriptive study carried out in the city of Parakou (Benin), from January 15 to April 15, 2017. Sample consisted of 247 sexually active women selected through a systematic random sampling. Cervical specimens collected with swab were subject to multiplex PCR to characterize 14 HR/HPV genotypes. Results: The prevalence of HR/HPV infection was rated 32.8% [95% CI: 27.1-39.3]. All the fourteen HR/HPV genotypes investigated were detected using PCR among our study population. The most common types of HR/HPV were, in descending order, HPV45 (25.9%), HPV35 (18.5%), HPV52 (17.3%), HPV51 (16.0%) and HPV58 (14.8%). HPV16 and 18 were found out at respective proportions of 2.5% and 7.4%. Age group 20 years or less had the highest prevalence of HR/HPV infection (55.7%) followed by age group from 21 to 30 years (38.3%). Conclusion: The prevalence of HR/HPV infection is high among sexually active women in Parakou in 2017 and the most frequent HR/HPV are not those found commonly in precancerous and cancerous cervical lesions.
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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 | 0.000 | 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".