Oral Human Papillomavirus Infection and Oral Lesions in HIV-Positive and HIV-Negative Dental Patients
Bibliographic record
Abstract
We evaluated the risk factors associated with oral human papillomavirus (HPV) infection and oral lesions in 161 human immunodeficiency virus (HIV)-positive patients and 128 HIV-negative patients presenting for oral examination at 2 urban healthcare centers. Patients were interviewed on risk factors and provided oral-rinse samples for HPV DNA typing by polymerase chain reaction. Statistical associations were assessed by logistic regression. Oral HPV was prevalent in 32% and 16% of HIV-positive patients and HIV-negative patients, respectively, including high-risk HPV type 16 (8% and 2%, respectively; P = .049) and uncommon HPV types 32/42 (6% and 5%, respectively; P = .715). Among HIV-negative patients, significant risk factors for oral HPV included multiple sex partners (≥21 vs ≤5; odds ratio [OR], 9.1; 95% confidence interval [CI], 1.7-49.3), heavy tobacco smoking (>20 pack-years vs none; OR, 9.2; 95% CI, 1.4-59.4), and marijuana use (OR, 4.0; 95% CI, 1.3-12.4). Among HIV-positive patients, lower CD4(+) T-cell count only was associated with oral HPV detection (≤200 vs ≥500 cells/mm(3); OR, 4.5; 95% CI, 1.3-15.5). Detection of high-risk HPV was also associated with concurrent detection of potentially cancerous oral lesions among HIV-negative patients but not among HIV-positive patients. The observed risk factor associations with oral HPV in HIV-negative patients are consistent with sexual transmission and local immunity, whereas in HIV-positive patients, oral HPV detection is strongly associated with low CD4(+) T-cell counts.
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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 | 0.003 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".