Association between human papillomaviruses, metabolic syndrome, and all-cause death; analysis of the U.S. NHANES 2003–2004 to 2015–2016
Bibliographic record
Abstract
INTRODUCTION: Human papillomavirus (HPV) is the most common sexually transmitted infection, attributed to 4.5% of all cancers worldwide. Co-infection with the metabolic syndrome (MetS), a common cluster of cardiometabolic risk factors, has been shown to increase the persistence of HPV. The purpose of this study was to estimate the association between HPV and MetS on mortality risk. METHODS: Data for the current study was drawn from seven consecutive cycles (2003-2004 to 2015-2016) of the U.S. NHANES. The final analytic sample consisted of 5,101 individuals aged 18-65y with HPV and MetS information with follow-up to Dec. 31st, 2019. Baseline HPV status was assessed by either vaginal swab, penile swab or oral rinse and used to classify participants as: no HPV (n = 1,619), low (n = 1,138), probable (n = 672), and high-risk (n = 1,672; 22% type 16, and 10% type 18) HPV using IARC criteria. MetS was assessed by the Harmonized criteria. RESULTS: The average follow-up was 9.4 y with 240 all-cause deaths (no HPV: n = 46 deaths; low-risk: n = 60 deaths; probable: n = 37 deaths, and; high-risk: n = 97 deaths). HPV status alone revealed no associations with mortality in fully adjusted models. Cross-classification into discrete MetS/HPV strata yielded an increased risk of mortality in females with high-risk HPV/MetS relative to the no MetS/no HPV group. CONCLUSIONS: In this study, low, probable, and high-risk HPV and MetS were differentially related to mortality risk in men and women. Further work is necessary to separate the temporal, age, vaccination, and sex effects of HPV diagnosis in these relationships using prospective studies with detailed histories of HPV infection and persistence.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".