Loss of quality of life associated with genital warts: baseline analyses from a prospective study
Bibliographic record
Abstract
OBJECTIVE: The quadrivalent human papillomavirus (HPV) vaccine is effective against HPV types responsible for 90% of anogenital warts. This study estimated the quality of life lost to genital warts using the EQ-5D, a generic instrument widely used for applications in economic analyses. The findings are described in terms that are more specific to individuals with genital warts using psychosocial questions adapted from the HPV impact profile, a measure developed for HPV-related conditions. METHODS: Between September 2006 and February 2008, 42 physicians across Canada recruited 330 consenting patients 18 years and older with genital warts, either at the first or follow-up visit for an initial or recurrent episode. The quality of life lost associated with genital warts was estimated by the difference between participants' EQ-5D scores and age and gender-specific population norms. RESULTS: The study questionnaire was self-completed by 270 participants who were aged 31.5 years (SD 10.4) on average. The majority of participants were women (53.3%), heterosexual (93.5%) and in a stable relationship (66.0%). Genital warts were associated with detriments in the EQ-5D domains of anxiety/depression, pain/discomfort and usual activities. The absolute difference in the EQ-5D utility score and the EQ-VAS health status between genital warts patients and population norms was 9.9 (95% CI 7.3 to 12.5) and 6.0 (95% CI 4.1 to 7.9) percentage points, respectively. These results did not vary significantly according to patient age, gender, time since first episode or number of episodes. CONCLUSION: The results suggest that genital warts negatively affect the wellbeing of men and women as reflected by poorer quality of life scores compared with population norms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".