Understanding recurrent herpes labialis management and impact on patients’ quality of life: the HERPESCOPE study
Bibliographic record
Abstract
Herpes labialis (HL) is a common and benign disease. However, frequent episodes can impair quality of life (QoL) and impact healthcare consumption. The aim of this survey was to understand patients' profiles, behavior, treatment and quality of life, using web-based questionnaires administered in the USA and in France. A total of 1002 and 1005 patients completed it, respectively. Self-diagnosis of HL is usually made at the very start of the prodromal phase. In the USA, 41% of patients seek medical advice at some point and they are often prescribed a topical antiviral drug (AVD) associated with an over-the-counter drug. Those who treat HL by themselves purchase mainly non-antiviral topical drugs. In France, the treatment is almost identical (topical AVD) whether patients seek medical advice (32%) or not. In both countries, patients with 6 or more annual episodes often go to the doctor and use systemic AVD. Continuous treatment is prescribed to 55% and 35% of patients with at least 4 annual episodes, in the USA and France respectively. Sick leaves are delivered to 33% and 14% of patients, respectively. QoL is significantly impaired in a majority of patients, all the more so when HL episodes are more frequent.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".