2024 British Association for Sexual Health and HIV (BASHH) UK national guideline on the management of vulval conditions
Bibliographic record
Abstract
BackgroundThe management of vulval disorders in Genitourinary Medicine (GUM) clinics requires targeted approaches due to the wide range of conditions affecting the vulva. Vulval diseases encompass various aetiologies, including dermatoses, pain syndromes, and pre-malignant conditions, necessitating specialized care often involving multidisciplinary collaboration.PurposeThis guideline aims to provide evidence-based recommendations for the diagnosis and management of specific vulval conditions that may present in GUM clinics. The focus is on conditions commonly managed by Genitourinary Physicians, either independently or in partnership with other specialists, depending on available local expertise. Additionally, guidance on onward referral is included to ensure optimal patient care.Study SampleThe guideline primarily addresses the management of individuals aged 16 years and older presenting to GUM clinics with non-infective vulval conditions.Data CollectionRecommendations within this guideline are derived from a review of existing literature, clinical expertise, and consensus among specialists. Emphasis is placed on diagnostic tests and treatment regimens tailored to the following conditions: Lichen sclerosus, Lichen planus, Eczema, Lichen simplex, Psoriasis, Vulval high-grade squamous intraepithelial lesions (previously vulval intraepithelial neoplasia), Vulval pain syndromes, and Non-sexually acquired acute genital ulceration (Ulcer of Lipschütz).ConclusionsThis guideline offers practical recommendations for the effective management of specific vulval disorders in GUM settings. It is not intended to be a comprehensive review of all vulval diseases but rather a focused resource to assist clinicians in providing high-quality, patient-centred care. Onward referral pathways are also outlined to support collaborative and multidisciplinary management of complex cases.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.055 | 0.022 |
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".