The impact of high risk human papillomavirus testing in an inner London colposcopy clinic
Bibliographic record
Abstract
This is an audit of a new technique to improve the colposcopy service. Samples were tested for high risk HPV DNA using Digene Hybrid Capture II. Sixty-four percent of the sampled women under 30 had detectable high risk HPV DNA, decreasing to 44% in 30--39 year olds and to 27% in women over 40. High risk HPV prevalence increased with severity of cytology, although 22% with normal colposcopy had detectable high risk HPV. Of those women treated for cervical dysplasia, 83% had detectable high risk HPV prior to treatment, compared to only 32% afterwards. The audit has shown that high risk HPV testing has considerable discriminatory value. It has been integrated successfully into the service, particularly to manage low grade cervical abnormalities and to add valuable information following treatment for cervical dysplasia. Results need to be interpreted alongside colposcopy, cytology, and histology, and care must be taken in the interpretation of a single high risk HPV result.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 teacher head, 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".