Oral Abstracts
Bibliographic record
Abstract
Aims: To investigate factors that were associated with the proportion of adults with low CD4 cell counts (CD4 < 200 cells/ll) that were not receiving antiretroviral therapy (ART). Methods: The annual Survey of Prevalent HIV Infections Diagnosed (SOPHID) provides an epidemiological profile of, and determines the prevalence of, individuals living with diagnosed HIV infections in England, Wales and Northern Ireland. Adults reported to the 2004 SOPHID survey with both CD4 and ART reported were included in the dataset. Results: Individuals with CD4<200 accounted for 14% (4934/35,242) of all reports in 2004, of which 19% (950) were not on ART. The proportion of individuals with CD4<200 not on ART varied from 9% (Northern Ireland) to 36% (North East) across region of treatment. There was also variation across SHAs within regions. The proportion not on ART varied by most advanced clinical stage: 55% death with AIDS, 13% AIDS, 17% symptoms pre-AIDS and 29% asymptomatic. The proportion of individuals not on ART decreased with increasing age (26% at 15-24; 15% at 50+). There was little difference observed by ethnicity, exposure category or sex. Recent diagnoses accounted for 16% (84/ 514) of individuals not on ART with CD4 <200 in London. Conclusion: One in five individuals with low CD4 cell counts were not on ART, of which relatively few were because they were recently diagnosed. Further work will be required to investigate regional and demographic differences in the proportion not on treatment and to consider reasons why people were not on ART according to BHIVA guidelines.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".