Naively changing HAART
Bibliographic record
Abstract
BACKGROUND: Few UK studies have systematically investigated which antiretroviral therapy (ART) combinations HIV-infected people are commenced on, when they start and reasons for stopping or changing their regimens. OBJECTIVE: To describe when HIV-infected ART-naive patients started first-, second- or third-line triple ART, classes of drugs prescribed and whether stopping ART was associated with virological, immunological or clinical indicators of treatment failure. DESIGN: A multicentre prospective open cohort study, employing the National Prospective Monitoring System on the use, cost and outcome of HIV service provision in UK hospitals-HIV Health-economics Collaboration (NPMS-HHC). SETTING: Five hundred and eighty-five ART-naive patients seen in one London and two non-London HIV clinics between 1 January 1998 and 31 December 1999. RESULTS: Of 4,044 HIV-infected individuals seen, 585 (15%) were ART naive. Median time interval (interquartile range, IQR) between HIV diagnosis and starting triple ART was 800 (63-2,094) days. Median CD4 count when first diagnosed with HIV infection was 278 (IQR 127-481) cells/ micro L which dropped to 190 (IQR 86-297) cells/ micro L when starting triple ART. Of these 585 patients, 162 started second-line and 46 third-line ART during the study period. Of those patients who stopped ART, 51% did not have evidence of virological, immunological or clinical indicators of therapy failure. CONCLUSIONS: Reasons for the delay between diagnosis of HIV infection and starting ART are varied. The large proportion of individuals who stopped ART for reasons other than virological, immunological or clinical indicators of therapy failure, are most likely due to drug-associated toxicity. Both of these findings need to be elucidated in greater detail through prospective studies.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.002 |
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".