Non‐medically supervised treatment interruptions among participants in a universally accessible antiretroviral therapy programme
Bibliographic record
Abstract
BACKGROUND: We examined clinical outcomes, patient characteristics and trends over time of non-medically supervised treatment interruptions (TIs) from a free-of-charge antiretroviral therapy (ART) programme in British Columbia (BC), Canada. METHODS: Data from ART-naïve individuals > or =18 years old who initiated triple combination highly active antiretroviral therapy (HAART) between January 2000 and June 2006 were analysed. Participants having > or =3 month gap in HAART coverage were defined as having a TI. Cox proportional hazards modelling was used to examine factors associated with TIs and to examine factors associated with resumption of treatment. RESULTS: A total of 1707 participants were study eligible and 643 (37.7%) experienced TIs. TIs within 1 year of ART initiation decreased from 29% of individuals in 2000 to 19% in 2006 (P<0.001). TIs were independently associated with a history of injection drug use (IDU) (P=0.02), higher baseline CD4 cell counts (P<0.001), hepatitis C co-infection (P<0.001) and the use of nelfinavir (NFV) (P=0.04) or zidovudine (ZDV)/lamivudine (3TC) (P=0.009) in the primary HAART regimen. Male gender (P<0.001), older age (P<0.001), AIDS at baseline (P=0.008) and having a physician who had prescribed HAART to fewer patients (P=0.03) were protective against TIs. Four hundred and eighty-eight (71.9%) participants eventually restarted ART with male patients and those who developed an AIDS-defining illness prior to their TI more likely to restart therapy. Higher CD4 cell counts at the time of TI and unknown hepatitis C status were associated with a reduced likelihood of restarting ART. CONCLUSION: Treatment interruptions were associated with younger, less ill, female and IDU participants. Most participants with interruptions eventually restarted therapy. Interruptions occurred less frequently in recent years.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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 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".