Intermittent use of triple-combination therapy is predictive of mortality at baseline and after 1 year of follow-up
Bibliographic record
Abstract
OBJECTIVE: To characterize the impact of intermittent use of triple drug antiretroviral therapy on survival. DESIGN, SETTING AND PARTICIPANTS: Population-based analysis of 1282 antiretroviral therapy naive HIV-positive individuals aged 18 years and older in British Columbia who started triple-combination therapy between August 1996 and December 1999. Therapy use was estimated by dividing the number of months of medications dispensed by the number of months of follow-up. Intermittent therapy was defined as the participant having obtained less than 75% of their medication in the first 12 months. MAIN OUTCOME MEASURE: Cumulative all-cause mortality rates from the start of triple drug antiretroviral therapy to 30 September 2000. RESULTS: As of 30 September 2000, 106 subjects had died. Cumulative mortality was 3.9% (+/- 0.5%) at 12 months. In a multivariate model, after controlling for other variables that were significant in the univariate analyses each 100 cell decrement in baseline CD4 cell count and the intermittent use of antiretroviral drugs were associated with increased mortality with risk ratios of 1.31 [95% confidence interval (CI), 1.16-1.49; P < 0.001] and 2.90 (95% CI, 1.93-4.36; P < 0.001), respectively. In order to control for downward drift, intermittent use of therapy was measured over the first year whereas other factors were measured at the end of year 1. After adjusting for all other factors, those participants who used antiretroviral drugs intermittently were 2.97 times (95% CI, 1.33-6.62; P = 0.008) more likely to die. CONCLUSION: Our study demonstrates that even after adjusting for other prognostic factors intermittent use of antiretroviral therapy was associated with increased mortality.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".