Cause-Specific Mortality in HIV-Positive Patients Who Survived Ten Years after Starting Antiretroviral Therapy
Bibliographic record
Abstract
OBJECTIVES: To estimate mortality rates and prognostic factors in HIV-positive patients who started combination antiretroviral therapy between 1996-1999 and survived for more than ten years. METHODS: We used data from 18 European and North American HIV cohort studies contributing to the Antiretroviral Therapy Cohort Collaboration. We followed up patients from ten years after start of combination antiretroviral therapy. We estimated overall and cause-specific mortality rate ratios for age, sex, transmission through injection drug use, AIDS, CD4 count and HIV-1 RNA. RESULTS: During 50,593 person years 656/13,011 (5%) patients died. Older age, male sex, injecting drug use transmission, AIDS, and low CD4 count and detectable viral replication ten years after starting combination antiretroviral therapy were associated with higher subsequent mortality. CD4 count at ART start did not predict mortality in models adjusted for patient characteristics ten years after start of antiretroviral therapy. The most frequent causes of death (among 340 classified) were non-AIDS cancer, AIDS, cardiovascular, and liver-related disease. Older age was strongly associated with cardiovascular mortality, injecting drug use transmission with non-AIDS infection and liver-related mortality, and low CD4 and detectable viral replication ten years after starting antiretroviral therapy with AIDS mortality. Five-year mortality risk was <5% in 60% of all patients, and in 30% of those aged over 60 years. CONCLUSIONS: Viral replication, lower CD4 count, prior AIDS, and transmission via injecting drug use continue to predict higher all-cause and AIDS-related mortality in patients treated with combination antiretroviral therapy for over a decade. Deaths from AIDS and non-AIDS infection are less frequent than deaths from other non-AIDS causes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".