Heterogeneity in outcomes of treated HIV-positive patients in Europe and North America: relation with patient and cohort characteristics
Bibliographic record
Abstract
BACKGROUND: HIV cohort collaborations, which pool data from diverse patient cohorts, have provided key insights into outcomes of antiretroviral therapy (ART). However, the extent of, and reasons for, between-cohort heterogeneity in rates of AIDS and mortality are unclear. METHODS: We obtained data on adult HIV-positive patients who started ART from 1998 without a previous AIDS diagnosis from 17 cohorts in North America and Europe. Patients were followed up from 1 month to 2 years after starting ART. We examined between-cohort heterogeneity in crude and adjusted (age, sex, HIV transmission risk, year, CD4 count and HIV-1 RNA at start of ART) rates of AIDS and mortality using random-effects meta-analysis and meta-regression. RESULTS: During 61 520 person-years, 754/38 706 (1.9%) patients died and 1890 (4.9%) progressed to AIDS. Between-cohort variance in mortality rates was reduced from 0.84 to 0.24 (0.73 to 0.28 for AIDS rates) after adjustment for patient characteristics. Adjusted mortality rates were inversely associated with cohorts' estimated completeness of death ascertainment [excellent: 96-100%, good: 90-95%, average: 75-89%; mortality rate ratio 0.66 (95% confidence interval 0.46-0.94) per category]. Mortality rate ratios comparing Europe with North America were 0.42 (0.31-0.57) before and 0.47 (0.30-0.73) after adjusting for completeness of ascertainment. CONCLUSIONS: Heterogeneity between settings in outcomes of HIV treatment has implications for collaborative analyses, policy and clinical care. Estimated mortality rates may require adjustment for completeness of ascertainment. Higher mortality rate in North American, compared with European, cohorts was not fully explained by completeness of ascertainment and may be because of the inclusion of more socially marginalized patients with higher mortality risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.046 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.017 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".