Mortality According to CD4 Count at Start of Combination Antiretroviral Therapy Among HIV-infected Patients Followed for up to 15 Years After Start of Treatment: Collaborative Cohort Study
Bibliographic record
Abstract
BACKGROUND: CD4 count at start of combination antiretroviral therapy (ART) is strongly associated with short-term survival, but its association with longer-term survival is less well characterized. METHODS: We estimated mortality rates (MRs) by time since start of ART (<0.5, 0.5-0.9, 1-2.9, 3-4.9, 5-9.9, and ≥10 years) among patients from 18 European and North American cohorts who started ART during 1996-2001. Piecewise exponential models stratified by cohort were used to estimate crude and adjusted (for sex, age, transmission risk, period of starting ART [1996-1997, 1998-1999, 2000-2001], and AIDS and human immunodeficiency virus type 1 RNA at baseline) mortality rate ratios (MRRs) by CD4 count at start of ART (0-49, 50-99, 100-199, 200-349, 350-499, ≥500 cells/µL) overall and separately according to time since start of ART. RESULTS: A total of 6344 of 37 496 patients died during 359 219 years of follow-up. The MR per 1000 person-years was 32.8 (95% confidence interval [CI], 30.2-35.5) during the first 6 months, declining to 16.0 (95% CI, 15.4-16.8) during 5-9.9 years and 14.2 (95% CI, 13.3-15.1) after 10 years' duration of ART. During the first year of ART, there was a strong inverse association of CD4 count at start of ART with mortality. This diminished over the next 4 years. The adjusted MRR per CD4 group was 0.97 (95% CI, .94-1.00; P = .054) and 1.02 (95% CI, .98-1.07; P = .32) among patients followed for 5-9.9 and ≥10 years, respectively. CONCLUSIONS: After surviving 5 years of ART, the mortality of patients who started ART with low baseline CD4 count converged with mortality of patients with intermediate and high baseline CD4 counts.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".