Retention Among North American HIV-Infected Persons in Clinical Care, 2000–2008
Bibliographic record
Abstract
BACKGROUND: Retention in care is key to improving HIV outcomes. The goal of this study was to describe 'churn' in patterns of entry, exit, and retention in HIV care in the United States and Canada. METHODS: Adults contributing ≥1 CD4 count or HIV-1 RNA (HIV-lab) from 2000 to 2008 in North American AIDS Cohort Collaboration on Research and Design clinical cohorts were included. Incomplete retention was defined as lack of 2 HIV-laboratories (≥90 days apart) within 12 months, summarized by calendar year. Beta-binomial regression models were used to estimate adjusted odds ratios (OR) and 95% confidence intervals (CI) of factors associated with incomplete retention. RESULTS: Among 61,438 participants, 15,360 (25%) with incomplete retention significantly differed in univariate analyses (P < 0.001) from 46,078 (75%) consistently retained by age, race/ethnicity, HIV risk, CD4, antiretroviral therapy use, and country of care (United States vs. Canada). From 2000 to 2004, females (OR = 0.82, CI: 0.70 to 0.95), older individuals (OR = 0.78, CI: 0.74 to 0.83 per 10 years), and antiretroviral therapy users (OR = 0.61, CI: 0.54 to 0.68 vs. all others) were less likely to have incomplete retention, whereas black individuals (OR = 1.31, CI: 1.16 to 1.49, vs. white), those with injection drug use HIV risk (OR = 1.68, CI: 1.49 to 1.89, vs. noninjection drug use), and those in care longer (OR = 1.09, CI: 1.07 to 1.11 per year) were more likely to have incomplete retention. Results from 2005 to 2008 were similar. DISCUSSION: From 2000 to 2008, 75% of the North American AIDS Cohort Collaboration on Research and Design population was consistently retained in care with 25% experiencing some changes in status or churn. In addition to the programmatic and policy implications, the findings of this study identify patient groups who may benefit from focused retention efforts.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".