Antiretroviral Treatment Patterns and Incident HIV-Associated Morphologic and Lipid Abnormalities in a Population-Based Cohort
Bibliographic record
Abstract
This study provides population-based estimates of the incidence of constituent symptoms associated with HIV-related lipodystrophy syndrome. Possible predictors of symptomatology based on analysis of accrued cases are provided after adjustment for a broad range of personal, clinical, and treatment characteristics. Patients enrolled in a province-wide HIV/AIDS treatment program reported annually on the occurrence of lipoatrophy, lipohypertrophy, and elevated triglyceride and cholesterol levels. Of 1261 individuals who provided baseline data, 745 were available at follow-up, among whom incidence was 27% for lipoatrophy, 21% for lipohypertrophy, and 10% and 16% for increased triglyceride and cholesterol levels, respectively. In logistic multivariate modeling, incident lipoatrophy was associated with duration of stavudine (per quarter) (adjusted odds ratio [AOR] 1.18; 95% confidence interval [CI] 1.09-1.27) and having been diagnosed with AIDS (AOR 2.07; 95% CI 1.20-3.56). Lipohypertrophy risk increased with use of protease inhibitor (AOR 3.53; 95% CI 1.81-6.86) and stavudine (AOR 3.67; 95% CI 1.61-8.38). Incident cholesterol or triglyceride abnormalities were associated with protease inhibitor use (AOR 7.17; 95% CI 2.46-20.96) and duration of ritonavir (per quarter) (AOR 1.12; 95% CI 1.04-1.21). Our findings suggest high annual rates of incidence and a role of first line antiretroviral therapies in symptom development. These outcomes, in conjunction with the findings of others have important implications for evolving treatment patterns.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".