Clinical assessment of HIV-associated lipodystrophy in an ambulatory population
Bibliographic record
Abstract
OBJECTIVE: To identify clinical factors associated with prevalence of fat atrophy (lipoatrophy) and fat accumulation (lipoaccumulation) in HIV-1 infected patients. DESIGN: Evaluation of HIV-1 infected patients seen for routine care between 1 October and 31 December 1998 in the eight HIV Outpatient Study (HOPS) clinics. SETTING: Eight clinics specializing in the care of HIV-1 infected patients. PATIENTS: A total of 1077 patients were evaluated for signs of fat maldistribution. INTERVENTIONS: A standardized set of questions and specific clinical signs were assessed. Demographic, clinical and pharmacological data for each patient were also included in the analysis. MAIN OUTCOME MEASURES: Demographic, immunologic, virologic, clinical, laboratory, and drug treatment factors were assessed in stratified and multivariate analyses for their relationship to the presence and severity of fat accumulation and atrophy. RESULTS: Independent factors for moderate/severe lipoatrophy for 171 patients were increasing age, any use of stavudine, use of indinavir for longer than 2 years, body mass index (BMI) loss, and measures of duration and severity of HIV disease. Independent risk factors for moderate/severe fat accumulation for 104 patients were increasing age, BMI gain, measures of amount and duration of immune recovery, and duration of antiretroviral therapy (ART). The number of non-drug risk factors substantially increased the likelihood of lipoatrophy. If non-drug risk factors were absent, lipoatrophy was unusual regardless of the duration of drug use. CONCLUSIONS: HIV-associated lipodystrophy is associated with several host, disease, and drug factors. While prevalence of lipoatrophy increased with the use of stavudine and indinavir, and lipoaccumulation was associated with duration of ART, other non-drug factors were strongly associated with both fat atrophy and accumulation.
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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".