Cost consequences of HIV-associated lipoatrophy
Bibliographic record
Abstract
HIV-associated lipoatrophy may affect up to 35% of patients who have received antiretroviral (ARV) regimens for more than one year, and may result in depression, social isolation, and career barriers. Interventions including the injection of dermal fillers for restoration of facial fat loss are being used for treating HIV-associated lipoatrophy. Since reimbursement is often lacking, patients must consider the pros and cons of such interventions, weighed against the other costs of daily life. The primary goal of the study is to provide reliable estimates of the costs of treating HIV-associated lipoatrophy, specifically facial lipoatrophy. Costs are provided for a single site and are estimated from published studies reporting administration patterns of dermal fillers, publicly available list prices, and physician service fees for similar subcutaneous injections of the face. Fourteen studies were identified that reported experience with five dermal fillers used to treat HIV-associated facial lipoatrophy: poly-L-lactic acid, calcium hydroxylapatite, polyalkylimide gel, hyaluronic acid, and silicone oil. Typical courses involve four physician visits, but could vary from 1 to 13. The cost of a course of dermal filler treatment at a single site ranges across four products (all other than hyaluronic acid) from $3690 to $16,544, and is typically not covered by the payers. Physician fees for an entire course of similar outpatient procedures reimbursed by insurers are approximately $500, and may vary according to location, specialty, and market conditions. These procedures need to be repeated per site injected with intervals of 1-3 years. Treatment of HIV-associated lipoatrophy may represent a considerable out-of-pocket expense for many patients with HIV. This could have implications for deciding whether to undergo a restorative procedure, which procedure to undergo, and whether to pursue other options that may include switching ARV regimens.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".