RATES OF HIV/AIDS CARE AND ANTIRETROVIRAL THERAPY RESPONSE AMONG ACTIVE INJECTION DRUG USERS
Bibliographic record
Abstract
There have long been concerns with delivering highly active antiretroviral therapy (HAART) to human immunodeficiency virus (HIV)-infected injection drug users (IDU), although few estimates of the level of HIV/AIDS service use among active IDU exist [1,2]. We would like to present some findings from a study conducted to discern levels of HIV/AIDS service use among a sample of HIV-infected injection drug users who were known to be actively injecting. We recruited a quasi-random sample of HIV-infected IDU from a harm reduction program in Vancouver, Canada [3]. We dichotomized participants into those who were receiving what was potentially appropriate HIV care and those who were inadequately treated for their HIV disease. These definitions were defined a priori based on the International AIDS Society–USA HIV treatment guidelines at the time the participants were recruited [4]. Appropriate care was defined as: (1) being on antiretroviral therapy; (2) having never been on antiretroviral therapy but with a CD4 cell count > 200 cells/μl; or (3) having ceased antiretroviral therapy but with a CD4 cell count that was persistently > 200 cells/μl. Conversely, inadequate treatment was defined a priori as: (1) living with HIV disease but never having had a CD4 cell count test performed (all had never used HAART); or (2) having been on antiretroviral therapy previously but off antiretroviral therapy despite a CD4 cell count < 200 cells/μl [4]. Between 1 December 2003 and 15 December 2004, 164 HIV-positive participants were recruited, and CD4 and plasma HIV RNA levels were obtained for 157 (95.7%) individuals. Among the cohort of 164 IDU, 70 (43%) had never received antiretrovirals {median CD4 cell count 400 cells/μl [interquartile range (IQR): 270–610 cells/μl], and median plasma HIV RNA level: 38 650 [IQR: 11 000–81 700]}. Among these 70 individuals, 21 (14%) had never had their CD4 cell count measured previously [median CD4 cell count: 450 cells/μL (IQR: 270–590 cells/μl), and median plasma HIV RNA level: 36 400 (IQR: 17 500–58 900)]. Among the 94 individuals with a history of antiretroviral use, 57 (60.6%) were currently no longer taking antiretrovirals [median CD4 cell count: 225 cells/μl (IQR: 120–375 cells/μl) and median plasma HIV RNA: 60 700 (IQR: 21 700–100 000) copies/ml]. Among this group, 20 (21.3%) had a CD4 cell count < 200 cells/μl. Among the 37 (23%) IDU who were currently on antiretrovirals, the median CD4 cell count was 280 cells/μl (IQR: 150–430 cells/μl) and the median plasma HIV RNA was 139 (IQR: 0–16 000) copies/ml. Overall, there were 117 (71.3%) individuals who met the combined definition of potentially appropriate treatment, whereas there were 47 (28.7%) individuals who met the combined definition of inadequate HIV/AIDS care (Fig. 1). All outcomes were confirmed through a database linkage [1]. Distribution of HIV-infected injection drug users by HIV care status. Definitions of ‘appropriate’ and ‘inappropriate’ are based on International AIDS Society (IAS) guidelines at the time the participants were enrolled. ARV: antiretroviral therapy Although our definitions of HIV/AIDS care were based on international consensus guidelines [4], for the fraction of IDU who were defined as ceasing HAART inappropriately it is possible that individuals ceased HAART because of toxicities rather than life-style issues [5]. It should also be acknowledged that some IDU may have refused HIV care or antiretrovirals despite its free availability in our setting. Finally, it would be useful to compare our estimates to a population of non-IDU. While cessation of drug use and maximal virological suppression should undoubtedly be pursued [4], the present study demonstrates reasonable levels of HIV care despite ongoing active drug use. While novel strategies will be required for the significant proportion of individuals who were receiving inadequate HIV/AIDS care, these findings should be useful for informing the various international HAART expansion initiatives [6–8]. This study was supported by the US National Institutes of Health (R01 DA011591-04A1) and Administrative Supplement NOT-DA-05-007. We thank Aaron Eddie, Suzy Coulter, Megan Oleson, Peter Vann, Dave Isham, Steve Gaspar, Soni Thindal and Deborah Graham for their research and administrative assistance. E.W., T.K., R.Z. and S.A.S. have no conflicts of interest to disclose. M.W.T. reports having served on advisory boards of Abbott, GlaxoSmithKline, Boehringer Ingelheim and Bristol-Meyers Squibb, and has received research support from Merck Frosst Canada. R.S.H. has received grant funding and honoraria and/or reimbursement from the pharmaceutical industry for participating in continued medical education programmes and conferences from Abbott, Agouron Pharmaceuticals Inc., Boehringer Ingelheim Pharmaceuticals Inc., Bristol-Myers Squibb, GlaxoSmithKline and Merck Frosst Laboratories. J.S.G.M. has received educational grants from, served as an ad hoc adviser to, or spoken at various events sponsored by Abbott Laboratories, Agouron Pharmaceuticals Inc., Boehringer Ingelheim Pharmaceuticals Inc., Borean Pharma AS, Bristol–Myers Squibb, DuPont Pharma, Gilead Sciences, GlaxoSmithKline, Hoffmann-La Roche, Immune Response Corporation, Incyte, Janssen-Ortho Inc., Kucera Pharmaceutical Company, Merck Frosst Laboratories, Pfizer Canada Inc., Sanofi Pasteur, Shire Biochem Inc., Tibotec Pharmaceuticals Ltd and Trimeris Inc.
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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) | 0.001 | 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 | 0.001 | 0.002 |
| 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".