Factors associated with the response to antiretroviral therapy among HIV-infected patients with and without a history of injection drug use
Bibliographic record
Abstract
Studies have found that HIV-positive injection drug users appear to have a lower uptake of highly active antiretroviral therapy (HAART) compared with other HIV-positive individuals in Canada, the United States and Europe [1–4]. In July of 1997 the Therapeutic Guidelines of the HIV/AIDS Drug Treatment Program in British Columbia were revised to recommend HAART for all antiretroviral-naive individuals with plasma viral loads greater than 5000 copies/ml or CD4 cell counts less than 500 cells/mm3. We examined the impact of the resultant enhanced access to HAART on favourable virological response, particularly among participants with a history of injection drug use compared with non-drug users enrolled in this province-wide population-based programme. We categorized participants into two cohorts based on the update of the therapeutic guidelines in July 1997. Cohort 1 consisted of individuals who were first prescribed antiretroviral therapy from 1 August 1996 to 31 July 1997. During this time, HAART was only available to those with plasma viral loads greater than 100 000 copies/ml and CD4 cell counts less than 500 cells/mm3. Cohort 2 were individuals who met the updated guideline criteria and were eligible for HAART from 1 August 1997 to 31 October 1998. In this analysis, a history of injection drug use was obtained by self-report or by the physician. Programme enrollment data were used to assign a level of physician HIV-related experience for each subject, estimated via the cumulative number of patients receiving antiretroviral therapy within their practice, by the date of the subject's first known eligibility [1]. Adherence to antiretroviral therapy was defined as the ratio of the number of months patients received antiretroviral therapy refills relative to the total number of months they were actually prescribed [1]. Cox proportional hazard models were used to estimate the hazard of decreasing plasma viral load below 500 copies/ml at least twice consecutively after the start of antiretroviral therapy. The following prognostic variables were placed in the stepwise procedure to select for those meeting the P < 0.05 level for entry into the multivariate model: age, sex, previous AIDS-defining illness, cohort, injection drug use, baseline plasma viral load, CD4 cell count, adherence, physician HIV-related experience and the use of HAART. There were 826 participants in cohort 1 and 580 participants in cohort 2 who were first prescribed antiretroviral therapy between 1 August 1996 and 31 October 1998. No difference was observed between the two cohorts with respect to age, injection drug use history, CD4 cell count, AIDS diagnosis, adherence or physician experience (P > 0.05). Cohort 2 had a lower median plasma viral load (78 500 versus 97 500, P = 0.03), and in keeping with the contemporary guidelines, were more likely to be receiving HAART (89.1 versus 44.7%, P = 0.001) than cohort 1. As shown in Table 1, after adjusting for sex, CD4 cell count, AIDS diagnosis, baseline viral load, physician HIV-related experience, adherence, and the use of HAART in cohort 1, we found a history of injection drug use to be independently associated with not having achieved viral suppression below 500 copies/ml compared with non-injection drug users [relative hazard (RH) = 0.76; 95% confidence interval (CI) 0.59–0.98]. In cohort 2, after adjusting for the same factors, injection drug use was not significantly associated with the time to achieving plasma viral load suppression (RH = 0.97; 95% CI 0.71–1.31). Furthermore, the receipt of HAART among participants with a history of injection drug use in cohort 2 was 89.2% (116/130), whereas in cohort 1 it was only 39.6% (84/212).Table 1: Relative hazards from univariate and multivariate Cox regression analyses of factors associated with plasma viral load suppression below 500 copies/ml on at least two consecutive measurements. We concluded that enhanced access to HAART via updated therapeutic guidelines promoted the use of HAART, even among participants with a history of injection drug use, and that they are as likely to suppress their viral load as non-injection drug users. Anita Palepuab Benita Yipc Cari Millerac Steffanie A. Strathdeece Michael V. O'Shaughnessycd Julio S. G. Montanerbc Robert S. Hoggc
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 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".