Outpatient pharmacy care and HIV viral load response among patients on HAART
Bibliographic record
Abstract
Adherence to highly active antiretroviral therapy (HAART) is necessary to achieve long-term effectiveness. The impact of HIV/AIDS-specific pharmacy services on patient adherence and HIV viral suppression is currently not well described. This study aimed to compare the impact of differing levels of HIV-pharmacy care on adherence and time to HIV viral suppression among participants on HAART enrolled in a population-based HIV/AIDS drug treatment programme in British Columbia. We performed a retrospective observational study of 788 treatment-naïve patients who started HAART between August 1997 and July 2000 and were followed until 31 March 2002. The degree of outpatient pharmacy care was defined according to pharmacy dispensing site for the participants' first prescription of HAART: highest at the AIDS-tertiary care hospital outpatient pharmacies, intermediate at HIV/AIDS drug treatment programme funded off-site pharmacies and lowest at family physician's offices. Cox-proportional hazard models examined the independent effect of pharmacy dispensing site on time to two consecutive HIV viral suppressions controlling for other prognostic factors including physicians' experience, age, gender, injection drug use, use of therapy containing NNRTI versus PI, adherence >90%, AIDS diagnosis at baseline, baseline CD4 cell count and HIV viral load. The median time on antiretrovirals was 28 months (IQR=14-38). There were 489 (62.1%) participants who obtained their medications from the AIDS-tertiary care outpatient pharmacies; 98 (12.4%) from off-site pharmacies and 201 (25.5%) from their physicians' offices. The proportion of patients exhibiting >90% adherence to treatment was observed to be higher among patients receiving their HAART at the AIDS-tertiary care pharmacies compared to off-site pharmacies and to physicians' offices (70.4, 59.2 and 55.7%, respectively; p=0.0001). After adjusting for other prognostic factors, subjects who were first dispensed medications from the AIDS-tertiary care pharmacy were 1.42 times (CI: 1.10-1.84) more likely to achieve HIV viral suppression than those getting their medications from off-site pharmacies and physicians' offices. Providing regular outpatient pharmacy care is independently associated with improved HIV viral load response through enhanced adherence to HAART. Standardization of pharmacy practices for dispensing HAART may improve outcomes for patients who receive their HIV medications from other non-tertiary care pharmacy sites.
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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".