Global burden of HIV/AIDS in 2004 resulting from alcohol attributable non-adherence to medication regimes
Bibliographic record
Abstract
Shield, K. D., Shuper, P. A., Gmel, G. & Rehm, J. (2013). Global burden of HIV/AIDS in 2004 resulting from non-adherence to medication regimes and alcohol-attributable non-adherence to medication regimes. International Journal of Alcohol and Drug Research, 2(1), 19-44. doi: 10.7895/ijadr.v2i1.52 (http://dx.doi.org/10.7895/ijadr.v2i1.52)Aims: Using novel methodology, this article aims to quantify the number of HIV/AIDS-related deaths and the potential years of life lost (PYLL) in 2004 resulting from non-adherence to antiretroviral treatment (ART) and non-adherence to ART due to alcohol consumption.Design: HIV/AIDS-related deaths and PYLL attributable to non-adherence to ART and attributable specifically to non-adherence due to alcohol consumption were calculated using attributable fractions. These fractions were based on new risk modeling methodology, which combines estimates of the mortality of those people currently adhering to ART, the mortality attributable to non-adherence to ART, and the proportion of those people not adhering to ART because of alcohol consumption.Measurements: Data on alcohol indicators were obtained from the Comparative Risk Assessment study, data on deaths and PYLL were obtained from the World Health Organization, and ART indicators were obtained from UNAIDS.Findings: In 2004, for people 15 years of age and older, 67,000 (95% CI: 62,000–72,000) deaths and 1,608,000 (95% CI: 1,491,000–1,725,000) PYLL were caused by non-adherence to ART, of which 8,000 (95% CI: 3,000–13,000) HIV/AIDS-related deaths and 187,000 (95% CI: 70,000–304,000) HIV/AIDS-related PYLL were attributable to alcohol consumption.Conclusions: As the burden of disease for HIV/AIDS-related deaths attributable to non-adherence to ART and attributable to alcohol consumption is non-trivial, additional research is required to examine the effectiveness of different interventions aimed at reducing alcohol consumption among people with HIV/AIDS and at increasing adherence to ART among both drinkers and non- drinkers.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".