Excess mortality attributable to AIDS among people living with HIV in high‐income countries: a systematic review and meta‐analysis
Bibliographic record
Abstract
INTRODUCTION: Identifying strategies to further reduce AIDS-related mortality requires accurate estimates of the extent to which mortality among people living with HIV (PLHIV) is due to AIDS-related or non-AIDS-related causes. Existing approaches to estimating AIDS-related mortality have quantified AIDS-related mortality as total mortality among PLHIV in excess of age- and sex-matched mortality in populations without HIV. However, recent evidence suggests that, with high antiretroviral therapy (ART) coverage, a growing proportion of excess mortality among PLHIV is non-AIDS-related. METHODS: We searched Embase on 22/09/2023 for English language studies that contained data on AIDS-related mortality rates among adult PLHIV and age-matched comparator all-cause mortality rates among people without HIV. We extracted data on the number and rates of all-cause and AIDS-related deaths, demographics, ART use and AIDS-related mortality definitions. We calculated the proportion of excess mortality among PLHIV that is AIDS-related. The proportion of excess mortality due to AIDS was pooled using random-effects meta-analysis. RESULTS: Of 4485 studies identified by the initial search, eight were eligible, all from high-income settings: five from Europe, one from Canada, one from Japan and one from South Korea. No studies reported on mortality among only untreated PLHIV. One study included only PLHIV on ART. In all studies, most PLHIV were on ART by the end of follow-up. Overall, 1,331,742 person-years and 17,471 deaths were included from PLHIV, a mortality rate of 13.1 per 1000 person-years. Of these deaths, 7721 (44%) were AIDS-related, an overall AIDS-related mortality rate of 5.8 per 1000 person-years. The mean overall mortality rate among the general population was 2.8 (95% CI: 1.8-4.0) per 1000 person-years. The meta-analysed percentage of excess mortality that was AIDS-related was 53% (95% CI: 45-61%); 52% (43-60%) in Western and Central Europe and North America, and 71% (69-74%) in the Asia-Pacific region. DISCUSSION: Although we searched all regions, we only found eligible studies from high-income countries, mostly European, so, the generalizability of these results to other regions and epidemic settings is unknown. CONCLUSIONS: Around half of the excess mortality among PLHIV in high-income regions was non-AIDS-related. An emphasis on preventing and treating comorbidities linked to non-AIDS mortality among PLHIV is required.
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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 | 0.017 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.033 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".