One-year mortality among adults with advanced HIV in sub-Saharan Africa: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: In sub-Saharan Africa (SSA), people with HIV continue to present with advanced HIV disease (AHD), putting them at high risk of life-threatening opportunistic diseases. We aimed to estimate mortality among this population. METHODS: We conducted a systematic review and meta-analysis of studies reporting one-year mortality among adults living with HIV and presenting to care with CD4 + cell count ≤200 cells/mm 3 in SSA. MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials were searched for studies (comprising >500 participants) published between January 1, 2016 and March 21, 2025. Screening and data extraction were done in duplicate. Pooled mortality proportions across CD4 + cell count and time strata were calculated using a generalized linear mixed model. Risk of bias was assessed using a modified Newcastle-Ottawa scale. The protocol is registered with PROSPERO, CRD42023451498. RESULTS: Thirty-six studies with 313 362 participants were included. The weighted median age was 35 years, 64% were female, and 98.9% were antiretroviral therapy-naive. One-year mortality was 12% (95% CI 8-16) among people with CD4 + cell count ≤200 cells/mm 3 and increased with lower CD4 + cell count (≤100 cells/mm 3 , 15% (95% CI 11-19); ≤50 cells/mm 3 , 20% (95% CI 12-31)). Most deaths occurred within the first 3 months after AHD presentation. Heterogeneity was substantial. Risk of bias was high in 18 (50%) of 36 included studies. DISCUSSION: There is high 1-year mortality among people presenting with AHD in SSA. It is a priority to identify AHD with CD4 + testing, improve retention in care, and evaluate additional interventions to reduce mortality in this population.
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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 | 0.014 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.044 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".