Burden of HIV-Related Cytomegalovirus Retinitis in Resource-Limited Settings: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: Cytomegalovirus (CMV) is a late-stage opportunistic infection in people living with human immunodeficiency virus (HIV)/AIDS. Lack of ophthalmological diagnostic skills, lack of convenient CMV treatment, and increasing access to antiretroviral therapy have all contributed to an assumption that CMV retinitis is no longer a concern in low- and middle-income settings. METHODS: We conducted a systematic review and meta-analysis of published and unpublished studies reporting prevalence of CMV retinitis in low- and middle-income countries. Eligible studies assessed the occurrence of CMV retinitis by funduscopic examination within a cohort of at least 10 HIV-positive adult patients. RESULTS: We identified 65 studies from 24 countries, mainly in Asia (39 studies, 12 931 patients) and Africa (18 studies, 4325 patients). By region, the highest prevalence was observed in Asia with a pooled prevalence of 14.0% (11.8%-16.2%). Almost a third (31.6%, 95% confidence interval [CI], 27.6%-35.8%) had vision loss in 1 or both eyes. Few studies reported immune status, but where reported CD4 count at diagnosis of CMV retinitis was <50 cells/µL in 73.4% of cases. There was no clear pattern of prevalence over time, which was similar for the period 1993-2002 (11.8%; 95% CI, 8%-15.7%) and 2009-2013 (17.6%; 95% CI, 12.6%-22.7%). CONCLUSIONS: Prevalence of CMV retinitis in resource low- and middle-income countries, notably Asian countries, remains high, and routine retinal screening of late presenting HIV-positive patients should be considered. HIV programs must ensure capacity to manage the needs of patients who present late for care.
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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 | 0.006 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".