The evolution of HIV-associated cryptococcal meningitis in Uganda from 2010 to 2022
Bibliographic record
Abstract
Given extensive improvements in access to antiretroviral therapy (ART) over the past 12 years, the HIV and cryptococcal meningitis landscapes have dramatically changed since 2010. We sought to evaluate changes in clinical presentation and clinical outcomes of people presenting with HIV-associated cryptococcal meningitis between 2010 and 2022 in Uganda. We analyzed three prospective cohorts of HIV-infected Ugandans with cryptococcal meningitis during 2010-2012, 2013-2017, and 2018-2022. We summarized baseline demographics, clinical characteristics at presentation, and 2-week and 16-week mortality. Overall, 2022 persons had confirmed cryptococcal meningitis between 2010 and 2022. In the most recent 2018-2022 cohort, 48% presented as ART-naïve, and the median CD4 cell count was 26 cells/µl. Participants in the 2018-2022 cohort had the lowest cerebrospinal fluid (CSF) opening pressure (median 22 cmH2O) and the highest percentage with sterile CSF quantitative cultures (21%) compared with earlier cohorts (P < .001 for both), signifying a less severely ill population presenting with cryptococcal meningitis. Two-week mortality was lowest among participants with cryptococcal meningitis enrolled in a clinical trial in the 2018-2022 cohort at 13% compared to 26% in both 2010-2012 and 2013-2017 (P < .001). While AIDS-related deaths have dramatically declined over the past 12 years, cryptococcosis persists, presenting challenges to HIV program implementation. Two-week mortality has improved in the most recent cohort, likely due to the establishment of cryptococcal screening programs, better supportive care including scheduled lumbar punctures, and the availability of flucytosine-an essential component of antifungal therapy.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".