The impact of routine cryptococcal antigen screening on survival among <scp>HIV</scp>‐infected individuals with advanced immunosuppression in <scp>K</scp>enya
Bibliographic record
Abstract
OBJECTIVES: To test the hypothesis that a screening and treatment intervention for early cryptococcal infection would improve survival among HIV-infected individuals with low CD4 cell counts. METHODS: Newly enrolled patients at Family AIDS Care and Education Services (FACES) in Kenya with CD4 ≤ 100 cells/μl were tested for serum cryptococcal antigen (sCrAg). Individuals with sCrAg titre ≥ 1:2 were treated with high-dose fluconazole. Cox proportional hazard models of Kaplan-Meier curves were used to compare survival among individuals with CD4 ≤ 100 cells/μl in the intervention and historical control groups. RESULTS: The median age was 34 years [IQR: 29,41], 54% were female, and median CD4 was 43 cells/μl [IQR: 18,71]. Follow-up time was 1224 person-years. In the intervention group, 66% (514/782) were tested for sCrAg; of whom, 11% (59/514) were sCrAg positive. Mortality was 25% (196/782) in the intervention group and 25% (191/771) in the control group. There was no significant difference between the intervention and control group in overall survival [hazard ratio (HR): 1.1 (95%CI:0.9,1.3)] or three-month survival [HR: 1.0 (95%CI:0.8,1.3)]. Within the intervention group, sCrAg-positive individuals had significantly lower survival rates than sCrAg-negative individuals [HR:1.8 (95%CI: 1.0, 3.0)]. CONCLUSIONS: A screening and treatment intervention to identify sCrAg-positive individuals and treat them with high-dose fluconazole did not significantly improve overall survival among HIV-infected individuals with CD4 counts ≤ 100 cells/μl compared to a historical control, perhaps due to intervention uptake rates or poor efficacy of high-dose oral fluconazole.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".