High Prevalence of Tuberculosis and Serious Bloodstream Infections in Ambulatory Individuals Presenting for Antiretroviral Therapy in Malawi
Bibliographic record
Abstract
BACKGROUND: Tuberculosis (TB) and serious bloodstream infections (BSI) may contribute to the high early mortality observed among patients qualifying for antiretroviral therapy (ART) with unexplained weight loss, chronic fever or chronic diarrhea. METHODS AND FINDINGS: A prospective cohort study determined the prevalence of undiagnosed TB or BSI among ambulatory HIV-infected adults with unexplained weight loss and/or chronic fever, or diarrhea in two routine program settings in Malawi. Subjects with positive expectorated sputum smears for AFB were excluded. Investigations Bacterial and mycobacterial blood cultures, cryptococcal antigen test (CrAg), induced sputum (IS) for TB microscopy and solid culture, full blood count and CD4 lymphocyte count. Among 469 subjects, 52 (11%) had microbiological evidence of TB; 50 (11%) had a positive (non-TB) blood culture and/or positive CrAg. Sixty-five additional TB cases were diagnosed on clinical and radiological grounds. Nontyphoidal Salmonellae (NTS) were the most common blood culture pathogens (29 cases; 6% of participants and 52% of bloodstream isolates). Multivariate analysis of baseline clinical and hematological characteristics found significant independent associations between oral candidiasis or lymphadenopathy and TB, marked CD4 lymphopenia and NTS infection, and severe anemia and either infection, but low positive likelihood ratios (<2 for all combinations). CONCLUSIONS: We observed a high prevalence of TB and serious BSI, particularly NTS, in a program cohort of chronically ill HIV-infected outpatients. Baseline clinical and hematological characteristics were inadequate predictors of infection. HIV clinics need better rapid screening tools for TB and BSI. Clinical trials to evaluate empiric TB or NTS treatment are required in similar populations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".