Implementation of systematic screening for tuberculosis disease and tuberculosis preventive treatment among people living with HIV attending antiretroviral treatment clinics in Ghana: a national pilot study
Bibliographic record
Abstract
OBJECTIVES: To assess the yield and cost of implementing systematic screening for tuberculosis (TB) disease among people living with HIV (PLHIV) and initiation of TB preventive treatment (TPT) in Ghana. DESIGN: Prospective cohort study from August 2019 to December 2020. SETTING: One hospital from each of Ghana's regions (10 total). PARTICIPANTS: Any PLHIV already receiving or newly initiating antiretroviral treatment were eligible for inclusion. INTERVENTIONS: All participants received TB symptom screening and chest radiography. Those with symptoms and/or an abnormal chest X-ray provided a sputum sample for microbiological testing. All without TB disease were offered TPT. PRIMARY AND SECONDARY OUTCOME MEASURES: We estimated the proportion diagnosed with TB disease and proportion initiating TPT. We used logistic regression to identify factors associated with TB disease diagnosis. We used microcosting to estimate the health system cost per person screened (2020 US$). RESULTS: Of 12 916 PLHIV attending participating clinics, 2639 (20%) were enrolled in the study and screened for TB disease. Overall, 341/2639 (12.9%, 95% CI 11.7% to 14.3%) had TB symptoms and/or an abnormal chest X-ray; 50/2639 (1.9%; 95% CI 1.4% to 2.5%) were diagnosed with TB disease, 20% of which was subclinical. In multivariable analysis, only those newly initiating antiretroviral treatment were at increased odds of TB disease (adjusted OR 4.1, 95% CI 2.0 to 8.2). Among 2589 participants without TB, 2581/2589 (99.7%) initiated TPT. Overall, the average cost per person screened during the study was US$57.32. CONCLUSION: In Ghana, systematic TB disease screening among PLHIV was of high yield and modest cost when combined with TPT. Our findings support WHO recommendations for routine TB disease screening among PLHIV.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".