Design and protocol for a pragmatic randomised study to optimise screening, prevention and care for tuberculosis and HIV in Malawi (PROSPECT Study)
Bibliographic record
Abstract
Background: Adults seeking diagnosis and treatment for tuberculosis (TB) and HIV in low-resource settings face considerable barriers and have high pre-treatment mortality. Efforts to improve access to prompt TB treatment have been hampered by limitations in TB diagnostics, with considerable uncertainty about how available and new tests can best be implemented. Design and methods: The PROSPECT Study is an open, three-arm pragmatic randomised study that will investigate the effectiveness and cost-effectiveness of optimised HIV and TB diagnosis and linkage to care interventions in reducing time to TB diagnosis and prevalence of undiagnosed TB and HIV in primary care in Blantyre, Malawi. Participants (≥ 18 years) attending a primary care clinic with TB symptoms (cough of any duration) will be randomly allocated to one of three groups: (i) standard of care; (ii) optimised HIV diagnosis and linkage; or (iii) optimised HIV and TB diagnosis and linkage. We will test two hypotheses: firstly, whether prompt linkage to HIV care should be prioritised for adults with TB symptoms; and secondly, whether an optimised TB triage testing algorithm comprised of digital chest x-ray evaluated by computer-aided diagnosis software and sputum GeneXpert MTB/Rif can outperform clinician-directed TB screening. The primary trial outcome will be time to TB treatment initiation by day 56, and secondary outcomes will include prevalence of undiagnosed TB and HIV, mortality, quality of life, and cost-effectiveness. Conclusions: The PROSPECT Study will provide urgently-needed evidence under “real-life” conditions to inform clinicians and policy makers on how best to improve TB/HIV diagnosis and treatment in Africa. Clinical trial registration: NCT03519425 (08/05/2018)
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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 | 0.066 | 0.067 |
| Meta-epidemiology (narrow) | 0.006 | 0.005 |
| Meta-epidemiology (broad) | 0.009 | 0.005 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.157 | 0.027 |
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".