High mortality among patients with tuberculosis accessing primary care facilities: secondary analysis from an open-label cluster-randomised trial
Bibliographic record
Abstract
Background Tuberculosis (TB) mortality remains persistently high, despite global TB control efforts. The aim of this study was to assess if a quality improvement (QI) intervention reduced deaths in TB patients accessing primary healthcare (PHC) services. Methods In this pre specified secondary analysis of a cluster-randomized controlled study conducted in 2016–2018 in South Africa (Clinicaltrials.gov, NCT02654613), we compared 18-month case-fatality rates among newly diagnosed TB patients irrespective of HIV status randomized to clinics receiving the QI intervention and standard of care (SOC) [(eight clusters and 20 clinics per arm)]. Statistical inferences used a t -test from a two-stage approach recommended for cluster-randomized trials with fewer than 15 clusters per arm. Findings Among the 5817 newly diagnosed TB patients enrolled (intervention = 3473; control = 2344), 562 died by 18-months [case-fatality rate (CFR) = 9·7%]. Ninety percent of the deaths (506/562) occurred within six months of TB treatment initiation. Quality improvement intervention arm clinics compared to control arm clinics did not demonstrate a significant difference in TB CFR. Case-fatality rates were 9·5% [95% Confidence Interval (CI): 6·9–12·9] and 11·3% (95% CI: 8·7–14·7) [adjusted rate ratio (aRR), 0·9 (95% CI: 0·6–1·2)] in the intervention and control arms, respectively. In people living with HIV/AIDS (PLWHA) CFR in the intervention and control arms: were 10·8% (95% CI: 7·8–14·7) and 14·4% (95% CI: 9·3–22·4) in those on antiretroviral therapy (ART) and 18·6 (95% CI: 9·1–38·0) and 33·0 (95% CI: 16·2–67·3), in those with no ART data respectively. In the intervention and control arms CFR in HIV-TB coinfected patients was 6·5 (95% CI: 3·6–11·6) and 11·5 (95% CI: 6·5–20·0) in those on ART with viral loads <200 copies/ml and 22·4 (95% CI: 16·7–30·2) and 19·7 (95% CI: 11·3–34·5) in those with no viral load data as they commenced ART within 12 months before initiating TB treatment, respectively. Interpretation The quality improvement intervention did not significantly reduce mortality. We observed that TB CFR was higher among PLWHA not on ART and HIV-TB coinfected patients. Funding Research reported in this publication was supported by South African Medical Research Council (SAMRC), and UK Government's Newton Fund through United Kingdom Medical Research Council (UKMRC).
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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 | 0.016 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.010 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".