Impact of a tuberculosis treatment adherence intervention versus usual care on treatment completion rates: results of a pragmatic cluster randomized controlled trial
Bibliographic record
Abstract
BACKGROUND: With the global shortage of skilled health workers estimated at 7.2 million, outpatient tuberculosis (TB) care is commonly task-shifted to lay health workers (LHWs) in many low- and middle-income countries where the shortages are greatest. While shown to improve access to care and some health outcomes including TB treatment outcomes, lack of training and supervision limit the effectiveness of LHW programs. Our objective was to refine and evaluate an intervention designed to address common causes of non-adherence to TB treatment and LHW knowledge and skills training needs. METHODS: We employed a pragmatic cluster randomized controlled trial. Participants included 103 health centres (HCs) providing TB care in four districts in Malawi, randomized 1:1 stratified by district and HC funding (Ministry of Health, non-Ministry funded). At intervention HCs, a TB treatment adherence intervention was implemented using educational outreach, a point-of-care reminder tool, and a peer support network. Clusters in the control arm provided usual care. The primary outcome was the proportion of patients with successful TB treatment (i.e., cure or treatment completion). We used a generalized linear mixed model, with district as a fixed effect and HC as a random effect, to compare proportions of patients with treatment success, among the trial arms, with adjustment for baseline differences. RESULTS: We randomized 51 HCs to the intervention group and 52 HCs to the control group. Four intervention and six control HCs accrued no eligible patients, and 371 of 1169 patients had missing outcome, HC, or demographic data, which left 74 HCs and 798 patients for analysis. Randomization group was not related to missing outcome, however, district, age, and TB type were significantly related and included in the primary analysis model. Among the 1153 patients with HC and demographic data, 297/605 (49%) and 348/548 (64%) in the intervention and control arms, respectively, had treatment success. The intervention had no significant effect on treatment success (adjusted odds ratio 1.35 [95% confidence interval 0.93-1.98]). CONCLUSION: We found no significant effect of the intervention on TB treatment outcomes with high variability in implementation quality, highlighting important challenges to both scale-up and sustainability. TRIAL REGISTRATION: ClinicalTrials.gov NCT02533089 . Registered August 20, 2015.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".