Predictors of tuberculosis treatment outcome at Senkatana clinic in Lesotho
Bibliographic record
Abstract
Introduction: tuberculosis (TB) is one of the top ten causes of death and the leading cause from a single infectious agent called Mycobacterium tuberculosis. This study aims to evaluate TB treatment outcomes among patients on first-line anti-tuberculosis treatment and identify the factors associated with successful TB treatment outcomes at Senkatana TB clinic in Lesotho from 2015-2017. Methods: a registry-based retrospective cohort study of all TB first-line cases recorded from 2015 to 2017 was conducted at Senkatana TB clinic. Data were captured and cleaned in Epi info version 7, and exported into Stata version 14 for analysis. Bivariate logistic regression analysis was used to determine factors associated with TB treatment outcome with p-value <0.05 indicating statistical significance. Results: a total of 1,027 TB patients were registered between 2015 and 2017. Of these, 602 (58.6%) were males and 425 (41.4%) were females, with a mean age of 39 years (SD ±12.5). A total of 843 (82.1%) patients were co-infected with HIV, of which 92.3% (n=778) were on anti-retroviral therapy (ART). The analysis of HIV co-infected with TB patients by age showed that the TB/HIV co-infection rate varies with age (p<0.001). Overall treatment success rate was at 73.4% (n= 754) and 273 (26.6%) had poor treatment outcomes, and 118 (11.5%) patients died. The odds of successful TB treatment outcome were higher in females than males (78.1% vs 70.1%, OR 1.52, 95% CI: 1.14 - 2.03, p=0.004). With regards to age, the odds of successful TB treatment outcome were higher for the 20-24 years age group (88.2% vs 65.3%, OR 3.98, 95% CI: 1.42 - 11.22, P=0.009) and 55-59 years (91.7% vs 65.3%, OR 5.84, 95% CI: 1.56 - 21.88, P=0.009), compared to ≥ 65 years age group. In addition, successful TB treatment outcomes were higher among HIV co-infected TB patients who were taking ART during TB treatment than those not taking ART (75.8% vs 23.8%, OR 11.70, 95% CI: 6.40 - 21.43, P<0.001). Patients observed by family members or friends were more likely to develop treatment success (aOR: 1.87, 95% CI: 1.13 - 3.08). Factory workers in high-risk groups had successful treatment outcomes (aOR: 1.77, 95% CI: 1.04 - 3.01). Conclusion: tuberculosis treatment success rate was low and constant over the period of three years. Death rate, loss to follow, and not evaluated were high among our study participants and above the World Health Organization (WHO) target. In unadjusted analyses, female sex, younger age, HIV co-infected taking ART, having a treatment observer, and belonging to high-risk groups, were significantly associated with successful TB treatment outcome.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".