Understanding how geographic, demographic and treatment history impact health outcomes of patients with multi-drug-resistant tuberculosis in Pakistan, 2014–2017
Bibliographic record
Abstract
Tuberculosis (TB) is one of the top 10 leading causes of morbidity and mortality worldwide [1]. In 2017, approximately 10 million people were infected with TB and 1.3 million patients faced mortality [1]. Patients with active TB can infect up to 10-15 people over a year. There is a greater risk of transmission in overcrowded areas with limited air ventilation including large family units, prisons and slums [1, 2]. Without proper diagnosis and treatment, roughly 45% of non-HIV positive TB patients face mortality [1]. With the help of global organizations and national TB treatment and control programmes, the global incidence of TB is declining by approximately 2% each year [1]. The World Health Organization (WHO) TB-strategy aims to end the TB epidemic and encourages partners to fund national TB programmes to improve diagnosis and treatment of TB. The goal is to ultimately decrease death rates by 90% and decrease incidence rates by 80% [1]. To achieve these goals, the decline in TB incidence needs to reach approximately 4-5% per year [1]. The WHO 2018 TB report identified multidrug resistant TB (MDR-TB) as the leading factor hindering that goal [1]. The incidence and spread of MDR-TB has drastically increased, where approximately 558 000 new cases of MDR-TB were diagnosed in 2017 causing more than 230 000 deaths globally [1]. MDR-TB is identified by resistance to the two most powerful anti-TB treatment drugs including isoniazid and rifampicin [3]. Patients with MDR-TB are required to start second-line anti-TB drugs (SLDs), which are limited, expensive, less effective and more toxic [1,2]. Therapy duration is one of the major limitations of second-line treatments, which may require up to two years of consistent use. Since TB affects mostly developing countries, long treatment durations and associated costs become a major challenge. In 2015, 15% of new TB cases were reported as MDR-TB, which drastically increased to 24% by 2017 [1]. Even with significant improvements in molecular tests and diagnostic methods, MDR-TB is still on the rise where the success rate of treatments is between 50 and 60% [1]. Additional characteristics including socioeconomic and sociocultural factors need to be considered when targeting and treating patients with MDR-TB.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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".