Prevalence and Treatment Outcome of Smear Positive Pulmonary Tuberculosis Patients in General Population of District Swat, Pakistan
Bibliographic record
Abstract
Mycobacterium tuberculosis is responsible for causing TB disease. Primarily it infects the lungs, which is known as pulmonary tuberculosis when the disease disseminates to other parts of the body known as extra-pulmonary tuberculosis. Recently, WHO ranked Pakistan the fifth TB endemic country in the world. The objective of this study was to evaluate the prevalence and treatment outcome of smear-positive PTB patients among all forms of TB registered with TB centre at District swat. Two-year data from January 2016 to December 2017 were reviewed. In this study period, complete information of total 1392 cases of pulmonary tuberculosis (PTB) were reviewed. Of these, 626(45%) were founded to be males, while 766(55%) were females with an overall mean age of 32.9 years. In the age-wise distribution, this study showed a high number of cases, 657(47.3%) in the economic age group from 16-30. In contrast, the lowest number of cases, 112(8%), were recorded in the 60 years older adults. Of the two-year study period, 745(53.5%) patients were recorded in 2017, while 647(46.5%) patients were recorded in 2016. The overall prevalence rate in the 100,000 population was calculated to be 58.8(0.058%). Based on seasonality, high cases notification was reported in quarter 2 (April- June), while lower cases notification was recorded in quarter 4 (October-December). Treatment outcome record showed that 861(61.9%) were cured, 452(32.5%) treatment completed, 34(2.4%) died, 13(0.9%) treatment failed, 32 (2.3%) lost to follow up, and no patient was transferred to other facilities. In conclusion, still, PTB is prevalent in the district, and the overall treatment success rate is low.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".