Estimation of the burden of bacteriologically positive Tuberculosis among Adults in Kashmir: A baseline for future surveys in the Valley
Bibliographic record
Abstract
BACKGROUND: India has the highest burden of both Tuberculosis and MDR-Tuberculosis based on estimates reported in the Global Tuberculosis Report 2016. The estimates have been revised upwards based on the newer evidence, and the current study was done to estimate the prevalence of bacteriologically positive pulmonary Tuberculosis among the adult population and to provide baseline information for future measurements of Tuberculosis burden and trends. METHODS: A cluster-based sampling design was adopted in 10 districts of Kashmir valley in India. Assuming a prevalence of 217 per lakh population, a design effect of 2.5, a relative precision of 0.25% and the expected participation rate of 80%, a sample size of 49,716 was achieved. A total of 67 clusters were identified where each cluster had 750 subjects aged ≥15 years, and eligible individuals were questioned for pulmonary symptoms suggestive of Tuberculosis. RESULTS: Of the total 42,805 that were interviewed, 3.85% had pulmonary Tuberculosis symptoms. A total of 1539 sputum samples were collected from symptomatic and 1351 chest X- rays were done. Cartridge based nucleic acid amplification test (CBNAAT) tests were done on individuals with suspicious X-ray findings. The prevalence of bacteriologically positive pulmonary Tuberculosis was found to be 147 per 100,000 population. Females are affected more than males, and the age of female Tuberculosis patients is less than that of males. CONCLUSION: The study is the first survey of its kind providing a baseline for further research in the state. CBNAAT is going to be game-changer which surmounts the drawbacks of sputum smear microscopy.
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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 | 0.003 | 0.003 |
| 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".