Mycobacterium tuberculosis Complex Drug Resistance in a High Tuberculosis Incidence Area from the WHO Eastern Mediterranean Region
Bibliographic record
Abstract
PURPOSE: The incidence of tuberculosis (TB) in Golestan province of Iran has been ranked 10th among countries of World Health Organization (WHO) Eastern Mediterranean Region. The province is residence of ethnically heterogeneous groups. However, there are limited data on Mycobacterium tuberculosis drug resistance in this province. The main aim of this study was to determine the resistance profile of M. tuberculosis complex (MTBC) isolates to first-line anti-TB drugs. METHODS: The clinical specimens were collected from 11807 cases diagnosed during this study. MTBC isolates were tested for susceptibility to first-line anti-TB drugs. RESULTS: A total of 176 new cases were diagnosed as culture positive for MTBC. There was one case that had multidrug-resistant (MDR) isolate and 18 (10.2%) had isolates that were resistant to at least one drug (any drug resistant). Resistance to streptomycin and isoniazid was noted in 15 (8.5%) and 5 isolates (2.8%), respectively. Also, a statistically significant association was observed between age groups and any drug resistance pattern (p = 0.022): 1-24 years vs. 25-45 years (p = 0.033), 25-45 years vs. >65 years (p = 0.010), 46-65 years vs. >65 years (p = 0.050). One third of any drug resistant isolates were obtained from TB patients of Persian ethnic group. CONCLUSION: Despite the high incidence of TB, the rate of MDR-TB in Golestan province was similar to those reported by WHO for Iranian new cases from other regions. One-tenth of the studied isolates showed any drug resistance pattern. This rate of any drug resistance implies the possibility of initial resistance of MTBC isolates circulating in this region.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".