Prevalence of Mycobacterium tuberculosis Infection in Suspected Patients in a Teaching Hospital in Northeastern Iran: A Cross-Sectional Study
Bibliographic record
Abstract
Background: Mycobacterium tuberculosis is an infectious agent responsible for major health problems and a large number of mortalities. The prevalence of Mycobacterium tuberculosis infection varies across countries. Knowing the infection prevalence can aid in improving public health and reduce the associated costs. The aim of this study was to determine the prevalence of tuberculosis (TB) infection in suspected cases in Mashhad, Iran.Methods: All the clinical specimens suspected of TB infection were sent to a laboratory for diagnosis during -March 2017 to March 2018. The samples were analyzed microscopically using Ziehl–Neelsen staining, by polymerase chain reaction (PCR) to identify the Mycobacterium tuberculosis species using IS6110 primers, and the samples were also grown on Lowenstein–Jensen medium.Results: Of 2,755 clinical samples analyzed, 153 (5.55%) were identified as Mycobacterium tuberculosis-positive, of which 54.9% originated from females and 45.1% from males. The highest rate of infection was observed in spring, especially in May (15%). Most TB cases were found in patients in VIP (43.1%), thorax (17%), and internal (15%) wards. TB infection was mostly detected in bronchial tube (70%) and sputum (23.5%) samples. The most common positive smear was 1+ (36%). Of the 153 cases, (147) 96.1% were culture –positive and 2% were PCR-negative also 84.3% were smear –positive.Conclusion: The highest rate of infection occurred in spring, when the number of religious tourists entering the city was at its peak. Considering the sensitive location of this city, awareness regarding TB status can lead to improved health in the community and development of basic strategies to control and eliminate the transmission of this infection from Mashhad to other areas.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.002 |
| 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".