ReviewYonsei medical journal2007
Current issues on molecular and immunological diagnosis of tuberculosis.
Review in Yonsei medical journal, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Systematic review and meta-analysis of antigen detection tests for the diagnosis of tuberculosis.Clinical and vaccine immunology : CVI · 2011Pooled it
- Production of MPT-64 recombinant protein from virulent strain ofIranian journal of veterinary research · 2018Article
- Accuracy of the QuantiFERON-TB Gold in Tube for diagnosing tuberculosis in a young pediatric population previously vaccinated with Bacille Calmette-Guérin .Revista paulista de pediatria : orgao oficial da Sociedade de Pediatria de Sao Paulo · 2014Article
- Evaluation of immunological parameters in purified protein derivative positive tuberculin workers.Iranian journal of basic medical sciences · 2013Article
- Expression and evaluation of Chikungunya virus E1 and E2 envelope proteins for serodiagnosis of Chikungunya virus infection.Yonsei medical journal · 2008Article
- Pulmonary tuberculosis in a young pregnant female: challenges in diagnosis and management.Infectious diseases in obstetrics and gynecology · 2008Article
- Molecular findings and approaches spotlighting Mycobacterium bovis persistence in cattle.Veterinary researchReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Laboratory diagnosis of tuberculosis (TB) traditionally relies on smear microscopy and culture of Mycobacterium tuberculosis from clinical samples. With recent advances in technology, there have been numerous efforts to develop new diagnostic tests for TB that overcome the low sensitivity and specificity and long turnover time associated with current diagnostic tests. Molecular biological tests based on nucleic acid amplification have brought an unprecedented opportunity for the rapid and specific detection of M. tuberculosis from clinical specimens. With automated sequencing analysis, species identification of mycobacteria is now easier and more accurate than with conventional methods, and rapid detection of mutations in the genes associated with resistance to TB drugs provides early information on the potential drug resistance for each clinical isolate or for clinical samples. In addition, immunological tests for the detection of M. tuberculosis antigens and antibodies to the antigens have been explored to identify individuals at risk of developing TB or with latent TB infection (LTBI). The recent introduction of commercial IFN-gamma assay kits for the detection of LTBI provides a new approach for TB control even in areas with a high incidence of TB. However, these molecular and immunological tools still require further evaluation using large scale cohort studies before implementation in TB control programs.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.