The mixed strains infection phenomenon is a major problem posing serious challenges in control of tuberculosis (TB). In patients with mixed infection, several different strains of Mycobacterium tuberculosis can be isolated simultaneously. Although different genotyping methods and various molecular approaches can be employed for detection of mixed infection in clinical samples, the MIRU-VNTR technique is more sensitive with higher discriminative power than many widely used techniques. Furthermore, the recent introduction of whole genome sequencing (WGS) promises to reveal more details about mixed infection with high resolution. WGS has been used for detection of mixed infection with high sensitivity and discriminatory, but the technology is currently limited to developed countries. Mixed infection may involve strains with different susceptibility patterns, which may alter the treatment outcome. In this report, we review the current concepts of mixed strains infection and also infection involving strains with a different susceptibility pattern in TB. We evaluate the importance of identifying mixed infection for diagnosis as well as treatment and highlight the accuracy and clinical utility of direct genotyping of clinical specimens.
This research output has an Altmetric Attention Score of 21. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 August 2021.
All research outputs
#2,286,581
of 34,372,222 outputs
Outputs from Tuberculosis (formerly Tubercle and Lung Disease)
#34
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Outputs of similar age
#32,864
of 353,979 outputs
Outputs of similar age from Tuberculosis (formerly Tubercle and Lung Disease)
#1
of 31 outputs
Altmetric has tracked 34,372,222 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,250 research outputs from this source. They receive a mean Attention Score of 4.9. This one has done particularly well, scoring higher than 97% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 353,979 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 31 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.
