ArticleBMC microbiology2022
Impact of pathobiological diversity of Mycobacterium tuberculosis on clinical features and lethal outcome of tuberculosis.
Article in BMC microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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
6 citing papers in PubMed.
- Association between human genomes and mycobacterial genomes contributes to severity and transmissibility of pulmonary tuberculosis.iScience · 2026Article
- Article
- Genetic Diversity ofPathogens (Basel, Switzerland) · 2024Article
- Genetic diversity ofHeliyon · 2023Article
- Insight into pathogenomics and phylogeography of hypervirulent and highly-lethal Mycobacterium tuberculosis strain cluster.BMC infectious diseases · 2023Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMycobacterium tuberculosis population in Russia is dominated by the notorious Beijing genotype whose major variants are characterized by contrasting resistance and virulence properties. Here we studied how these strain features could impact the progression of pulmonary tuberculosis (TB) concerning clinical manifestation and lethal outcome.
resultsThe study sample included 548 M. tuberculosis isolates from 548 patients with newly diagnosed pulmonary TB in Omsk, West Siberia, Russia. Strains were subjected to drug susceptibility testing and genotyping to detect lineages, sublineages, and subtypes (within Beijing genotype). The Beijing genotype was detected in 370 (67.5%) of the studied strains. The strongest association with multidrug resistance (MDR) was found for epidemic cluster Beijing B0/W148 (modern sublineage) and two recently discovered MDR clusters 1071-32 and 14717-15 of the ancient Beijing sublineage. The group of patients infected with hypervirulent and highly lethal (in a mouse model) Beijing 14717-15 showed the highest rate of lethal outcome (58.3%) compared to Beijing B0/W148 (31.4%; P = 0.06), Beijing Central Asian/Russian (29.7%, P = 0.037), and non-Beijing (15.2%, P = 0.001). The 14717-15 cluster mostly included isolates from patients with infiltrative but not with fibrous-cavernous and disseminated TB. In contrast, a group infected with low virulent 1071-32-cluster had the highest rate of fibrous-cavernous TB, possibly reflecting the capacity of these strains for prolonged survival and chronicity of the TB process.
conclusionsThe group of patients infected with hypervirulent and highly lethal in murine model 14717-15 cluster had the highest proportion of the lethal outcome (58.3%) compared to the groups infected with Beijing B0/W148 (31.4%) and non-Beijing (15.2%) isolates. This study carried out in the TB high-burden area highlights that not only drug resistance but also strain virulence should be considered in the implementation of personalized TB treatment.
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.