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‘”Why me, why now?” Using clinical immunology and epidemiology to explain who gets nontuberculous mycobacterial infection

Overview of attention for article published in BMC Medicine, March 2016
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Title
‘”Why me, why now?” Using clinical immunology and epidemiology to explain who gets nontuberculous mycobacterial infection
Published in
BMC Medicine, March 2016
DOI 10.1186/s12916-016-0606-6
Pubmed ID
Authors

M. Alexandra Lake, Lyn R. Ambrose, Marc C. I. Lipman, David M. Lowe

Abstract

The prevalence of nontuberculous mycobacterial (NTM) disease is rising. An understanding of known risk factors for disease sheds light on the immunological and physical barriers to infection, and how and why they may be overcome. This review focuses on human NTM infection, supported by experimental and in vitro data of relevance to the practising clinician who seeks to understand why their patient has NTM infection and how to further investigate. First, the underlying immune response to NTM disease is examined. Important insights regarding NTM disease susceptibility come from nature's own knockouts, the primary immune deficiency disorders. We summarise the current knowledge surrounding interferon-gamma (IFNγ)-interleukin-12 (IL-12) axis abnormalities, followed by a review of phagocytic defects, T cell lymphopenia and rarer genetic conditions known to predispose to NTM disease. We discuss how these define key immune pathways involved in the host response to NTM. Iatrogenic immunosuppression is also important, and we evaluate the impact of novel biological therapies, as well as bone marrow transplant and chemotherapy for solid organ malignancy, on the epidemiology and presentation of NTM disease, and discuss the host defence dynamics thus revealed. NTM infection and disease in the context of other chronic illnesses including HIV and malnutrition is reviewed. The role of physical barriers to infection is explored. We describe how their compromise through different mechanisms including cystic fibrosis, bronchiectasis and smoking-related lung disease can result in pulmonary NTM colonisation or infection. We also summarise further associations with host factors including body habitus and age. We use the presented data to develop an over-arching model that describes human host defences against NTM infection, where they may fail, and how this framework can be applied to investigation in routine clinical practice.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 151 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 <1%
Unknown 150 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 17%
Student > Master 21 14%
Student > Ph. D. Student 16 11%
Other 16 11%
Student > Doctoral Student 12 8%
Other 29 19%
Unknown 32 21%
Readers by discipline Count As %
Medicine and Dentistry 52 34%
Immunology and Microbiology 23 15%
Biochemistry, Genetics and Molecular Biology 14 9%
Agricultural and Biological Sciences 9 6%
Nursing and Health Professions 3 2%
Other 15 10%
Unknown 35 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 18 June 2018.
All research outputs
#15,365,885
of 22,858,915 outputs
Outputs from BMC Medicine
#3,059
of 3,438 outputs
Outputs of similar age
#180,211
of 300,567 outputs
Outputs of similar age from BMC Medicine
#43
of 52 outputs
Altmetric has tracked 22,858,915 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,438 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.6. This one is in the 8th percentile – i.e., 8% of its peers scored the same or lower than it.
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 300,567 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 52 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.