↓ Skip to main content

Systematic review regarding metabolic profiling for improved pathophysiological understanding of disease and outcome prediction in respiratory infections

Overview of attention for article published in Respiratory Research, October 2015
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (51st percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 X users
facebook
1 Facebook page
googleplus
1 Google+ user

Citations

dimensions_citation
34 Dimensions

Readers on

mendeley
89 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Systematic review regarding metabolic profiling for improved pathophysiological understanding of disease and outcome prediction in respiratory infections
Published in
Respiratory Research, October 2015
DOI 10.1186/s12931-015-0283-6
Pubmed ID
Authors

Manuela Nickler, Manuel Ottiger, Christian Steuer, Andreas Huber, Janet Byron Anderson, Beat Müller, Philipp Schuetz

Abstract

Metabolic profiling through targeted quantification of a predefined subset of metabolites, performed by mass spectrometric analytical techniques, allows detailed investigation of biological pathways and thus may provide information about the interaction of different organic systems, ultimately improving understanding of disease risk and prognosis in a variety of diseases. Early risk assessment, in turn, may improve patient management in regard to cite-of-care decisions and treatment modalities. Within this review, we focus on the potential of metabolic profiling to improve our pathophysiological understanding of disease and management of patients. We focus thereby on lower respiratory tract infections (LRTI) including community-acquired pneumonia (CAP) and chronic obstructive pulmonary disease (COPD), an important disease responsible for high mortality, morbidity and costs worldwide. Observational data from numerous clinical and experimental studies have provided convincing data linking metabolic blood biomarkers such as lactate, glucose or cortisol to patient outcomes. Also, identified through metabolomic studies, novel innovative metabolic markers such as steroid hormones, biogenic amines, members of the oxidative status, sphingo- and glycerophospholipids, and trimethylamine-N-oxide (TMAO) have shown promising results. Since many uncertainties remain in predicting mortality in these patients, further prospective and retrospective observational studies are needed to uncover metabolic pathways responsible for mortality associated with LRTI. Improved understanding of outcome-specific metabolite signatures in LRTIs may optimize patient management strategies, provide potential new targets for future individual therapy, and thereby improve patients' chances for survival.

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 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Unknown 88 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 16%
Student > Ph. D. Student 12 13%
Researcher 10 11%
Student > Bachelor 7 8%
Student > Postgraduate 7 8%
Other 14 16%
Unknown 25 28%
Readers by discipline Count As %
Medicine and Dentistry 20 22%
Pharmacology, Toxicology and Pharmaceutical Science 7 8%
Nursing and Health Professions 7 8%
Biochemistry, Genetics and Molecular Biology 6 7%
Agricultural and Biological Sciences 5 6%
Other 18 20%
Unknown 26 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 October 2015.
All research outputs
#14,914,476
of 25,374,647 outputs
Outputs from Respiratory Research
#1,499
of 3,062 outputs
Outputs of similar age
#138,456
of 291,054 outputs
Outputs of similar age from Respiratory Research
#24
of 45 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,062 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.9. This one is in the 48th percentile – i.e., 48% 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 291,054 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.
We're also able to compare this research output to 45 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.