Evidence map›Paper›PMID 26471192›Full record

SynthesisRespiratory research2015

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

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

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in Respiratory research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
2.8field-weighted citation impact, top 9% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 42 citations in OpenAlex.

  1. Pooled it
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  4. Review
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  10. Review
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  12. Observational
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  18. A Study on Tissue-Specific Metabolite Variations inMolecules (Basel, Switzerland) · 2019
    Article
  19. Observational
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Manuela NicklerMedical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland. Manuela.Nickler@ksa.ch.
Manuel OttigerMedical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland. Manuel.Ottiger@ksa.ch.
Christian SteuerDepartment of Laboratory Medicine, Kantonsspital Aarau, Aarau, Switzerland. Christian.Steuer@ksa.ch.
Andreas HuberDepartment of Laboratory Medicine, Kantonsspital Aarau, Aarau, Switzerland. Andreas.Huber@ksa.ch.
Janet Byron AndersonPrincipal, Medical Linguistics Consulting, North Olmsted, OH, USA. medlinguistics@sbcglobal.net.
Beat MüllerMedical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland. happy.mueller@unibas.ch.
Philipp SchuetzMedical University Department, Division of General Internal and Emergency Medicine, Kantonsspital Aarau, Aarau, Switzerland. schuetzph@gmail.com.
Kantonsspital Aarau · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

MetabolomicsAnimalsBiomarkersEnergy MetabolismHumansLipid MetabolismLungOxidative StressPredictive Value of TestsPrognosisRespiratory Tract InfectionsRisk AssessmentRisk FactorsBiomarkers

Identifiers

PMID26471192
PMCPMC4608151
OpenAlexW2118222200

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.