Evidence map›Paper›PMID 28570715›Full record

ArticlePloS one2017

Exhaled volatile substances mirror clinical conditions in pediatric chronic kidney disease.

Juliane Obermeier, Phillip Trefz, Josephine Happ, Jochen K Schubert, Hagen Staude, Dagmar-Christiane Fischer, Wolfram Miekisch

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
2.7field-weighted citation impact, top 10% 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

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 71 citations in OpenAlex.

  1. Pooled it
  2. Trial
  3. Article
  4. Review
  5. Observational
  6. Article
  7. Review
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. Review
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Microbiota and Malodor-Etiology and Management.International journal of molecular sciences · 2020
    Review
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.

Juliane ObermeierDepartment of Anesthesiology and Intensive Care Medicine, Rostock Medical Breath Research Analytics and Technologies (ROMBAT), University Medicine Rostock, Rostock, Germany.
Phillip TrefzDepartment of Anesthesiology and Intensive Care Medicine, Rostock Medical Breath Research Analytics and Technologies (ROMBAT), University Medicine Rostock, Rostock, Germany.
Josephine HappDepartment of Anesthesiology and Intensive Care Medicine, Rostock Medical Breath Research Analytics and Technologies (ROMBAT), University Medicine Rostock, Rostock, Germany.
Jochen K SchubertDepartment of Anesthesiology and Intensive Care Medicine, Rostock Medical Breath Research Analytics and Technologies (ROMBAT), University Medicine Rostock, Rostock, Germany.
Hagen StaudeDepartment of Pediatrics, University Medicine Rostock, Rostock, Germany.
Dagmar-Christiane FischerDepartment of Pediatrics, University Medicine Rostock, Rostock, Germany.
Wolfram MiekischDepartment of Anesthesiology and Intensive Care Medicine, Rostock Medical Breath Research Analytics and Technologies (ROMBAT), University Medicine Rostock, Rostock, Germany.ORCID http://orcid.org/0000-0003-1619-0315
University of Rostock · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Monitoring metabolic adaptation to chronic kidney disease (CKD) early in the time course of the disease is challenging. As a non-invasive technique, analysis of exhaled breath profiles is especially attractive in children. Up to now, no reports on breath profiles in this patient cohort are available. 116 pediatric subjects suffering from mild-to-moderate CKD (n = 48) or having a functional renal transplant KTx (n = 8) and healthy controls (n = 60) matched for age and sex were investigated. Non-invasive quantitative analysis of exhaled breath profiles by means of a highly sensitive online mass spectrometric technique (PTR-ToF) was used. CKD stage, the underlying renal disease (HUS; glomerular diseases; abnormalities of kidney and urinary tract or polycystic kidney disease) and the presence of a functional renal transplant were considered as classifiers. Exhaled volatile organic compound (VOC) patterns differed between CKD/ KTx patients and healthy children. Amounts of ammonia, ethanol, isoprene, pentanal and heptanal were higher in patients compared to healthy controls (556, 146, 70.5, 9.3, and 5.4 ppbV vs. 284, 82.4, 49.6, 5.30, and 2.78 ppbV). Methylamine concentrations were lower in the patient group (6.5 vs 10.1 ppbV). These concentration differences were most pronounced in HUS and kidney transplanted patients. When patients were grouped with respect to degree of renal failure these differences could still be detected. Ammonia accumulated already in CKD stage 1, whereas alterations of isoprene (linked to cholesterol metabolism), pentanal and heptanal (linked to oxidative stress) concentrations were detectable in the breath of patients with CKD stage 2 to 4. Only weak associations between serum creatinine and exhaled VOCs were noted. Non-invasive breath testing may help to understand basic mechanisms and metabolic adaptation accompanying progression of CKD. Our results support the current notion that metabolic adaptation occurs early during the time course of CKD.

Indexed as

AdolescentBody Mass IndexBreath TestsCase-Control StudiesChildChild, PreschoolCross-Sectional StudiesFemaleHumansMass SpectrometryRenal Insufficiency, ChronicVolatile Organic CompoundsVolatile Organic Compounds

Identifiers

PMID28570715
PMCPMC5453591
OpenAlexW2620878032

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.