Evidence map›Paper›PMID 38559568›Full record

ArticlePhotoacoustics2024

An inexpensive UV-LED photoacoustic based real-time sensor-system detecting exhaled trace-acetone.

Jonas Pangerl, Pritam Sukul, Thomas Rück, Patricia Fuchs, Stefan Weigl, Wolfram Miekisch, Rudolf Bierl, Frank-Michael Matysik

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Photoacoustics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

3 citing papers in PubMed, 13 citations in OpenAlex.

  1. Article
  2. Article
  3. 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

8 authors at 2 institutions in 1 country.

Jonas PangerlSensorik-ApplikationsZentrum (SappZ), Regensburg University of Applied Sciences, Regensburg 93053, Germany.
Pritam SukulRostock Medical Breath Analytics and Technologies (RoMBAT), Dept. of Anaesthesiology, Intensive Care Medicine and Pain Therapy, University Medicine Rostock, Rostock 18057, Germany.
Thomas RückSensorik-ApplikationsZentrum (SappZ), Regensburg University of Applied Sciences, Regensburg 93053, Germany.
Patricia FuchsRostock Medical Breath Analytics and Technologies (RoMBAT), Dept. of Anaesthesiology, Intensive Care Medicine and Pain Therapy, University Medicine Rostock, Rostock 18057, Germany.
Stefan WeiglSensorik-ApplikationsZentrum (SappZ), Regensburg University of Applied Sciences, Regensburg 93053, Germany.
Wolfram MiekischRostock Medical Breath Analytics and Technologies (RoMBAT), Dept. of Anaesthesiology, Intensive Care Medicine and Pain Therapy, University Medicine Rostock, Rostock 18057, Germany.
Rudolf BierlSensorik-ApplikationsZentrum (SappZ), Regensburg University of Applied Sciences, Regensburg 93053, Germany.
Frank-Michael MatysikInstitute of Analytical Chemistry, Chemo- and Biosensing, University of Regensburg, Regensburg 93053, Germany.
Regensburg University of Applied Sciences · DEUniversity of Regensburg · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this research we present a low-cost system for breath acetone analysis based on UV-LED photoacoustic spectroscopy. We considered the end-tidal phase of exhalation, which represents the systemic concentrations of volatile organic compounds (VOCs) - providing clinically relevant information about the human health. This is achieved via the development of a CO

Indexed as

AcetoneBreath analysisPhotoacoustic spectroscopyReal-time mass-spectrometryUV-LED

Identifiers

PMID38559568
PMCPMC10973644
OpenAlexW4393071784

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.