Evidence map›Paper›PMID 38910962›Full record

ArticleFrontiers in pediatrics2024

A computerized tool for the systematic visual quality assessment of infant multiple-breath washout measurements.

Marc-Alexander Oestreich, Isabelle Doswald, Yasmin Salem, Noëmi Künstle, Florian Wyler, Bettina S Frauchiger, Anne-Christianne Kentgens, Philipp Latzin, Sophie Yammine

Abstract read
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Article in Frontiers in pediatrics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

9 authors.

Marc-Alexander OestreichDivision of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Isabelle DoswaldDivision of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Yasmin SalemDivision of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Noëmi KünstleUniversity Children's Hospital Basel (UKBB), University of Basel, Basel, Switzerland.
Florian WylerDivision of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Bettina S FrauchigerDivision of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Anne-Christianne KentgensDivision of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Philipp LatzinDivision of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Sophie YammineDivision of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Multiple-breath washout (MBW) is a sensitive method for assessing lung volumes and ventilation inhomogeneity in infants, but remains prone to artefacts (e.g., sighs). There is a lack of tools for systematic retrospective analysis of existing datasets, and unlike N Aim: We aimed to develop a computer-based tool for systematic evaluation of visual QC criteria of SF Methods: We developed a software package for visualization of raw Spiroware (Eco Medics AG, Switzerland) and signal processed WBreath (ndd Medizintechnik AG, Switzerland) SF Results: Our tool visualizes MBW signals and provides the user with (i) display options (e.g., zoom), (ii) options for a systematic QC assessment [e.g., decision to accept or reject, identification of artefacts (leak, sigh, irregular breathing pattern, breath hold), and comments], and (iii) additional information (e.g., automatic identification of sighs). Reviewer agreement was good using pre-defined QC criteria (κ 0.637-0.725). Differences in the decision to accept/reject had no substantial effect on MBW outcomes. Conclusion: Our visual quality control tool supports a systematic retrospective analysis of existing data sets. Based on predefined QC criteria, even inexperienced users can achieve comparable MBW results.

Indexed as

breathing patternfunctional residual capacityinfant lung functionlung clearance indexpulmonary function testingquality controlSF6-MBWsigh

Identifiers

PMID38910962
PMCPMC11191423

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