Evidence map›Paper›PMID 41516450›Full record

ArticleSensors (Basel, Switzerland)2025

Leveraging Central Sleep Apnea Events to Validate the Measurement of Lung Volume Changes Using Thoracic Bio-Impedance.

Martine A W Knoops-Borm, Rik Vullings, Hartmut Schneider, Home PSG Validation Study Consortium Group, Sebastiaan Overeem

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Martine A W Knoops-BormDepartment of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands.ORCID 0000-0002-4173-2553
Rik VullingsDepartment of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands.ORCID 0000-0002-2392-6098
Hartmut SchneiderOnera Health, 5617 BD Eindhoven, The Netherlands.
Home PSG Validation Study Consortium Group
Sebastiaan OvereemDepartment of Electrical Engineering, Eindhoven University of Technology, 5612 AP Eindhoven, The Netherlands.ORCID 0000-0002-6445-9836

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Sleep disordered breathing can cause serious health issues, yet current diagnostic methods are cumbersome and prone to error. Thoracic electrical bio-impedance (BioZ) is a promising alternative, but it remains unclear whether the measured BioZ variations reflect lung volume changes. We leverage linear reductions in lung volume during central sleep apnea (CSA) events to assess whether BioZ measurements capture changes in lungs. BioZ signals from 92 sleep studies were analyzed using linear regression to quantify their slope and linearity (R2). Group differences were assessed, and a linear mixed-effects model was used to evaluate the impact of the body mass index (BMI), gender, and sleeping position. Welch's ANOVA showed significant differences between CSA and breathing segments. A chi-squared analysis showed that CSA events were more likely to exhibit negative slopes. The mixed-effects model found no BMI or gender effects, but the supine posture was significantly associated with more negative linear trends. These findings indicate that BioZ captures lung volume changes and that the sleeping position significantly modulates how clearly these changes appear in the signal.

Indexed as

Electric ImpedanceLungLung Volume MeasurementsSleep Apnea, CentralAdultBody Mass IndexFemaleHumansMaleThoraxbio-impedancebioimpedancebiozcentral sleep apnealung volumethoracic

Identifiers

PMID41516450
PMCPMC12787590

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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.