Evidence map›Paper›PMID 39537659›Full record

ArticleScientific reports2024

Kinematic signature of high risk labored breathing revealed by novel signal analysis.

William B Ashe, Brendan D McNamara, Swet M Patel, Julia N Shanno, Sarah E Innis, Camille J Hochheimer, Andrew J Barros, Ronald D Williams, Sarah J Ratcliffe, J Randall Moorman and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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

11 authors.

William B AsheDepartment of Electrical and Computer Engineering, University of Virginia, Charlottesville, USA.
Brendan D McNamara *Department of Medicine, University of Virginia, Charlottesville, USA.
Swet M Patel *Department of Medicine, University of Virginia, Charlottesville, USA.
Julia N Shanno *Department of Biomedical Engineering, University of Virginia, Charlottesville, USA.
Sarah E Innis *Department of Biomedical Engineering, University of Virginia, Charlottesville, USA.
Camille J HochheimerDepartment of Public Health Sciences, University of Virginia, Charlottesville, USA.
Andrew J BarrosDepartment of Medicine, University of Virginia, Charlottesville, USA.
Ronald D WilliamsDepartment of Electrical and Computer Engineering, University of Virginia, Charlottesville, USA.
Sarah J RatcliffeDepartment of Public Health Sciences, University of Virginia, Charlottesville, USA.
J Randall MoormanDepartment of Medicine, University of Virginia, Charlottesville, USA.
Shrirang M GadreyDepartment of Medicine, University of Virginia, Charlottesville, USA. smg7t@virginia.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Breathing patterns (respiratory kinematics) contain vital prognostic information. This dimension of physiology is not captured by conventional vital signs. We sought to determine the feasibility and utility of quantifying respiratory kinematics. Using inertial sensors, we analyzed upper rib, lower rib, and abdominal motion of 108 patients with respiratory symptoms during a hospital encounter (582 two-minute recordings). We extracted 34 features based on an explainable correspondence with well-established breathing patterns. K-means clustering revealed that respiratory kinematics had three dimensions apart from the respiratory rate. We represented these dimensions using respiratory rate variability, respiratory alternans (rib-predominant breaths alternating with abdomen-predominant ones), and recruitment of accessory muscles (increased upper rib excursion). Latent profile analysis of the kinematic measures revealed two profiles consistent with the established clinical constructs of labored and unlabored breathing. In logistic regression, the labored breathing profile improved model discrimination for critical illness beyond the Sequential Organ Failure Assessment (SOFA) score (AUROC 0.77 v/s 0.72; p = 0.02). These findings quantitatively confirm the prior understanding that the respiratory rate alone does not adequately represent the complexity of respiratory kinematics; they demonstrate that high-dimensional signatures of labored breathing can be quantified in routine practice settings, and they can improve predictions of clinical deterioration.

Indexed as

RespirationAdultAgedBiomechanical PhenomenaFemaleHumansMaleMiddle AgedRespiratory MechanicsRespiratory RateSignal Processing, Computer-AssistedBiomedical EngineeringEarly Warning ScoresPhysiological MonitoringRespiratory FailureWork of Breathing

Identifiers

PMID39537659
PMCPMC11561144

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Registered trials

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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.