Evidence map›Paper›PMID 34893521›Full record

ArticleBMJ open respiratory research2021

New method to measure interbreath intervals in infants for the assessment of apnoea and respiration.

Tricia Adjei, Ryan Purdy, João Jorge, Eleri Adams, Miranda Buckle, Ria Evans Fry, Gabrielle Green, Chetan Patel, Richard Rogers, Rebeccah Slater and 3 more

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

Article in BMJ open respiratory research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
1.6field-weighted citation impact, top 15% 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

12 citing papers in PubMed, 17 citations in OpenAlex.

  1. Trial
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  6. Review
  7. Apnoea suppresses brain activity in infants.Imaging neuroscience (Cambridge, Mass.) · 2024
    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

13 authors at 2 institutions in 1 country.

Tricia AdjeiDepartment of Paediatrics, University of Oxford, Oxford, UK.
Ryan Purdy *Department of Paediatrics, University of Oxford, Oxford, UK.
João Jorge *Institute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.
Eleri AdamsNewborn Care Unit, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Miranda BuckleDepartment of Paediatrics, University of Oxford, Oxford, UK.
Ria Evans FryDepartment of Paediatrics, University of Oxford, Oxford, UK.
Gabrielle GreenDepartment of Paediatrics, University of Oxford, Oxford, UK.
Chetan PatelDepartment of Ophthalmology, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Richard RogersDepartment of Anaesthetics, Oxford University Hospitals NHS Foundation Trust, Oxford, UK.
Rebeccah SlaterDepartment of Paediatrics, University of Oxford, Oxford, UK.
Lionel TarassenkoInstitute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.
Mauricio VillarroelInstitute of Biomedical Engineering, Department of Engineering Science, University of Oxford, Oxford, UK.
Caroline HartleyDepartment of Paediatrics, University of Oxford, Oxford, UK caroline.hartley@paediatrics.ox.ac.uk.ORCID 0000-0002-7981-0836
University of Oxford · GBOxford University Hospitals NHS Trust · GB

Funding

Wellcome TrustWellcome Trust 213486/Z/18/Z
6 · The paper itself

Abstract

backgroundRespiratory disorders, including apnoea, are common in preterm infants due to their immature respiratory control compared with term-born infants. However, our inability to accurately measure respiratory rate in hospitalised infants results in unreported episodes of apnoea and an incomplete picture of respiratory activity.

methodsWe develop, validate and use a novel algorithm to identify interbreath intervals (IBIs) and apnoeas in preterm infants. In 42 preterm infants (1600 hours of recordings), we assess IBIs from the chest electrical impedance pneumograph using an adaptive amplitude threshold for the detection of breaths. The algorithm is refined by comparing its accuracy with clinically observed breaths and pauses in breathing. We develop an automated classifier to differentiate periods of true apnoea from artefactually low amplitude signal. We assess the performance of this algorithm in the detection of morphine-induced respiratory depression. Finally, we use the algorithm to investigate whether retinopathy of prematurity (ROP) screening alters the IBI distribution.

resultsIndividual breaths were detected with a false-positive rate of 13% and a false-negative rate of 12%. The classifier identified true apnoeas with an accuracy of 93%. As expected, morphine caused a significant shift in the IBI distribution towards longer IBIs. Following ROP screening, there was a significant increase in pauses in breathing that lasted more than 10 s (t-statistic=1.82, p=0.023). This was not reflected by changes in the monitor-derived respiratory rate and no episodes of apnoea were recorded in the medical records.

conclusionsWe show that our algorithm offers an improved method for the identification of IBIs and apnoeas in preterm infants. Following ROP screening, increased respiratory instability can occur even in the absence of clinically significant apnoeas. Accurate assessment of infant respiratory activity is essential to inform clinical practice.

Indexed as

ApneaInfant, PrematureHumansInfantInfant, NewbornRespirationrespiratory measurement

Identifiers

PMID34893521
PMCPMC8666899
OpenAlexW4200241999

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.