Evidence map›Paper›PMID 23118938›Full record

ArticlePloS one2012

Functional lung imaging during HFV in preterm rabbits.

Jordan Thurgood, Stuart Hooper, Melissa Siew, Megan Wallace, Stephen Dubsky, Marcus Kitchen, R Aidan Jamison, Richard Carnibella, Andreas Fouras

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 21% 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

8 citing papers in PubMed, 17 citations in OpenAlex.

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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

9 authors at 2 institutions in 1 country.

Jordan ThurgoodDepartment of Mechanical and Aerospace Engineering, Monash University, Melbourne, Victoria, Australia. jordan.thurgood@monash.edu
Stuart Hooper
Melissa Siew
Megan Wallace
Stephen Dubsky
Marcus Kitchen
R Aidan Jamison
Richard Carnibella
Andreas Fouras
Monash University · AUMonash Institute of Medical Research · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although high frequency ventilation (HFV) is an effective mode of ventilation, there is limited information available in regard to lung dynamics during HFV. To improve the knowledge of lung function during HFV we have developed a novel lung imaging and analysis technique. The technique can determine complex lung motion information in vivo with a temporal resolution capable of observing HFV dynamics. Using high-speed synchrotron based phase contrast X-ray imaging and cross-correlation analysis, this method is capable of recording data in more than 60 independent regions across a preterm rabbit lung in excess of 300 frames per second (fps). This technique is utilised to determine regional intra-breath lung mechanics of preterm rabbit pups during HFV. Whilst ventilated at fixed pressures, each animal was ventilated at frequencies of 1, 3, 5 and 10 Hz. A 50% decrease in delivered tidal volume was measured at 10 Hz compared to 1 Hz, yet at the higher frequency a 500% increase in minute activity was measured. Additionally, HFV induced greater homogeneity of lung expansion activity suggesting this ventilation strategy potentially minimizes tissue damage and improves gas mixing. The development of this technique permits greater insight and further research into lung mechanics and may have implications for the improvement of ventilation strategies used to support severe pulmonary trauma and disease.

Indexed as

High-Frequency VentilationAnimalsAnimals, NewbornFemaleLungLung Volume MeasurementsPregnancyRabbitsRadiographyRespiratory RateRheology

Identifiers

PMID23118938
PMCPMC3484156
OpenAlexW2053898470

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.