Evidence map›Paper›PMID 38273120›Full record

ArticleIntensive care medicine experimental2024

Estimation of normal lung weight index in healthy female domestic pigs.

Antonio Fioccola, Rosmery Valentina Nicolardi, Tommaso Pozzi, Isabella Fratti, Federica Romitti, Francesca Collino, Verena Reupke, Gianluigi Li Bassi, Alessandro Protti, Alessandro Santini and 5 more

Open access · goldAbstract read
In one paragraph

Article in Intensive care medicine experimental, 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
0.3field-weighted citation impact, top 48% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. Review
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

15 authors at 10 institutions in 4 countries.

Antonio Fioccola *Department of Health Sciences, University of Florence, Florence, Italy.
Rosmery Valentina Nicolardi *IRCCS San Raffaele Scientific Institute, Milan, Italy.
Tommaso PozziDepartment of Anesthesiology, University Medical Center Göttingen, Göttingen, Germany.
Isabella FrattiDepartment of Anesthesiology, University Medical Center Göttingen, Göttingen, Germany.
Federica RomittiDepartment of Anesthesiology, University Medical Center Göttingen, Göttingen, Germany.
Francesca CollinoDepartment of Surgical Sciences, University of Turin, Turin, Italy.
Verena ReupkeDepartment of Experimental Animal Medicine, University of Göttingen, Göttingen, Germany.
Gianluigi Li BassiCritical Care Research Group, The Prince Charles Hospital, Brisbane, QLD, Australia.
Alessandro ProttiDepartment of Biomedical Sciences, Humanitas University, Pieve Emanuele, Milan, Italy.
Alessandro SantiniDepartment of Anesthesia and Intensive Care Units, IRCCS Humanitas Research Hospital, Rozzano, Milan, Italy.
Massimo CressoniUnit of Radiology, IRCCS, Policlinico San Donato, San Donato Milanese, Milan, Italy.
Mattia BusanaDepartment of Anesthesiology, University Medical Center Göttingen, Göttingen, Germany.
Onnen MoererDepartment of Anesthesiology, University Medical Center Göttingen, Göttingen, Germany.
Luigi CamporotaDepartment of Adult Critical Care Guy's & St Thomas' NHS Foundation Trust, London, UK.
Luciano GattinoniDepartment of Anesthesiology, University Medical Center Göttingen, Göttingen, Germany. gattinoniluciano@gmail.com.ORCID http://orcid.org/0000-0001-5380-2494
Universitätsmedizin Göttingen · DEUniversity of Milan · ITHumanitas University · ITIRCCS Humanitas Research Hospital · ITIRCCS Policlinico San Donato · ITKing's College London · GBQueensland University of Technology · AUUniversity of Göttingen · DEUniversity of Turin · ITVita-Salute San Raffaele University · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionLung weight is an important study endpoint to assess lung edema in porcine experiments on acute respiratory distress syndrome and ventilatory induced lung injury. Evidence on the relationship between lung-body weight relationship is lacking in the literature. The aim of this work is to provide a reference equation between normal lung and body weight in female domestic piglets. MATERIALS AND

methods177 healthy female domestic piglets from previous studies were included in the analysis. Lung weight was assessed either via a CT-scan before any experimental injury or with a scale after autopsy. The animals were randomly divided in a training (n = 141) and a validation population (n = 36). The relation between body weight and lung weight index (lung weight/body weight, g/kg) was described by an exponential function on the training population. The equation was tested on the validation population. A Bland-Altman analysis was performed to compare the lung weight index in the validation population and its theoretical value calculated with the reference equation.

resultsA good fit was found between the validation population and the exponential equation extracted from the training population (RMSE = 0.060). The equation to determine lung weight index from body weight was: [Formula: see text] At the Bland and Altman analyses, the mean bias between the real and the expected lung weight index was - 0.26 g/kg (95% CI - 0.96-0.43), upper LOA 3.80 g/kg [95% CI 2.59-5.01], lower LOA - 4.33 g/kg [95% CI = - 5.54-(- 3.12)].

conclusionsThis exponential function might be a valuable tool to assess lung edema in experiments involving 16-50 kg female domestic piglets. The error that can be made due to the 95% confidence intervals of the formula is smaller than the one made considering the lung to body weight as a linear relationship.

Identifiers

PMID38273120
PMCPMC10811311
OpenAlexW4391239423

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.