Evidence map›Paper›PMID 39050483›Full record

ArticleFrontiers in physiology2024

Body mass index is associated with pulmonary gas and blood distribution mismatch in COVID-19 acute respiratory failure. A physiological study.

Kristín J Bjarnadóttir, Gaetano Perchiazzi, Caroline Lördal Sidenbladh, Aleksandra Larina, Ewa Wallin, Ing-Marie Larsson, Stephanie Franzén, Anders O Larsson, Mayson L A Sousa, Monica Segelsjö and 5 more

2 registry-linked trialsAbstract read
In one paragraph

Article in Frontiers in physiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 2 registered trials, which are not on this map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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.

NCT04316884 completednot on this map

Uppsala Intensive Care Study of Mechanisms for Organ Dysfunction in Covid-19

TypeobservationalSponsorUppsala UniversityRan2020 to 2025Enrolled380ConditionsCOVID-19, Organ Dysfunction Syndrome Sepsis, Organ Dysfunction Syndrome, Multiple, Septic Shock
NCT04474249 unknown statusnot on this map

Uppföljning av Patienter Som intensivvårdats för COVID-19

TypeobservationalSponsorUppsala UniversityRan2020 to 2022Enrolled300ConditionsCOVID19, ARDS, AKI, Circulatory Failure
3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
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.

Kristín J Bjarnadóttir *Anaesthesiology and Intensive Care Medicine, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Gaetano Perchiazzi *Anaesthesiology and Intensive Care Medicine, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Caroline Lördal SidenbladhAnaesthesiology and Intensive Care Medicine, Hudiksvall Hospital, Hudiksvall, Sweden.
Aleksandra LarinaAnaesthesiology and Intensive Care Medicine, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Ewa WallinAnaesthesiology and Intensive Care Medicine, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Ing-Marie LarssonAnaesthesiology and Intensive Care Medicine, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Stephanie FranzénAnaesthesiology and Intensive Care Medicine, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Anders O LarssonDepartment of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden.
Mayson L A SousaKeenan Centre for Biomedical Research, Critical Care Department, St. Michael's Hospital, Unity Health Toronto, Toronto, ON, Canada.
Monica SegelsjöSection of Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Tomas HansenSection of Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Robert FrithiofAnaesthesiology and Intensive Care Medicine, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Michael HultströmAnaesthesiology and Intensive Care Medicine, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Miklos LipcseyAnaesthesiology and Intensive Care Medicine, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Mariangela PellegriniAnaesthesiology and Intensive Care Medicine, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The effects of obesity on pulmonary gas and blood distribution in patients with acute respiratory failure remain unknown. Dual-energy computed tomography (DECT) is a X-ray-based method used to study regional distribution of gas and blood within the lung. We hypothesized that 1) regional gas/blood mismatch can be quantified by DECT; 2) obesity influences the global and regional distribution of pulmonary gas and blood; 3) regardless of ventilation modality (invasive vs. non-invasive ventilation), patients' body mass index (BMI) has an impact on pulmonary gas/blood mismatch. Methods: This single-centre prospective observational study enrolled 118 hypoxic COVID-19 patients (92 male) in need of respiratory support and intensive care who underwent DECT. The cohort was divided into three groups according to BMI: 1. BMI<25 kg/m Results: 1) Regional pulmonary distribution of gas and blood and their mismatch were quantified using DECT imaging. 2) The BMI>40 kg/m Conclusion: 1) In a hypoxic COVID-19 population needing intensive care, pulmonary gas/blood mismatch can be quantified at a global and regional level using DECT. 2) Obesity influences the global and regional distribution of gas and blood within the lung, and BMI>40 kg/m Trial Registration: Clinicaltrials.gov, identifier NCT04316884, NCT04474249.

Indexed as

acute respiratory failureCOVID-19dual-energy computed tomographymechanical ventilationobesityventilation/perfusion mismatch

Identifiers

PMID39050483
PMCPMC11266150

What OpenQuestion holds

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Registered trials

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.