Evidence map›Paper›PMID 35741215›Full record

ReviewDiagnostics (Basel, Switzerland)2022

Lung Sonography in Critical Care Medicine.

Robert Breitkopf, Benedikt Treml, Sasa Rajsic

Open access · goldAbstract readReview
In one paragraph

Review in Diagnostics (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
2.6field-weighted citation impact, top 10% 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

6 citing papers in PubMed, 18 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Lung Imaging and Artificial Intelligence in ARDS.Journal of clinical medicine · 2024
    Review
  5. Review
  6. 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

3 authors at 1 institution in 1 country.

Robert BreitkopfDepartment of Anaesthesiology and Intensive Care Medicine, Medical University Innsbruck, 6020 Innsbruck, Austria.
Benedikt TremlDepartment of Anaesthesiology and Intensive Care Medicine, Medical University Innsbruck, 6020 Innsbruck, Austria.ORCID 0000-0002-3648-7338
Sasa RajsicDepartment of Anaesthesiology and Intensive Care Medicine, Medical University Innsbruck, 6020 Innsbruck, Austria.ORCID 0000-0001-6193-3662
Innsbruck Medical University · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the last five decades, lung sonography has developed into a core competency of intensive care medicine. It is a highly accurate bedside tool, with clear diagnostic criteria for most causes of respiratory failure (pneumothorax, pulmonary edema, pneumonia, pulmonary embolism, chronic obstructive pulmonary disease, asthma, and pleural effusion). It helps in distinguishing a hypovolemic from a cardiogenic, obstructive, or distributive shock. In addition to diagnostics, it can also be used to guide ventilator settings, fluid administration, and even antimicrobial therapy, as well as to assess diaphragmatic function. Moreover, it provides risk-reducing guidance during invasive procedures, e.g., intubation, thoracocentesis, or percutaneous dilatational tracheostomy. The recent pandemic has further increased its scope of clinical applications in the management of COVID-19 patients, from their initial presentation at the emergency department, during their hospitalization, and after their discharge into the community. Despite its increasing use, a consensus on education, assessment of competencies, and certification is still missing. Deep learning and artificial intelligence are constantly developing in medical imaging, and contrast-enhanced ultrasound enables new diagnostic perspectives. This review summarizes the clinical aspects of lung sonography in intensive care medicine and provides an overview about current training modalities, diagnostic limitations, and future developments.

Indexed as

COVID-19critically illintensive careinvasive procedurelung sonographymonitoringpoint-of-care

Identifiers

PMID35741215
PMCPMC9222177
OpenAlexW4281777467

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.