Evidence map›Paper›PMID 34017030›Full record

ArticleScientific reports2021

Clinical characterization of respiratory large droplet production during common airway procedures using high-speed imaging.

S K Mueller, R Veltrup, B Jakubaß, S Kniesburges, M J Huebner, J S Kempfle, S Dittrich, H Iro, M Döllinger

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 19% 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, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.

  1. Risk of Transmitting Coronavirus Disease 2019 During Nebulizer Treatment: A Systematic Review.Journal of aerosol medicine and pulmonary drug delivery · 2021
    Pooled it
  2. Article
  3. Observational
  4. Article
  5. Article
  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

9 authors at 3 institutions in 2 countries.

S K MuellerDepartment of Otolaryngology, Head and Neck Surgery, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Waldstrasse 1, 91054, Erlangen, Germany. mueller.sarinakatrin@gmail.com.
R VeltrupLaboratory for Computational Medicine, Department of Otolaryngology, Head and Neck Surgery, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
B JakubaßLaboratory for Computational Medicine, Department of Otolaryngology, Head and Neck Surgery, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
S KniesburgesLaboratory for Computational Medicine, Department of Otolaryngology, Head and Neck Surgery, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
M J HuebnerIntensive Care Medicine/Department of Pediatric Cardiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
J S KempfleDepartment of Otolaryngology, Massachusetts Eye and Ear, Harvard Medical School, Boston, USA.
S DittrichIntensive Care Medicine/Department of Pediatric Cardiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
H IroDepartment of Otolaryngology, Head and Neck Surgery, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Waldstrasse 1, 91054, Erlangen, Germany.
M DöllingerLaboratory for Computational Medicine, Department of Otolaryngology, Head and Neck Surgery, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany.
Friedrich-Alexander-Universität Erlangen-Nürnberg · DEUniversitätsklinikum Erlangen · DEMassachusetts Eye and Ear Infirmary · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the COVID-19 pandemic, a significant number of healthcare workers have been infected with SARS-CoV-2. However, there remains little knowledge regarding large droplet dissemination during airway management procedures in real life settings. 12 different airway management procedures were investigated during routine clinical care. A high-speed video camera (1000 frames/second) was for imaging. Quantitative droplet characteristics as size, distance traveled, and velocity were computed. Droplets were detected in 8/12 procedures. The droplet trajectories could be divided into two distinctive patterns (type 1/2). Type 1 represented a ballistic trajectory with higher speed large droplets whereas type 2 represented a random trajectory of slower particles that persisted longer in air. The use of tracheal cannula filters reduced the amount of droplets. Respiratory droplet patterns generated during airway management procedures follow two distinctive trajectories based on the influence of aerodynamic forces. Speaking and coughing produce more droplets than non-invasive ventilation therapy confirming these behaviors as exposure risks. Even large droplets may exhibit patterns resembling the fluid dynamics smaller airborne aerosols that follow the airflow convectively and may place the healthcare provider at risk.

Indexed as

Air MicrobiologyCoughAerosolsCOVID-19HumansPandemicsRespiratory SystemAerosols

Identifiers

PMID34017030
PMCPMC8137881
OpenAlexW3162852707

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.