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1000
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Abstract/Summary
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Background!#!The COVID(coronavirus disease)-19 pandemic is characterized by high infectivity, droplet transmission, and high viral load in the upper respiratory tract. Severe disease courses are associated with interstitial pneumonia and ventilated patients, in whom tracheotomy (TT)-a droplet- and aerosol-producing medical intervention-is regularly necessary. TT as a potential infection risk for medical staff is scarcely found in the literature. Therefore, the aim of this study was to quantify droplet exposure of the surgical team during TT, to better define the requirements for personal protective equipment (PPE).!##!Materials and methods!#!Surgical TT was performed in four non-infectious patients, during which the surgeon and his assistant both wore a surgical nasal mask with a transparent visor. After the procedure, the type, distribution, and number of droplets on the visor were determined macroscopically and microscopically.!##!Results!#!An average of 29 droplets were found on the middle third of the visor, 4 on the right third, and 13 on the left third, with an average droplet size of 571 µm (± 381 µm). The smallest droplets were 55 µm, the largest 1431 µm. An increase in the number of droplets was found with increased ventilation during the procedure. Blood droplets were more common than secretion droplets.!##!Conclusion!#!Contamination of the visor with droplets was demonstrated. Especially in the case of TT in highly infectious patients, e.g., COVID-19 patients, the use of hooded headgear in combination with breathing apparatus with air purification and power supply is recommended to ensure best protection from infection for the surgeon and the surgical assistant.
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1000
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Hinweis
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DeepGreen-ID: 2dc87c32039245258b38654757a0ddc1 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
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