New Reusable Mask Design With Superior Filtration and Fit
NCT ID: NCT04826809
Last Updated: 2023-07-07
Study Results
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View full resultsBasic Information
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COMPLETED
NA
41 participants
INTERVENTIONAL
2021-04-09
2022-10-27
Brief Summary
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Detailed Description
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Dr. Nordell has developed a machine-washable mask which shows potential to be significantly more effective than other masks on the market. It uses a fabric that is machine washable, without need for a filter or replaceable component. This fabric, Evolon-100 or E-100, is a microfilament fabric produced by a private company outside of the USA (and is therefore not yet FDA approved as of December 2020).
Unofficial data shows this mask passes the "N95 fit test" before and after multiple washes on the majority of individuals tested, and the material used in Dr. Nordell's design filters 93-96% of 0.3 micron particles. For reference, the N95 mask used in the hospital (whenever concern for potential exposure to COVID-19 or similar contagion exists) filters 95% of 0.3 micron particles when factoring in air leak, assessed with the "fit test." Voluntary survey of users also shows it is more comfortable than other masks, including the N95. This mask is also reported to be breathable even after prolonged use.
This mask design addresses every factor in respirator design. The design intentionally uses pleats to increase the effective mask surface area while decreasing the seal perimeter, resulting in increased air flow, lower pressure drop, and increased filtration efficiency. The investigators propose that it has a higher filtration ability than other washable fabrics tested, filtering at least 93% of 0.3 micron particles, even up to 96%. It also helps prevent air leak, a large factor limiting efficacy of most non-standard masks. It is easy to don and doff, and it is very easy to clean and disinfect. This material can be washed multiple times in a standard washing machine without reducing its effectiveness. And finally, it is very affordable, with materials for one mask costing less than $1.50. All materials used beyond this specific fabric are easily purchased on the internet or in a fabric store.
Upon completion of this research, the investigators hope to demonstrate that this mask is a superior alternative in multiple settings, including hospitals in developing countries with little or no N95 mask access, non-hospital settings such as businesses and schools, as well as for the general population, especially those with high risk for COVID-related complications.
Conditions
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Study Design
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NA
SINGLE_GROUP
PREVENTION
NONE
Study Groups
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Health care workers
Health care workers will complete a fit test while wearing the Nordell Single E-100 layer + (cotton layer) mask, Nordell Double E-100 layer mask and an N95 mask
N95 mask
Standard 1870 N95 one time use mask
Nordell single E-100 layer mask
Nordell mask design using one layer of E-100 fabric plus cotton fabric overlay
Nordell double E-100 layer mask
Nordell mask design using two layers of E-100 fabric
Interventions
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N95 mask
Standard 1870 N95 one time use mask
Nordell single E-100 layer mask
Nordell mask design using one layer of E-100 fabric plus cotton fabric overlay
Nordell double E-100 layer mask
Nordell mask design using two layers of E-100 fabric
Eligibility Criteria
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Inclusion Criteria
* Passed N95 fit test within the past year
* No medical history of: high blood pressure, current or recent pneumonia or upper respiratory infection, and no uncontrolled chronic asthma
* Ideally with wide representation of genders, race, age, BMI, occupation/role in hospital.
* Willing and able to provde verbal consent.
Exclusion Criteria
18 Years
ALL
Yes
Sponsors
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Mayo Clinic
OTHER
Responsible Party
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Janielle R. Nordell
Principal Investigator
Principal Investigators
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Janielle R Nordell, MD
Role: PRINCIPAL_INVESTIGATOR
Mayo Clinic
Locations
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Mayo Clinic Health System in Mankato
Mankato, Minnesota, United States
Countries
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Provided Documents
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Document Type: Study Protocol
Related Links
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Mayo Clinic Clinical Trials
Other Identifiers
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20-011897
Identifier Type: -
Identifier Source: org_study_id
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