Airway Ultrasound Assessment in the Prediction of Difficult Airway
NCT ID: NCT04816435
Last Updated: 2021-03-25
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
200 participants
OBSERVATIONAL
2021-01-01
2022-01-01
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
PROSPECTIVE
Interventions
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Ultrasound test
Ultrasound evaluation of airway
Eligibility Criteria
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Inclusion Criteria
* Non-urgent surgery under general anesthesia with orotracheal intubation
* Acceptance to participate and grant written consent
Exclusion Criteria
* Patients with a history of craniocervical pathology (trauma, tumor, malformations)
* Pregnancy
* Patient Refusal
18 Years
ALL
Yes
Sponsors
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Instituto de Investigación Sanitaria de la Fundación Jiménez Díaz
OTHER
Responsible Party
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Locations
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Hospital Universitario Fundación Jimenez Díaz
Madrid, , Spain
Countries
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References
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Madrid-Vazquez L, Casans-Frances R, Gomez-Rios MA, Cabrera-Sucre ML, Granacher PP, Munoz-Alameda LE. Machine learning models based on ultrasound and physical examination for airway assessment. Rev Esp Anestesiol Reanim (Engl Ed). 2024 Oct;71(8):563-569. doi: 10.1016/j.redare.2024.05.006. Epub 2024 May 31.
Other Identifiers
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FJD-ECOVAD-01
Identifier Type: -
Identifier Source: org_study_id
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