Airway Ultrasound Assessment in the Prediction of Difficult Airway

NCT ID: NCT04816435

Last Updated: 2021-03-25

Study Results

Results pending

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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Recruitment Status

UNKNOWN

Total Enrollment

200 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-01-01

Study Completion Date

2022-01-01

Brief Summary

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To assess whether the thickness of pre-tracheal fat, greater than 28 mm, and measured by ultrasound, constitutes a reliable parameter in the prediction of a difficult airway.

Detailed Description

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Conditions

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Airway Complication of Anesthesia Anesthesia Intubation Complication

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Interventions

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Ultrasound test

Ultrasound evaluation of airway

Intervention Type DIAGNOSTIC_TEST

Eligibility Criteria

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Inclusion Criteria

* Patients risk ASA I-IV
* Non-urgent surgery under general anesthesia with orotracheal intubation
* Acceptance to participate and grant written consent

Exclusion Criteria

* Urgent surgery
* Patients with a history of craniocervical pathology (trauma, tumor, malformations)
* Pregnancy
* Patient Refusal
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

Yes

Sponsors

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Instituto de Investigación Sanitaria de la Fundación Jiménez Díaz

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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Hospital Universitario Fundación Jimenez Díaz

Madrid, , Spain

Site Status

Countries

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Spain

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.

Reference Type DERIVED
PMID: 38825182 (View on PubMed)

Other Identifiers

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FJD-ECOVAD-01

Identifier Type: -

Identifier Source: org_study_id

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