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Facial Analysis to Classify Difficult Intubation

This study is currently recruiting participants.
See Contacts and Locations
Verified July 2017 by Scott Segal, M.D, Wake Forest University Health Sciences
Sponsor:
Information provided by (Responsible Party):
Scott Segal, M.D, Wake Forest University Health Sciences
ClinicalTrials.gov Identifier:
NCT01612949
First received: June 4, 2012
Last updated: July 14, 2017
Last verified: July 2017
  Purpose
The aim of this project is to develop a computer algorithm that can accurately predict how easy or difficult it is to intubate a patient based upon digital photographs from three different perspectives. Such an application can provide a consistent, quantitative measure of intubation difficulty by analyzing facial features in captured photographs - features which have previously been shown to correlate with how easy or how hard it would be to perform the intubation procedure. This is in contrast to established subjective protocols that also serve to predict intubation difficulty, albeit with lower accuracy. A digital application has the potential to decrease potential complications related to intubation difficulty and increase patient safety.

Condition Intervention
Difficult Intubation Other: photographing head and neck

Study Type: Observational
Study Design: Observational Model: Cohort
Time Perspective: Prospective
Official Title: Comparison of a Computerized Image Analysis to Conventional Airway Examination Techniques to Predict Difficult Endotracheal Intubation

Further study details as provided by Scott Segal, M.D, Wake Forest University Health Sciences:

Primary Outcome Measures:
  • Computer algorithm to predict difficulty of endotracheal intubation [ Time Frame: Approximately 1 year, based on current enrollment pattern ]
    The outcome will be a computer algorithm that can accurately predict how easy or difficult it is to intubate a patient based upon digital photographs from three different perspectives. Such an application can provide a consistent, quantitative measure of intubation difficulty by analyzing facial features in captured photographs-features which have previously been shown to correlate with how easy or how hard it would be to perform the intubation procedure. A digital application has the potential to decrease complications related to intubation difficulty and increase patient safety.


Estimated Enrollment: 1000
Study Start Date: May 2012
Estimated Study Completion Date: June 2018
Estimated Primary Completion Date: June 2018 (Final data collection date for primary outcome measure)
Groups/Cohorts Assigned Interventions
easy to intubate, model derivation
easy to intubate, model derivation. photographing head and neck
Other: photographing head and neck
Taking three photographs of head and neck-one photograph from front, one from left and one fron right. The photographs are analyzed by facial structure software to create face model.
difficult to intubate, model derivation
difficult to intubate, model derivation.photographing head and neck
Other: photographing head and neck
Taking three photographs of head and neck-one photograph from front, one from left and one fron right. The photographs are analyzed by facial structure software to create face model.
easy to intubate, model validation
easy to intubate, model validation. photographing head and neck
Other: photographing head and neck
Taking three photographs of head and neck-one photograph from front, one from left and one fron right. The photographs are analyzed by facial structure software to create face model.
difficult to intubate, model validation
difficult to intubate, model validation. photographing head and neck
Other: photographing head and neck
Taking three photographs of head and neck-one photograph from front, one from left and one fron right. The photographs are analyzed by facial structure software to create face model.

Detailed Description:

Both control and experimental cohorts will be recruited in this study. In order to drive clinical acceptance of this technique, the investigators will need to study and then demonstrate applicability to all patients regardless of race or gender. This will require the recruitment of a control population of patients who have been demonstrated at surgery to be easy to intubate. Such patients are in relative abundance. The experimental group will consist of patients who are found at surgery to be difficult to intubate. Patients are defined as easy to intubate if their anesthetic record described a single attempt with a Macintosh 3 blade resulting in a grade 1 laryngoscopic view (full exposure of the vocal cords). Difficult intubation was defined by at least one of: more than one attempt by an operator with at least one year of anesthesia experience, grade 3 or 4 laryngoscopic view on a 4 point scale, 5 need for a second operator, or non-elective use of an alternative airway device such as a bougie, fiberoptic bronchoscope or intubating laryngeal mask airway.

The primary purpose of the study is to develop algorithms capable of discriminating patients who are likely to be difficult to intubate from those who are likely to be easy to intubate based on facial appearance. The primary analysis is the demonstration of statistical significance in the ability of the derived algorithms to determine successfully whether a subject was easy or difficult to intubate. A secondary analysis is the demonstration of a statistical difference in performance between the derived algorithms versus conventional airway assessment tests.

  Eligibility

Ages Eligible for Study:   18 Years to 64 Years   (Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
Patients undergoing surgical procedures requiring general anesthesia with endotracheal intubation; patients from all ethnic groups
Criteria

Inclusion Criteria:

  • Patients requiring endotracheal intubation
  • Patients consenting to acquisition of photographic images of the head and neck

Exclusion Criteria:

  • Patients who had undergone head or neck surgery
  • Patients in whom central venous catheters or other interventions that prevent full view of the features of the face in frontal and profile views
  • Patients who were neither easy nor difficult to intubate by our criteria
  Contacts and Locations
Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the Contacts provided below. For general information, see Learn About Clinical Studies.

Please refer to this study by its ClinicalTrials.gov identifier: NCT01612949

Contacts
Contact: Scott Segal, MD, MHCM (336) 716-7084 bsegal@wakehealth.edu
Contact: Iwona Bonney, PhD 617-636-9322 ibonney@tuftsmedicalcenter.org

Locations
United States, North Carolina
Wake Forest Baptist Medical Center Recruiting
Winston-Salem, North Carolina, United States, 27157
Contact: Scott Segal, MD    336-716-4497      
Principal Investigator: Scott Segal, MD, MHCM         
Sponsors and Collaborators
Wake Forest University Health Sciences
Investigators
Principal Investigator: Scott Segal, MD, MHCM Wake Forest University Health Sciences
  More Information

Publications:
Responsible Party: Scott Segal, M.D, Professor and Chair Department of Anesthesiology, Wake Forest University Health Sciences
ClinicalTrials.gov Identifier: NCT01612949     History of Changes
Other Study ID Numbers: IRB00036442
Study First Received: June 4, 2012
Last Updated: July 14, 2017
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: Undecided

Studies a U.S. FDA-regulated Drug Product: No

Keywords provided by Scott Segal, M.D, Wake Forest University Health Sciences:
endotracheal intubation
facial structure
Mallampati score
computerized facial analysis

ClinicalTrials.gov processed this record on July 25, 2017