Trial Outcomes & Findings for Anthropometric and US-Guided Difficult Intubation Prediction With ML Models (NCT NCT06904586)
NCT ID: NCT06904586
Last Updated: 2025-05-31
Results Overview
The dataset, labeled based on expert assessment of difficult intubation, was classified using eight widely accepted machine learning algorithms: logistic regression (LR) \[6\], support vector machine (SVM) \[7\], random forest (RF) \[8\], K-nearest neighbors (KNN) \[9\], Gaussian naive Bayes (GNB) \[10\], CatBoost \[11\], XGBoost \[12\], and decision tree (DT) \[13\]. From the original 30 parameters, the 15 most influential features were selected based on feature extraction methods and literature relevance. Preprocessing steps included handling missing values, with incomplete records excluded. The dataset was split into training (80%) and test (20%) sets. Models were trained on the training set, with hyperparameter tuning performed via 5-fold cross-validation to avoid overfitting. Final model performance was evaluated on the independent test set.
COMPLETED
329 participants
Taking ultrasonographic and anthropometric measurements of each patient took approximately 20 minutes. Machine learning estimates for each patient are approximately 1 min.
2025-05-31
Participant Flow
Participant milestones
| Measure |
Patients Between the Ages of 18 and 20 Who Will Receive General Anesthesia
Thyromental distance: Distance between the chin and thyroid cartilage with a tape measure when the patient is in a neutral position
Neck circumference: Measurement of neck circumference with a tape measure when the patient is in a neutral position
Mouth opening distance: Distance between the upper and lower teeth at the point where the mouth opening is maximum when the patient is in a neutral position.
Distance from jawbone to hyoid bone with neck in neutral position: Distance from mentum to hyoid bone with neck in neutral position by ultrasonography
Distance from jawbone to hyoid bone with neck in extension: Ultrasound measurement of distance from mentum to hyoid bone with neck in extension
Distance between skin and trachea: Ultrasound measurement of distance between skin and trachea
Distance between skin and epiglottis: Distance between skin and epiglottis measured by ultrasonography
Distance between skin and anterior commissure of vocal cord:: Distance between skin and anterior commissure of vocal cord measured by ultrasonography
Distance between skin and hyoid bone: Distance between skin and hyoid bone measured by ultrasonography
Maximum Tongue Thickness: Measurement of Maximal Tongue Thickness by Ultrasonography
|
|---|---|
|
Overall Study
STARTED
|
329
|
|
Overall Study
COMPLETED
|
329
|
|
Overall Study
NOT COMPLETED
|
0
|
Reasons for withdrawal
Withdrawal data not reported
Baseline Characteristics
Race and Ethnicity were not collected from any participant.
Baseline characteristics by cohort
| Measure |
Patients Between the Ages of 18 and 20 Who Will Receive General Anesthesia
n=329 Participants
Thyromental distance: Distance between the chin and thyroid cartilage with a tape measure when the patient is in a neutral position
Neck circumference: Measurement of neck circumference with a tape measure when the patient is in a neutral position
Mouth opening distance: Distance between the upper and lower teeth at the point where the mouth opening is maximum when the patient is in a neutral position.
Distance from jawbone to hyoid bone with neck in neutral position: Distance from mentum to hyoid bone with neck in neutral position by ultrasonography
Distance from jawbone to hyoid bone with neck in extension: Ultrasound measurement of distance from mentum to hyoid bone with neck in extension
Distance between skin and trachea: Ultrasound measurement of distance between skin and trachea
Distance between skin and epiglottis: Distance between skin and epiglottis measured by ultrasonography
Distance between skin and anterior commissure of vocal cord:: Distance between skin and anterior commissure of vocal cord measured by ultrasonography
Distance between skin and hyoid bone: Distance between skin and hyoid bone measured by ultrasonography
Maximum Tongue Thickness: Measurement of Maximal Tongue Thickness by Ultrasonography
|
|---|---|
|
Age, Categorical
<=18 years
|
0 Participants
n=329 Participants
|
|
Age, Categorical
Between 18 and 65 years
|
317 Participants
n=329 Participants
|
|
Age, Categorical
>=65 years
|
12 Participants
n=329 Participants
|
|
Age, Continuous
|
45 years
STANDARD_DEVIATION 20 • n=329 Participants
|
|
Sex: Female, Male
Female
|
190 Participants
n=329 Participants
|
|
Sex: Female, Male
Male
|
139 Participants
n=329 Participants
|
|
Region of Enrollment
Turkey
|
329 Participants
n=329 Participants
|
PRIMARY outcome
Timeframe: Taking ultrasonographic and anthropometric measurements of each patient took approximately 20 minutes. Machine learning estimates for each patient are approximately 1 min.The dataset, labeled based on expert assessment of difficult intubation, was classified using eight widely accepted machine learning algorithms: logistic regression (LR) \[6\], support vector machine (SVM) \[7\], random forest (RF) \[8\], K-nearest neighbors (KNN) \[9\], Gaussian naive Bayes (GNB) \[10\], CatBoost \[11\], XGBoost \[12\], and decision tree (DT) \[13\]. From the original 30 parameters, the 15 most influential features were selected based on feature extraction methods and literature relevance. Preprocessing steps included handling missing values, with incomplete records excluded. The dataset was split into training (80%) and test (20%) sets. Models were trained on the training set, with hyperparameter tuning performed via 5-fold cross-validation to avoid overfitting. Final model performance was evaluated on the independent test set.
Outcome measures
| Measure |
Patients Between the Ages of 18 and 20 Who Will Receive General Anesthesia
n=329 Participants
Thyromental distance: Distance between the chin and thyroid cartilage with a tape measure when the patient is in a neutral position
Neck circumference: Measurement of neck circumference with a tape measure when the patient is in a neutral position
Mouth opening distance: Distance between the upper and lower teeth at the point where the mouth opening is maximum when the patient is in a neutral position.
Distance from jawbone to hyoid bone with neck in neutral position: Distance from mentum to hyoid bone with neck in neutral position by ultrasonography
Distance from jawbone to hyoid bone with neck in extension: Ultrasound measurement of distance from mentum to hyoid bone with neck in extension
Distance between skin and trachea: Ultrasound measurement of distance between skin and trachea
Distance between skin and epiglottis: Distance between skin and epiglottis measured by ultrasonography
Distance between skin and anterior commissure of vocal cord:: Distance between skin and anterior commissure of vocal cord measured by ultrasonography
Distance between skin and hyoid bone: Distance between skin and hyoid bone measured by ultrasonography
Maximum Tongue Thickness: Measurement of Maximal Tongue Thickness by Ultrasonography
|
|---|---|
|
Support Vector Machine Algorithm Percentage of Accuracy in Predicted Difficult Intubations
support vector macine Accuracy
|
89.39 percentage of estimate
Interval 80.0 to 95.0
|
|
Support Vector Machine Algorithm Percentage of Accuracy in Predicted Difficult Intubations
Logistic Regression Accuracy
|
77.27 percentage of estimate
Interval 70.0 to 95.0
|
|
Support Vector Machine Algorithm Percentage of Accuracy in Predicted Difficult Intubations
Random Forest Accuracy
|
87.88 percentage of estimate
Interval 80.0 to 95.0
|
|
Support Vector Machine Algorithm Percentage of Accuracy in Predicted Difficult Intubations
Decision Tree Accuracy
|
80.30 percentage of estimate
Interval 80.0 to 95.0
|
|
Support Vector Machine Algorithm Percentage of Accuracy in Predicted Difficult Intubations
K-Nearest Neighbors Accuracy
|
74.24 percentage of estimate
Interval 70.0 to 95.0
|
|
Support Vector Machine Algorithm Percentage of Accuracy in Predicted Difficult Intubations
Gaussian Naive Bayes Accuracy
|
71.21 percentage of estimate
Interval 70.0 to 95.0
|
|
Support Vector Machine Algorithm Percentage of Accuracy in Predicted Difficult Intubations
CatBoost Accuracy
|
83.33 percentage of estimate
Interval 80.0 to 95.0
|
|
Support Vector Machine Algorithm Percentage of Accuracy in Predicted Difficult Intubations
XGBoost Accuracy
|
81.82 percentage of estimate
Interval 80.0 to 95.0
|
Adverse Events
Patients Between the Ages of 18 and 20 Who Will Receive General Anesthesia
Serious adverse events
Adverse event data not reported
Other adverse events
Adverse event data not reported
Additional Information
Results disclosure agreements
- Principal investigator is a sponsor employee
- Publication restrictions are in place