CI

At a glance

ClinicalIndex Comparison Record
N/ACompleted· 595 enrolled
Drug / intervention
Deep convolutional neural networks analysisother
Likely dose
Not stated in record
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Standardized by ClinicalIndex from the ClinicalTrials.gov record · verify against the source.

Search/NCT05085743
NCT05085743N/ACompleted
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The Prediction of Proper Depth of Endotracheal Tube Fixation Before Intubation by Using Deep Convolutional Neural Networks and Chest Radiographs

Chang Gung Memorial Hospital·observational·Posted Oct 20, 2021·Updated Oct 20, 2021

In Brief

An observational study evaluating Deep convolutional neural networks analysis for Intubation and Machine Learning. Completed, enrolled 595 participants across 1 site.

Detailed Summary

Malposition of an endotracheal tube (ETT) may lead to a great disaster. Developing a handy way to predict the proper depth of ETT fixation is in need. Deep convolutional neural networks (DCNNs) are proven to perform well on chest radiographs analysis. The investigators hypothesize that DCNNs can also evaluate pre-intubation chest radiographs to predict suitable ETT depth and no related studies are found. The authors evaluated the ability of DCNNs to analyze pre-intubation chest radiographs along with patients' data to predict the proper depth of ETT fixation before intubation.

Study Details

Study Typeobservational
Allocation--
Masking--
Primary Purpose--
ConditionsIntubation, Machine Learning
CountriesTaiwan
Collaborators--

Timeline

N/ACompletedFinished
2020202120222023202420252026
First PostedOct 20, 2021
Enrollment StartNov 1, 2019
Primary CompletionOct 31, 2020
TodayJul 2, 2026
Enrollment to primary: 1 yearPosted 4.7 years ago

Interventions

Deep convolutional neural networks analysisother

using Deep convolutional neural networks to analyze pre-intubation chest radiographs along with patients' data to predict the proper depth of ETT fixation