GastroscopyNCT04682821
The Research of AI Assistant Gastroscope Training
A study testing Artificial intelligence assistant system in people with Gastroscopy and Training, run by Renmin Hospital of Wuhan University at 1 site in China.
Trial summary
In this study, we proposed a prospective study about the effectiveness of artificial intelligence system for gastroscope training in novice endoscopists. The subjects would be divided into two groups. Read more about this study
- Who is it for?
- Ages 18 to 70 yearsHealthy volunteers can take part
- Conditions the study is for
- Gastroscopy, Training, Artificial Intelligence
- What is being tested?
- Artificial intelligence assistant system
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 288 participants
- Where
- 1 siteChina
- Study dates
- 23 Dec 2020to 26 Jun 2021
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 70 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Who may be able to join
- Males or females who are over 18 years old;
- After qualified medical education and obtained the Certificate of Chinese medical practitioner;
Who cannot join
- A doctor who has already been trained in gastroenteroscopy;
- Doctors without qualified medical education and didn't obtaine the Certificate of Chinese medical practitioner;
- The researcher believes that the subjects are not suitable for participating in clinical trials.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: The Research of Artificial Intelligence Assistance System Effectiveness for Novice Endoscopists Gastroscopy Training
In this study, we proposed a prospective study about the effectiveness of artificial intelligence system for gastroscope training in novice endoscopists. The subjects would be divided into two groups. The experimental group would be trained in painless gastroscopy with the assistance of the artificial intelligence assistant system. The artificial intelligence assistant system can prompt abnormal lesions and the parts covered by the examination (the stomach is divided into 26 parts). The control group would receive routine painless gastroscopy training without special prompts. Then we compare the gastroscopy operation score, coverage rate of blind spots in gastroscopy,check the average test score before and after training, training satisfaction, detection rate of lesions and so on between the two group.
Read the detailed description
In this study, we proposed a prospective study about the effectiveness of artificial intelligence system for gastroscope training in novice endoscopists. The subjects would be divided into two groups. The experimental group would be trained in painless gastroscopy with the assistance of the artificial intelligence assistant system. The artificial intelligence assistant system can prompt abnormal lesions and the parts covered by the examination (the stomach is divided into 26 parts). The control group would receive routine painless gastroscopy training without special prompts. Then we compare the gastroscopy operation score, coverage rate of blind spots in gastroscopy,check the average test score before and after training, training satisfaction, detection rate of lesions and so on between the two group.
- Conditions
- Gastroscopy, Training, Artificial Intelligence
- Being tested
- Artificial intelligence assistant system
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial intelligence assistant systemOther
The intervention is the use of the artificial intelligence assistant system in addition to the common training. The system is an non-invasive AI system which could help the endoscopists to diagnosis and monitor the blind spot during the gastroscope.
| Study group | Role | What they receive |
|---|---|---|
| with Artificial intelligence assistant system | Experimental | The experiment group would receive the training with the help of artificial intelligence assistant system in addition to the common training. The system is an non-invasive AI system which could help the endoscopists to diagnosis and monitor the blind spot during the gastroscope. Receives: Other: Artificial intelligence assistant system |
| without Artificial intelligence assistant system | No intervention | The control group would receive the training without the help of artificial intelligence assistant system. That is, they would receive the common training process. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Gastroscopy operation score
Using a professional gastroscopy operation scoring scale, the full score is 100 points, and the score is divided into small items. In this experiment, the effect of training between the two groups was compared by comparing the scores of gastroscopy operation in the experimental group and the control group.
Measured: three month
Secondary outcomes (4)
Coverage rate of blind spots in gastroscopy
Evaluate the gastroscope operation videos retained by each physician during the examination, and calculate the coverage of 26 parts of the gastric mucosa in the experimental group and the control group during the examination. The calculation method is: the coverage rate of the blind area of the gastroscopy = the actual number of parts covered by the examination/26 parts of the stomach x 100%.
Measured: three month
Check the average test score before and after training
the difference between the theoretical test score after the training and the theoretical test score before the training, the calculation method: the theoretical test score after the training-the theoretical test score before the training.
Measured: three month
Training satisfaction
An AI assistant group fills out a questionnaire after training, and determines the satisfaction with AI assistant training through a grading method.
Measured: three month
Detection rate of lesions
the detection rate of lesions in the experimental group and the control group by gastroscopy. Calculation method = number of gastroscopes with detected lesions/total number of gastroscopes completed by beginner physicians x 100%.
Measured: three month
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Dec 2020
- Study start23 Dec 2020
- Primary completion25 May 2021
- Study completion26 Jun 2021
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for GastroscopyStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Screening
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind
- Who is masked
- Participant, Outcomes assessor
- Enrolment
- 288 participants (actual)
Sponsor and investigators
- Lead sponsor
- Renmin Hospital of Wuhan University
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- Honggang W Yu, Doctor, Principal investigator, Renmin Hospital of Wuhan University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04682821
- Sponsor's protocol ID
- EA-19-003-19
- Status last verified
- Dec 2020
- First submitted
- 20 Dec 2020
- Last updated
- 26 Oct 2021
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Huang L, Liu J, Wu L, Xu M, Yao L, Zhang L, Shang R, Zhang M, Xiong Q, Wang D, Dong Z, Xu Y, Li J, Zhu Y, Gong D, Wu H, Yu H. Impact of Computer-Assisted System on the Learning Curve and Quality in Esophagogastroduodenoscopy: Randomized Controlled Trial. Front Med (Lausanne). 2021 Dec 14;8:781256. doi: 10.3389/fmed.2021.781256. eCollection 2021.
PubMed 34970565
Study at a glance
From the registry record, last updated by the sponsor on 26 Oct 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Research of Artificial Intelligence Assistance System Effectiveness for Novice Endoscopists Gastroscopy Training
- ClinicalTrials.gov ID
- NCT04682821
- Acronym / sponsor ID
- EA-19-003-19
- Conditions
- Gastroscopy, Training, Artificial Intelligence
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 288 participants (actual)
- Lead sponsor
- Renmin Hospital of Wuhan UniversityUniversity, hospital or other
- Study start
- 23 Dec 2020 (actual)
- Primary completion
- 25 May 2021 (actual)
- Study completion
- 26 Jun 2021 (actual)
- First posted
- 24 Dec 2020 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
In this study, we proposed a prospective study about the effectiveness of artificial intelligence system for gastroscope training in novice endoscopists. The subjects would be divided into two groups. The experimental group would be trained in painless gastroscopy with the assistance of the artificial intelligence assistant system. The artificial intelligence assistant system can prompt abnormal lesions and the parts covered by the examination (the stomach is divided into 26 parts). The control group would receive routine painless gastroscopy training without special prompts. Then we compare the gastroscopy operation score, coverage rate of blind spots in gastroscopy,check the average test score before and after training, training satisfaction, detection rate of lesions and so on between the two group.
Detailed description
In this study, we proposed a prospective study about the effectiveness of artificial intelligence system for gastroscope training in novice endoscopists. The subjects would be divided into two groups. The experimental group would be trained in painless gastroscopy with the assistance of the artificial intelligence assistant system. The artificial intelligence assistant system can prompt abnormal lesions and the parts covered by the examination (the stomach is divided into 26 parts). The control group would receive routine painless gastroscopy training without special prompts. Then we compare the gastroscopy operation score, coverage rate of blind spots in gastroscopy,check the average test score before and after training, training satisfaction, detection rate of lesions and so on between the two group.
Study design
- Primary purpose
- Screening
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- Double blind (participant, outcomes assessor)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| with Artificial intelligence assistant system | Experimental | Other: Artificial intelligence assistant systemThe experiment group would receive the training with the help of artificial intelligence assistant system in addition to the common training. The system is an non-invasive AI system which could help the endoscopists to diagnosis and monitor the blind spot during the gastroscope. |
| without Artificial intelligence assistant system | No intervention | –The control group would receive the training without the help of artificial intelligence assistant system. That is, they would receive the common training process. |
Who may qualify
- Ages
- 18 to 70 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (2 listed)
- Males or females who are over 18 years old;
- After qualified medical education and obtained the Certificate of Chinese medical practitioner;
Key exclusion criteria (3 listed)
- A doctor who has already been trained in gastroenteroscopy;
- Doctors without qualified medical education and didn't obtaine the Certificate of Chinese medical practitioner;
- The researcher believes that the subjects are not suitable for participating in clinical trials.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Artificial intelligence assistant systemThe intervention is the use of the artificial intelligence assistant system in addition to the common training. The system is an non-invasive AI system which could help the endoscopists to diagnosis and monitor the blind spot during the gastroscope. | Other | with Artificial intelligence assistant system |
Primary outcome
Gastroscopy operation score
Time frame: three month
Using a professional gastroscopy operation scoring scale, the full score is 100 points, and the score is divided into small items. In this experiment, the effect of training between the two groups was compared by comparing the scores of gastroscopy operation in the experimental group and the control group.
4 secondary outcomes
Coverage rate of blind spots in gastroscopy
Time frame: three month
Check the average test score before and after training
Time frame: three month
Training satisfaction
Time frame: three month
Detection rate of lesions
Time frame: three month
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 26 Oct 2021.
- Derived from this study: PubMed 34970565Huang L, Liu J, Wu L, Xu M, Yao L, Zhang L, Shang R, Zhang M, Xiong Q, Wang D, Dong Z, Xu Y, Li J, Zhu Y, Gong D, Wu H, Yu H. Impact of Computer-Assisted System on the Learning Curve and Quality in Esophagogastroduodenoscopy: Randomized Controlled Trial. Front Med (Lausanne). 2021 Dec 14;8:781256. doi: 10.3389/fmed.2021.781256. eCollection 2021.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Honggang W Yu, Doctor principal investigator
Renmin Hospital of Wuhan University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Artificial intelligence assistant system in people with Gastroscopy and Training, run by Renmin Hospital of Wuhan University at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 26 Oct 2021. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Gastroscopy operation score (time frame: three month). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT04682821, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 26 Oct 2021.