Ignite Creation Date:
2025-12-24 @ 10:37 PM
Ignite Modification Date:
2025-12-25 @ 8:09 PM
Study NCT ID:
NCT05979935
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
2025-08-15
First Post:
2023-07-30
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
A Digital Tongue Diagnosis Model for High- and Low-risk Esophagogastroduodenal Varices in Cirrhosis
Sponsor:
Qilu Hospital of Shandong University
Organization:
Study Overview
Official Title:
A Clinical Study on the Diagnostic Value of Digital Tongue Diagnosis Model for High- and Low-risk Esophagogastroduodenal Varices in Patients With Liver Cirrhosis
Status:
ACTIVE_NOT_RECRUITING
Status Verified Date:
2025-08
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
The aim of this observational study is to establish an AI deep learning model that can dianosie high-risk varices for patients with cirrhosis effeciently.
The main question of this study is to esplore:
question 1: Developing a digital tongue diagnosis model, specifically a deep learning model to diagnose high-risk esophageal and gastric varices (HRV) associated with cirrhosis using sublingual vein images. Answering the question of whether the new tongue diagnosis method can accurately diagnose.
Question 2: Compare the diagnostic efficacy digital tongue diagnosis model with diagnostic models constructed using other biochemical indicators for HRV in cirrhosis, and answer the question of "how to use it optimally."
Question 3: Exploring the correlation between sublingual vein characteristics and Hepatic venous pressure gradient (HVPG).
Question 4: Compared with endoscopic examination results, validate the diagnostic performance of the model (AUC ≥ 0.90) and screen for key parameters of sublingual vein characteristics (such as sublingual vein varicosity diameter, vein length, color, etc.).
Question 5: Follow-up tongue examination images of patients with cirrhosis who underwent treatment (e.g., endoscopy, splenic embolization, TIPS, etc.) at 1, 2, and 3 years post-treatment were evaluated to assess the efficacy of digital tongue examination models in predicting high-risk esophageal and gastric variceal bleeding at 1, 2, and 3 years post-treatment, as well as the efficacy in predicting endoscopic treatment failure rates and patient mortality associated with bleeding.
The main question of this study is to esplore:
question 1: Developing a digital tongue diagnosis model, specifically a deep learning model to diagnose high-risk esophageal and gastric varices (HRV) associated with cirrhosis using sublingual vein images. Answering the question of whether the new tongue diagnosis method can accurately diagnose.
Question 2: Compare the diagnostic efficacy digital tongue diagnosis model with diagnostic models constructed using other biochemical indicators for HRV in cirrhosis, and answer the question of "how to use it optimally."
Question 3: Exploring the correlation between sublingual vein characteristics and Hepatic venous pressure gradient (HVPG).
Question 4: Compared with endoscopic examination results, validate the diagnostic performance of the model (AUC ≥ 0.90) and screen for key parameters of sublingual vein characteristics (such as sublingual vein varicosity diameter, vein length, color, etc.).
Question 5: Follow-up tongue examination images of patients with cirrhosis who underwent treatment (e.g., endoscopy, splenic embolization, TIPS, etc.) at 1, 2, and 3 years post-treatment were evaluated to assess the efficacy of digital tongue examination models in predicting high-risk esophageal and gastric variceal bleeding at 1, 2, and 3 years post-treatment, as well as the efficacy in predicting endoscopic treatment failure rates and patient mortality associated with bleeding.
Detailed Description:
Firstly, participants will be divided into two groups according to their degree of esophageal varices from endoscopic examination and CT report, including high-risk varices (HRV) group and low-risk varices (LRV) group. Secondly, participants will be asked to show their tongue, including the surface and sublingual veins of tongue, and the tongue images of each participants will be collected by researchers via camera. After finishing tongue image collection, participants will receive a professional tongue diagnosis report in Traditional Chinese Medicine and health suggestion. Finally, tongue images will be analyzed by AI deep learning model and some specifialized information will be estracted exactly. Besides, 60 patietns will be selected to eplore whtether sublingual vein characteristics is assoicated with HVPG. Finally, patietns will be followed up during 3 years, and gastric variceal bleeding, endoscopic treatment failure rates, and patient mortality risks related to bleeding will be analyzed.
Study Oversight
Has Oversight DMC:
False
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?: