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| Name | Class |
|---|---|
| The Third People's Hospital of Taiyuan | OTHER |
| QuFu People's Hospital | INDIV |
| Shenyang Sixth People's Hospital | OTHER |
| LanZhou University |
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Portal hypertension contributed to the main complications of liver cirrhosis. Currently, hepatic venous pressure gradient (HVPG) was the reference standard for evaluating portal pressure in patients with cirrhosis. However, the practice of HVPG is limited to require the extensive experience and highly specialized centers. In recent years, non-invasive methods were proposed to predict the degree of cirrhotic portal hypertension. Liver stiffness is currently the most widely used method for noninvasive assessment of portal hypertension. The renewing Baveno VII recommended that liver stiffness ≥ 25 kPa by transient elastography is sufficient to identify clinically significant portal hypertension (specificity and positive predictive value > 90%). Although liver stiffness has a good predictive value for evaluation of clinically significant portal hypertension, it is difficult to apply in primary hospitals due to expensive equipment.
Recently, a multicenter study has shown that artificial intelligence analysis based on ocular images can aid to screening and diagnosis hepatobiliary diseases. The patented technology of collecting and analyzing diagnostic images of Traditional Chinese Medicine (TCM) based on mobile phone terminals has been realized. This technology mainly includes image acquisition, quality control and analysis, and clinical information collection. Liver cirrhosis belongs to the diseases of bulging and accumulation in TCM, and the most common symptoms are the liver and gallbladder damp-heat and liver stagnation and spleen deficiency. The main contents of inspection diagnosis in TCM for liver disease include the images of the tongue, eye and palms. In our study, the patented technology of TCM based on artificial intelligence is applied to establish a precise evaluation model of traditional Chinese and western medicine for portal hypertension with cirrhosis by combining the macroscopic characteristics of images and microscopic pathological indicators.
Portal hypertension contributed to the main complications of liver cirrhosis. Currently, hepatic venous pressure gradient (HVPG) was the reference standard for evaluating portal pressure in patients with cirrhosis. However, the practice of HVPG is limited to require the extensive experience and highly specialized centers. In recent years, non-invasive methods were proposed to predict the degree of cirrhotic portal hypertension. Liver stiffness is currently the most widely used method for noninvasive assessment of portal hypertension. The renewing Baveno VII recommended that liver stiffness ≥ 25 kPa by transient elastography is sufficient to identify clinically significant portal hypertension (specificity and positive predictive value > 90%). Although liver stiffness has a good predictive value for evaluation of clinically significant portal hypertension, it is difficult to apply in primary hospitals due to expensive equipment.
Recently, a multicenter study has shown that artificial intelligence analysis based on ocular images can aid to screening and diagnosis hepatobiliary diseases. The patented technology of collecting and analyzing diagnostic images of Traditional Chinese Medicine based on mobile phone terminals has been realized. This technology mainly includes image acquisition, quality control and analysis, and clinical information collection. Liver cirrhosis belongs to the diseases of bulging and accumulation in Traditional Chinese Medicine, and the most common symptoms are the liver and gallbladder damp-heat and liver stagnation and spleen deficiency. The main contents of inspection diagnosis in Traditional Chinese Medicine for liver disease include the images of the tongue, eye and palms. In our study, the patented technology of Traditional Chinese Medicine based on artificial intelligence is applied to establish a precise evaluation model of traditional Chinese and western medicine for portal hypertension with cirrhosis by combining the macroscopic characteristics of images and microscopic pathological indicators.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Training cohort | Patients were fulfilled diagnosis of cirrhosis based on radiological, histological features of liver cirrhosis and clinical manifestations. |
| |
| Validation cohort | Patients were fulfilled diagnosis of cirrhosis based on radiological, histological features of liver cirrhosis and clinical manifestations. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Hepatic venous pressure gradient | Diagnostic Test | All patients underwent measurement of HVPG under local anesthesia. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Accuracy of the precise evaluation method of traditional Chinese and western medicine for portal hypertension with cirrhosis by combining the macroscopic characteristics of images and microscopic pathological indicators. | In HVPG (mmHg) as reference method in evaluating portal pressure measured by intervention specialist, to develop a new traditional Chinese and western medicine method based on the macroscopic characteristics of images and microscopic pathological indicators and evaluate the accuracy in diagnosing portal hypertension. | 1 year |
| Measure | Description | Time Frame |
|---|---|---|
| Accuracy of the precise evaluation method of traditional Chinese and western medicine for high risk varices with cirrhosis by combining the macroscopic characteristics of images and microscopic pathological indicators. | To assess the precise evaluation method of traditional Chinese and western medicine to avoid unnecessary endoscopies in patients with cirrhosis. | 1 year |
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Inclusion Criteria:
Exclusion Criteria:
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Patients was fulfilled the diagnosis of cirrhosis based on radiological, histological features of liver cirrhosis and clinical manifestations.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Xiaolong Qi, M.D. | Contact | +8618588602600 | qixiaolong@vip.163.com | |
| Chuan Liu, MD | Contact | +8615626415443 | 845424585@qq.com |
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| CHESS | Recruiting | Beijing | Beijing Municipality | 1000000 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 30215362 | Background | Qi X, Berzigotti A, Cardenas A, Sarin SK. Emerging non-invasive approaches for diagnosis and monitoring of portal hypertension. Lancet Gastroenterol Hepatol. 2018 Oct;3(10):708-719. doi: 10.1016/S2468-1253(18)30232-2. | |
| 27786365 | Background | Garcia-Tsao G, Abraldes JG, Berzigotti A, Bosch J. Portal hypertensive bleeding in cirrhosis: Risk stratification, diagnosis, and management: 2016 practice guidance by the American Association for the study of liver diseases. Hepatology. 2017 Jan;65(1):310-335. doi: 10.1002/hep.28906. Epub 2016 Dec 1. No abstract available. |
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| OTHER |
| Hospital of Chengdu Office of People's Government of Tibetan Autonomous Region | UNKNOWN |
| Beijing 302 Hospital | OTHER |
| Tsinghua University | OTHER |
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| Institute for TCM-X, MOE Key Laboratory of Bioinformatics/Bioinformatics Division, BNRIST, Department of Automation, Tsinghua University | Not yet recruiting | Beijing | Beijing Municipality | 100000 | China |
|
| 27639071 | Background | Abraldes JG, Bureau C, Stefanescu H, Augustin S, Ney M, Blasco H, Procopet B, Bosch J, Genesca J, Berzigotti A; Anticipate Investigators. Noninvasive tools and risk of clinically significant portal hypertension and varices in compensated cirrhosis: The "Anticipate" study. Hepatology. 2016 Dec;64(6):2173-2184. doi: 10.1002/hep.28824. Epub 2016 Oct 27. |
| 33982942 | Background | Pons M, Augustin S, Scheiner B, Guillaume M, Rosselli M, Rodrigues SG, Stefanescu H, Ma MM, Mandorfer M, Mergeay-Fabre M, Procopet B, Schwabl P, Ferlitsch A, Semmler G, Berzigotti A, Tsochatzis E, Bureau C, Reiberger T, Bosch J, Abraldes JG, Genesca J. Noninvasive Diagnosis of Portal Hypertension in Patients With Compensated Advanced Chronic Liver Disease. Am J Gastroenterol. 2021 Apr;116(4):723-732. doi: 10.14309/ajg.0000000000000994. |
| 35120736 | Background | de Franchis R, Bosch J, Garcia-Tsao G, Reiberger T, Ripoll C; Baveno VII Faculty. Baveno VII - Renewing consensus in portal hypertension. J Hepatol. 2022 Apr;76(4):959-974. doi: 10.1016/j.jhep.2021.12.022. Epub 2021 Dec 30. |
| 33509389 | Background | Xiao W, Huang X, Wang JH, Lin DR, Zhu Y, Chen C, Yang YH, Xiao J, Zhao LQ, Li JO, Cheung CY, Mise Y, Guo ZY, Du YF, Chen BB, Hu JX, Zhang K, Lin XS, Wen W, Liu YZ, Chen WR, Zhong YS, Lin HT. Screening and identifying hepatobiliary diseases through deep learning using ocular images: a prospective, multicentre study. Lancet Digit Health. 2021 Feb;3(2):e88-e97. doi: 10.1016/S2589-7500(20)30288-0. |
| ID | Term |
|---|---|
| D006975 | Hypertension, Portal |
| D005355 | Fibrosis |
| ID | Term |
|---|---|
| D008107 | Liver Diseases |
| D004066 | Digestive System Diseases |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
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