[Model selection and curative effect judgment criteria for artificial liver in the treatment of liver failure].
Artificial liver treatment
Effect
Hybrid mode
Liver failure
Therapy
Journal
Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology
ISSN: 1007-3418
Titre abrégé: Zhonghua Gan Zang Bing Za Zhi
Pays: China
ID NLM: 9710009
Informations de publication
Date de publication:
20 Feb 2022
20 Feb 2022
Historique:
entrez:
31
3
2022
pubmed:
1
4
2022
medline:
5
4
2022
Statut:
ppublish
Résumé
Artificial liver is one of the effective methods to treat liver failure. Patients with liver failure are critically ill and have great individualized differences. Therefore, the specific program for the treatment of liver failure with artificial liver should be individualized. The commonly used non-biological artificial liver models include simple plasmapheresis, double filtration plasmapheresis, plasma filtration with dialysis, double plasma molecular adsorption system, molecular absorbent recirculating system, hemodiafiltration, continuous venovenous hemodiafiltration, hybrid, etc. The curative effect should be properly judged from patient's symptoms, laboratory test indicators, survival rate and other aspects after artificial liver therapy. 人工肝是治疗肝衰竭的有效方法之一。肝衰竭患者病情危重、病情个体化差异较大,人工肝治疗肝衰竭的具体方案应个体化。常用的非生物型人工肝模式包括单纯血浆置换、双重滤过血浆置换、血浆透析滤过、双重血浆分子吸附系统、分子吸附再循环系统、血液透析滤过、连续性静脉-静脉血液透析滤过、组合模式人工肝治疗等。在人工肝治疗后,应从患者症状、实验室检查指标、生存率等方面对其疗效做出恰当的判断。.
Autres résumés
Type: Publisher
(chi)
人工肝是治疗肝衰竭的有效方法之一。肝衰竭患者病情危重、病情个体化差异较大,人工肝治疗肝衰竭的具体方案应个体化。常用的非生物型人工肝模式包括单纯血浆置换、双重滤过血浆置换、血浆透析滤过、双重血浆分子吸附系统、分子吸附再循环系统、血液透析滤过、连续性静脉-静脉血液透析滤过、组合模式人工肝治疗等。在人工肝治疗后,应从患者症状、实验室检查指标、生存率等方面对其疗效做出恰当的判断。.
Identifiants
pubmed: 35359063
doi: 10.3760/cma.j.cn501113-20220108-00008
doi:
Types de publication
Journal Article
Langues
chi
Sous-ensembles de citation
IM
Pagination
127-130Subventions
Organisme : Beijing Advanced Innovation Center for Big Data-Based Precision Medicine
ID : PXM2021_014226_000026
Organisme : Capital's Funds for Health Improvement and Research
ID : 2021-1G-2181