TY  - JOUR
AU  - Huang, Tinghuai
AU  - Huang, Jianwei
AU  - Liu, Timon Cheng-Yi
AU  - Li, Meng
AU  - She, Rui
AU  - Liu, Liyu
AU  - Qu, Hongguang
AU  - Liang, Fei
AU  - Cao, Yuanjing
AU  - Chen, Yuanzheng
AU  - Tang, Lu
PY  - 2023
DA  - 2023/10/24
TI  - Evaluating the Effect of Artificial Liver Support on Acute-on-Chronic Liver Failure Using the Quantitative Difference Algorithm: Retrospective Study
JO  - JMIR Form Res
SP  - e45395
VL  - 7
KW  - double plasma molecular absorption system
KW  - DPMAS
KW  - acute-on-chronic liver failure
KW  - quantitative difference
AB  - Background: Liver failure, including acute-on-chronic liver failure (ACLF), occurs mainly in young adults and is associated with high mortality and resource costs. The prognosis evaluation is a crucial part of the ACLF treatment process and should run through the entire diagnosis process. As a recently proposed novel algorithm, the quantitative difference (QD) algorithm holds promise for enhancing the prognosis evaluation of ACLF. Objective: This study aims to examine whether the QD algorithm exhibits comparable or superior performance compared to the Model for End-Stage Liver Disease (MELD) in the context of prognosis evaluation. Methods: A total of 27 patients with ACLF were categorized into 2 groups based on their treatment preferences: the conventional treatment (n=12) and the double plasma molecular absorption system (DPMAS) with conventional treatment (n=15) groups. The prognosis evaluation was performed by the MELD and QD scoring systems. Results: A significant reduction was observed in alanine aminotransferase (P=.02), aspartate aminotransferase (P<.001), and conjugated bilirubin (P=.002), both in P values and QD value (Lτ>1.69). A significant decrease in hemoglobin (P=.01), red blood cell count (P=.01), and total bilirubin (P=.02) was observed in the DPMAS group, but this decrease was not observed in QD (Lτ≤1.69). Furthermore, there was a significant association between MELD and QD values (P<.001). Significant differences were observed between groups based on patients’ treatment outcomes. Additionally, the QD algorithm can also demonstrate improvements in patient fatigue. DPMAS can reduce alanine aminotransferase, aspartate aminotransferase, and unconjugated bilirubin. Conclusions: As a dynamic algorithm, the QD scoring system can evaluate the therapeutic effects in patients with ACLF, similar to MELD. Nevertheless, the QD scoring system surpasses the MELD by incorporating a broader range of indicators and considering patient variability. 
SN  - 2561-326X
UR  - https://formative.jmir.org/2023/1/e45395
UR  - https://doi.org/10.2196/45395
UR  - http://www.ncbi.nlm.nih.gov/pubmed/37874632
DO  - 10.2196/45395
ID  - info:doi/10.2196/45395
ER  -