Accepted for/Published in: JMIR Formative Research
Date Submitted: Dec 28, 2022
Date Accepted: Sep 13, 2023
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Application of Quantitative Difference to Evaluate Artificial Liver Support Effect in Acute-on-chronic Liver Failure
ABSTRACT
Background:
The prognosis evaluation of liver failure should run through the whole diagnosis. The quantitative difference (QD) may be beneficial in the prognosis evaluation of acute-on-chronic liver failure (ACLF).
Objective:
This study aims to verify whether the QD algorithm has the same function or is even better than the Model for End-Stage Liver Disease (MELD).
Methods:
Conventional treatment (n=12) or double plasma molecular absorption system (DPMAS) with conventional treatment (n=15). The prognosis evaluation was performed by the MELD and QD scoring system.
Results:
A very signification reduction was observed in alanine aminotransferase, aspartate aminotransferase and conjugated bilirubin, both in P-value (P<0.01) and QD (>1.69), and a significant decrease in hemoglobin, red blood cell count and total bilirubin were observed in DPMAS group (P<0.05), but not in QD (≤1.69). Meanwhile, there was a significant association between MELD and QD scores. It significantly differed between groups divided by patients’ status after treatment. Besides, the QD algorithm can also show patients' improvement, such as fatigue and jaundice.
Conclusions:
Compared with the conventional treatment group, DPMAS can reduce alanine aminotransferase, aspartate aminotransferase and unconjugated bilirubin. As a dynamic algorithm, the QD scoring system can evaluate the therapeutic effect of patients with ACLF, which proves that it has the same function as MELD, but considers more indicators and patient variability.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.