AI Article Synopsis

  • * A study analyzed data from 411 patients to assess blood-based biomarkers (NLR, PLR, FIB4, etc.) for predicting hospital mortality, using statistical techniques to gauge their impact on mortality rates.
  • * Key findings revealed that NLR, PLR, and FIB4 were strong predictors of hospital mortality, while other markers like INPR, APRI, LMR, and ALBI did not significantly influence mortality predictions in this context.

Article Abstract

: There is a strong correlation between systemic inflammation intensity and clinical presentation, disease progression, and survival during liver cirrhosis decompensation. This study aimed to evaluate the prognostic performance of blood-based biomarkers as meta-inflammation markers, including NLR, PLR, LMR, INPR, MPR, ALBI, FIB4, and APRI, in predicting hospital mortality in patients with acute decompensation of alcohol-related liver cirrhosis. : Data from 411 patients with their first onset of acute decompensation were analyzed, forming two groups: deceased and survived during hospitalization. Generalized partial least squares regression analysis was applied to explore the effects of surrogate indicators on mortality rates, using mortality rate as the dependent variable. Root Mean Square Error, Akaike's, and Bayesian information criteria determined that four components accounted for most of the variance. : Variables with significant negative contributions to the outcome prediction (ranked by standardized regression coefficients) were encephalopathy grade, total bilirubin, Child-Turcotte-Pugh score, MELD, NLR, MPV, FIB4, INR, PLR, and ALT. Coefficient sizes ranged from -0.63 to -0.09, with -values from 0 to 0.018. : NLR, PLR, and FIB4 significantly contribute to hospital mortality prediction in patients with acute decompensation of alcohol-related liver cirrhosis. Conversely, some variables used to predict liver disease severity, including INPR, APRI, LMR, and ALBI score, did not significantly contribute to hospital mortality prediction in this patient population.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11508931PMC
http://dx.doi.org/10.3390/jcm13206208DOI Listing

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