Markers of inflammation predict survival in newly diagnosed cirrhosis: a prospective registry study

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The inflammatory activity in cirrhosis is often pronounced and related to episodes of decompensation. Systemic markers of inflammation may contain prognostic information, and we investigated their possible correlation with admissions and mortality among patients with newly diagnosed liver cirrhosis. We collected plasma samples from 149 patients with newly diagnosed (within the past 6 months) cirrhosis, and registered deaths and hospital admissions within 180 days. Ninety-two inflammatory markers were quantified and correlated with clinical variables, mortality, and admissions. Prediction models were calculated by logistic regression. We compared the disease courses of our cohort with a validation cohort of 86 patients with cirrhosis. Twenty of 92 markers of inflammation correlated significantly with mortality within 180 days (q-values of 0.00–0.044), whereas we found no significant correlations with liver-related admissions. The logistic regression models yielded AUROCs of 0.73 to 0.79 for mortality and 0.61 to 0.73 for liver-related admissions, based on a variety of modalities (clinical variables, inflammatory markers, clinical scores, or combinations thereof). The models performed moderately well in the validation cohort and were better able to predict mortality than liver-related admissions. In conclusion, markers of inflammation can be used to predict 180-day mortality in patients with newly diagnosed cirrhosis. Prediction models for newly diagnosed cirrhotic patients need further validation before implementation in clinical practice.
OriginalsprogEngelsk
Artikelnummer20039
TidsskriftScientific Reports
Vol/bind13
Antal sider11
ISSN2045-2322
DOI
StatusUdgivet - 2023

Bibliografisk note

Funding Information:
This project received funding from the Beckett Foundation (Grant No: 20-2-6102). During the study, NK was employed as a postdoctoral fellow in translational medicine at Copenhagen University, Center for Basic Metabolic Research via a grant from Novo Nordisk Foundation (SABridge.ku.dk). HW was supported by the Novo Nordisk Foundation (Grant NNF19SA0035440). HW and SR were supported by the Novo Nordisk Foundation (Grants NNF14CC0001, NNF21SA0072102). HBJ, RTJ, and TH were supported by Challenge grants from the Novo Nordisk Foundation (NNF18CC0034900, NNF15OC0016692).

Publisher Copyright:
© 2023, The Author(s).

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