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. 2023 Sep 26;26(10):108044.
doi: 10.1016/j.isci.2023.108044. eCollection 2023 Oct 20.

Biomarkers of alcohol abuse potentially predict delirium, delirium duration and mortality in critically ill patients

Nikolaus Schreiber  1   2 , Alexander C Reisinger  1 , Stefan Hatzl  1 , Nikolaus Schneider  1 , Laura Scholz  1 , Markus Herrmann  3 , Michael Kolland  2 , Max Schuller  2 , Alexander H Kirsch  2 , Kathrin Eller  2 , Christiane Kink  1 , Simon Fandler-Höfler  4 , Alexander R Rosenkranz  2 , Gerald Hackl  1 , Philipp Eller  1
Affiliations

Biomarkers of alcohol abuse potentially predict delirium, delirium duration and mortality in critically ill patients

Nikolaus Schreiber et al. iScience. .

Abstract

Carbohydrate-deficient transferrin (CDT) and the γ-glutamyltransferase-CDT derived Anttila-Index are established biomarkers for sustained heavy alcohol consumption and their potential role to predict delirium and mortality in critically ill patients is not clear. In our prospective observational study, we included 343 consecutive patients admitted to our ICU, assessed the occurrence of delirium and investigated its association with biomarkers of alcohol abuse measured on the day of ICU admission. 35% of patients developed delirium during ICU stay. We found significantly higher CDT levels (p = 0.011) and Anttila-Index (p = 0.001) in patients with delirium. CDT above 1.7% (OR 2.06), CDT per percent increase (OR 1.26, AUROC 0.75), and Anttila-Index per unit increase (OR 1.28, AUROC 0.74) were associated with delirium development in adjusted regression models. Anttila-Index and CDT also correlated with delirium duration exceeding 5 days. Additionally, Anttila-Index above 4, Anttila-Index per unit increase, and CDT per percent increase were independently associated with hospital mortality.

Keywords: clinical finding; medical science.

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Conflict of interest statement

The authors declared no competing interests.

Figures

None
Graphical abstract
Figure 1
Figure 1
Patient flow diagram.
Figure 2
Figure 2
Potential predictors for development of ICU-delirium (A–D) Predicted probabilities to develop ICU delirium were derived from binary logistic regression for (A) Anttila-Index (p < 0.001), (B) carbohydrate-deficient transferrin (CDT) (p = 0.008), (C) Sequential Organ Failure Assessment (SOFA)-score (p < 0.001), and (D) serum albumin (p < 0.001), respectively. Shaded areas depict 95% confidence intervals.
Figure 3
Figure 3
Carbohydrate-deficient transferrin and Anttila-Index are potential predictors of ICU-delirium (A–C) Multivariable logistic regression models for (A) carbohydrate-deficient transferrin (CDT) above cutoff 1.7% (OR 2.06, 95% CI 1.10–3.84, p = 0.023), (B) CDT per percent increase (OR 1.26, 95% CI 1.03–1.60, p = 0.036), and (C) Anttila-Index per unit increase (OR 1.28, 95% CI 1.04–1.60, p = 0.023) after adjustment for Sequential Organ Failure Assessment (SOFA)-score, serum albumin, mechanical ventilation and age. p values of Hosmer-Lemeshow-Tests were 0.74, 0.83, and 0.98, respectively.
Figure 4
Figure 4
Receiver operating characteristic curves for CDT [%] and the Anttila-Index Receiver operating characteristic (ROC) curves to evaluate the predictive and discriminative ability of CDT (black line) and the Anttila-Index (gray line) for development of ICU-delirium are shown. Respective areas under the receiver operating characteristic curves (AUROC) are depicted as well. AUROC, area under the receiver operating characteristic curve; ROC, receiver operating characteristic; CDT, Carbohydrate deficient transferrin; ICU, Intensive care unit.
Figure 5
Figure 5
Kaplan-Meier survival curve 30-day Kaplan-Meier survival estimates for critically ill patients with Anttila-Index below 4 (black line) and Anttila-Index above 4 (gray line). Three patients were not considered because of missing values for γ-glutamyltransferase.
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