Novel subgroups in acute respiratory failure based on the trajectories of three endotheliopathy biomarkers: A cohort study

Changes in nitric oxide inhibitors and mortality in critically ill patients: a cohort study

BACKGROUND

Optimal balance between macro- and microcirculation in critically ill patients is crucial for ensuring optimal organ perfusion. Nitric oxide (NO) is a regulator of vascular hemostasis and tone. The availability of NO is controlled by asymmetric dimethylarginine (ADMA), symmetric dimethylarginine (SDMA), and the availability of the NO substrates arginine and homoarginine. We investigated the changes in plasma concentrations of ADMA, SDMA, arginine, and homoarginine days 1-5 of intensive care unit (ICU) admission and the association between the change in concentration days 1-3 and 30-day all-cause mortality.

METHODS

Single-center cohort study of adult critically ill patients from the ICU at Copenhagen University Hospital - North Zealand. ADMA, SDMA, arginine, and homoarginine (NO-biomarkers) were measured on days 1-5. Initially, we determined the changes in NO-biomarkers days 1-5 with linear mixed models, and subsequently how the changes in NO-biomarkers days 1-3 were associated with 30-day all-cause mortality. Post-hoc we analyzed the association between plasma concentration at admission and 30-day all-cause mortality.

RESULTS

In total 567 out of 577 patients had plasma samples from days 1-5. Plasma concentrations of ADMA and arginine increased from days 1-5. SDMA concentrations increased from days 1-2, followed by a decrease from days 2-5. Concentrations of homoarginine did not change from days 1-3 but slightly increased from days 3-5. In total 512 patients were alive 3 days after ICU admission. Among these patients, a daily twofold increase in ADMA concentration from days 1-3 was associated with decreased mortality in multivariate analysis (HR 0.45; 95% CI 0.21-0.98; p = 0.046). An increase in SDMA, arginine, or homoarginine was not associated with mortality. Post-hoc we found that a twofold increase in ADMA or SDMA concentrations at admission was associated with mortality (HR 1.78; 95% CI 1.24-2.57; p = 0.0025, and HR 1.41; 95% CI 1.05-1.90; p = 0.024, respectively).

CONCLUSIONS

Increasing ADMA concentrations on days 1-3 are inversely associated with mortality, however not with the same strength as high ADMA or SDMA concentrations at admission. We suggest that admission concentrations are the focus of future research on ADMA and SDMA as predictors of mortality or potential therapeutical targets in ICU patients.

LASSO regression shows histidine and sphingosine 1 phosphate are linked to both sepsis mortality and endothelial damage

Sepsis is a major cause of death worldwide, with a mortality rate that has remained stubbornly high. The current gold standard of risk stratifying sepsis patients provides limited mechanistic insight for therapeutic targeting. An improved ability to predict sepsis mortality and to understand the risk factors would allow better treatment targeting. Sepsis causes metabolic dysregulation in patients; therefore, metabolomics offers a promising tool to study sepsis. It is also known that that in sepsis endothelial cells affecting their function regarding blood clotting and vascular permeability. We integrated metabolomics data from patients admitted to an intensive care unit for sepsis, with commonly collected clinical features of their cases and two measures of endothelial function relevant to blood vessel function, platelet endothelial cell adhesion molecule and soluble thrombomodulin concentrations in plasma. We used least absolute shrinkage and selection operator penalized regression, and pathway enrichment analysis to identify features most able to predict 30-day survival. The features important to sepsis survival include carnitines, and amino acids. Endothelial proteins in plasma also predict 30-day mortality and the levels of these proteins also correlate with a somewhat overlapping set of metabolites. Overall metabolic dysregulation, particularly in endothelial cells, may be a contributory factor to sepsis response. By exploring sepsis metabolomics data in conjunction with clinical features and endothelial proteins we have gained a better understanding of sepsis risk factors.