# Fibrinogen-to-Albumin Ratio as Predictor of Mortality in Acute Aortic Syndromes

## TL;DR

This study shows that the fibrinogen-to-albumin ratio can predict 30-day mortality in patients with acute aortic syndromes.

## Contribution

The study introduces the fibrinogen-to-albumin ratio as a novel, simple, and cost-effective predictor of mortality in acute aortic syndrome patients.

## Key findings

- Non-survivors had a significantly lower fibrinogen-to-albumin ratio than survivors.
- The fibrinogen-to-albumin ratio was independently associated with 30-day mortality after adjusting for multiple clinical factors.

## Abstract

Background: Acute aortic syndrome (AAS) is a life-threatening condition characterized by a high mortality, yet reliable prognostic biomarkers are still lacking. The fibrinogen-to-albumin ratio (FAR) has recently gained attention in cardiovascular research but has not been explored in the context of AAS. This study assessed the association between the FAR and 30-day mortality in AAS patients who presented to the emergency department. Methods: We included all AAS patients aged 18 years and older who presented to the emergency department between 2013 and 2021. The outcome measured was 30-day all-cause mortality. Cox regression analysis assessed the relationship between the FAR and the outcome. Results: A total of 171 patients (mean age 67, SD 13.7; 33% female) were included, with 68 (40%) dying within 30 days of admission. Non-survivors had a significantly lower FAR (mean 8.9, SD 4.97) than survivors (mean 10.8, SD 5.44, p = 0.02). FAR was significantly associated with 30-day mortality (crude HR 0.935, 95% CI 0.88–0.99, p = 0.02). This association remained significant after adjusting for age, sex, cardiopulmonary resuscitation, catecholamine administration, bleeding on admission, and type of AAS (adjusted HR 0.92, 95% CI 0.87–0.98, p = 0.01). Conclusions: FAR was independently associated with 30-day mortality in AAS patients who presented to the emergency department. Given its simplicity and cost-effectiveness, it could be a valuable biomarker, especially in resource-limited settings, to improve risk assessment and optimize resource allocation in AAS.