ePoster
Presentation Description
Institution: Alfred Health - Victoria, Australia
Purpose:
AAS requires swift diagnosis and management. The international multicentre Collaborative Acute Aortic Syndrome Project (CAASP) aims to evaluate AAS diagnosis and management. Our centre evaluated 56 AAS cases for CAASP and identified predictors of key AAS outcomes.
Methodology:
All patients with a thoracoabdominal CT from the 1st of January 2018 to the 1st of June 2021 were reviewed for AAS. Clinical, management, and mortality data were collected from the medical record. Statistical analysis was performed in RStudio.
Results:
We identified 54 AAS cases. Of the 6 treated endovascularly, 5 survived after 6 months.
In univariate analysis, heart rate, creatinine (Cr), estimated glomerular filtration rate (eGFR), and ischaemic limb predicted death at discharge. Deprivation decile, platelets, Cr, eGFR, and ischaemic limb predicted 30 day mortality. Age, deprivation decile, platelets, alanine transaminase (ALT), and complicated pathology predicted 90 day mortality. Age, deprivation decile, and platelets predicted 6 month mortality. Treatment type, admission ward type, critical care admission, COVID status, and diabetes mellitus (DM) history predicted admission length. Acute myocardial infarct (AMI) history, previous PCI, intravenous (IV) antihypertensive use, c-reactive protein, DM, and murmur predicted critical care admission length. Migratory pain predicted time to presentation. Deprivation decile, severe pain, migratory pain, family history, murmur, pulse deficit, ischaemic limb, shock, and tamponade predicted time to plan.
In multivariate analysis, after adjustment, admission length was associated with age and treatment type; critical care stay length was associated with AMI history and IV antihypertensive use.
Conclusion:
This study identifies several factors influencing outcomes in patients with AAS including age, AMI history and IV antihypertensive use. Further research utilising pooled data from this multi-centre study may identify key predictors for AAS outcomes.
Speakers
Authors
Authors
Dr Aaron Tran - , Dr Matthew Lukies -