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Decision-making algorithm for ascending aortic aneurysm: Effectiveness in clinical application?

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This summary is machine-generated.

Patients with ascending thoracic aortic aneurysms who did not follow surgical recommendations had worse outcomes. An algorithm using size and symptoms effectively identified patients needing surgery, preventing complications.

Keywords:
aortic dissectionaortic ruptureclinical careclinical outcomesdecision makingnatural historythoracic aortathoracic aortic aneurysm

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Area of Science:

  • Cardiovascular Surgery
  • Aortic Diseases
  • Medical Algorithms

Background:

  • Ascending thoracic aortic aneurysms (ATAA) pose a risk of rupture and dissection, particularly when diameters exceed 5 cm.
  • Preemptive surgical intervention is crucial for managing ATAA and preventing life-threatening complications.

Purpose of the Study:

  • To evaluate the clinical effectiveness of a size and symptom-based algorithm for preemptive surgery in patients with ATAA.
  • To compare outcomes between patients who adhered to surgical recommendations and those who did not.

Main Methods:

  • A retrospective analysis of 781 patients with ATAA from 2011-2017.
  • Patients were triaged to surgery (>5 cm or symptomatic) or medical observation using a specific algorithm.
  • Outcomes were compared between patients who did not undergo surgery (noncompliant/comorbidities vs. medical management groups).

Main Results:

  • Patients noncompliant with surgery recommendations (n=128) had significantly higher rates of aortic events (13.3% vs. 1.7%) and death (15.6% vs. 3.3%) compared to the medically managed group (n=181).
  • Aortic events occurred in 17 patients in the noncompliant group versus 3 in the medical group (P < .001).
  • Mortality was significantly higher in the noncompliant group (20 deaths) compared to the medical group (6 deaths) (P < .001).

Conclusions:

  • Non-adherence to surgical recommendations for ATAA significantly worsens patient outcomes.
  • The size and symptom-based algorithm effectively identified high-risk patients for surgery in a clinical setting.
  • The algorithm demonstrated clinical utility in stratifying patients for ATAA management.