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Updated: Jul 26, 2025

Novel and Innovative Hybrid Technique for Type A Aortic Dissection
Published on: March 28, 2025
Inflammatory risk stratification individualizes anti-inflammatory pharmacotherapy for acute type A aortic dissection
Hong Liu1, Haiyang Li2, Lu Han3
1Department of Cardiovascular Surgery, First Affiliated Hospital of Nanjing Medical University, Nanjing 210029, China.
Artificial intelligence identified optimal patients for ulinastatin treatment in acute type A aortic dissection (ATAAD). This approach personalizes anti-inflammatory therapy by predicting individual risk for multiple organ dysfunction syndrome (MODS).
Area of Science:
- Cardiovascular Medicine
- Artificial Intelligence in Healthcare
- Pharmacotherapy Optimization
Background:
- Systemic benefits of anti-inflammatory drugs vary in cardiovascular diseases.
- Acute type A aortic dissection (ATAAD) management requires precise therapeutic strategies.
- Predicting multiple organ dysfunction syndrome (MODS) is crucial for patient outcomes.
Purpose of the Study:
- To apply artificial intelligence (AI) for identifying patients with ATAAD who benefit most from ulinastatin.
- To develop and validate an inflammatory risk model predicting MODS in ATAAD patients.
- To personalize anti-inflammatory treatment selection based on individual risk and treatment effect.
Main Methods:
- Utilized the Chinese multicenter 5A study database (2016-2022) with 5,126 ATAAD patients.
- Developed an AI-driven inflammatory risk model using an extreme gradient-boosting (XGBoost) algorithm.
- Validated the model's predictive performance for MODS using key clinical features.
Main Results:
- A parsimonious six-feature risk model (eGFR, leukocytes, platelets, De Ritis ratio, hemoglobin, albumin) demonstrated strong predictive ability.
- AI identified specific patient subgroups with differential benefits from ulinastatin use based on predicted MODS risk.
- Ulinastatin showed a reduced risk ratio for MODS in patients with a predicted risk between 23.5%-41.6%.
Conclusions:
- AI-driven risk stratification enables personalized selection of anti-inflammatory therapy for ATAAD patients.
- Individualized treatment strategies considering risk probability and treatment effect are essential for optimizing ulinastatin use.
- This approach highlights the need for tailoring anti-inflammatory treatment goals in ATAAD management.
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