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Updated: Jan 28, 2026

Novel and Innovative Hybrid Technique for Type A Aortic Dissection
Published on: March 28, 2025
Perioperative Cerebral Protection and Monitoring of Acute Stanford Type A Aortic Dissection: A Retrospective Cohort
Yi Jiang1,2,3, Jianing Wang1,2,3, Chang Liu2,3
1Department of Thoracic and Cardiovascular Surgery, Nanjing Drum Tower Hospital, Graduate School of Peking Union Medical College, Chinese Academy of Medical Science & Peking Union Medical College, Peking Union Medical College Graduate School, Nanjing 210008, China.
Background:
Optimal cerebral protection strategies for acute Stanford type A aortic dissection (aTAAD) surgery remain controversial. This study aimed to evaluate the role of near-infrared spectroscopy (NIRS)-guided monitoring and its association with clinical outcomes.
Methods:
We retrospectively analyzed 619 patients undergoing aTAAD surgery (Hemi-Arch, Total-Arch, or Arch-Stent procedures). Intraoperative cerebral oxygenation was monitored using NIRS, with the magnitude of desaturation quantified as ΔNIRS. We assessed correlations between ΔNIRS and nasopharyngeal temperature, employed generalized additive models (GAM) to analyze nonlinear relationships with major adverse cardiovascular events (MACE), and used piecewise logistic regression to identify procedure-specific ΔNIRS risk thresholds.
Results:
ΔNIRS showed a significant positive correlation with lower temperatures in Total-Arch (R = 0.486, p < 0.001) and Arch-Stent (R = 0.216, p < 0.001) groups. GAM analysis revealed a nonlinear, accelerating relationship between higher ΔNIRS and increased log odds of MACE in Hemi-Arch and Total-Arch groups. Procedure-specific ΔNIRS thresholds were identified: 8.5% for Hemi-Arch, 19.6% for Total-Arch, and 20.9% for Arch-Stent. Patients with ΔNIRS above these thresholds had significantly higher rates of stroke and MACE.
Conclusions:
This study identifies ΔNIRS as a significant, procedure-dependent intraoperative monitoring indicator in aTAAD surgery, and the proposed risk thresholds provide a rationale for real-time NIRS-guided clinical decision-making.
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