Background: Acute type A aortic dissection (ATAAD) is a heterogeneous systemic inflammatory response syndrome. Identification of distinct inflammatory phenotypes may allow more precise therapy and improved care. We aim to investigate whether distinct inflammatory subphenotypes exist in ATAAD patients and respond differently to pharmacotherapies.
Methods: Retrospective analysis of data sets was conducted from the Additive Anti-inflammatory Actions for Aortopathy & Arteriopathy (5A) III study. Inflammatory subphenotypes were derived among 2008 ATAAD patients who received surgical repair at 11 Chinese hospitals (2016-2020) using latent class analysis applied to 14 laboratory signatures within 6 hours of hospital admission. Outcomes included operative mortality (Society of Thoracic Surgeons definition), derived subphenotype frequency, and the potential consequences of phenotype frequency distributions on the treatment effects.
Results: The median (interquartile range) age of patients was 54 (45-62) years, and 1423 (70.9%) were male. A two-class (two subphenotype) model was an improvement over a one-class model (P<·001), with 1451 (72.3%) patients in the hypoinflammatory subphenotype group and 557 (27.7%) in the hyperinflammatory subphenotype group. Patients with the hyperinflammatory subphenotype had higher operative mortality (71 [12.7%] vs 127 [8.8%]; P=0·007) than did those with the hypoinflammatory subphenotype. Furthermore, the interaction between ulinastatin treatment and subphenotype is not significant for operative mortality (P=0.15) but for ventilator time (P=0·04).
Conclusion: Two subphenotypes of ATAAD were identified in the 5A cohort that correlated with clinical outcomes, with significant interaction effect between anti-inflammatory treatment and subphenotypes for ventilator time, suggesting these phenotypes may help in understanding heterogeneity of treatment effects.
Trial registration: Clinical Trials. Gov: number NCT04918108.
Keywords: aortic dissection; inflammatory response; latent class analysis.
© 2022 Liu et al.