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Updated: May 5, 2026

Quantitative Analysis and Characterization of Atherosclerotic Lesions in the Murine Aortic Sinus
Published on: December 7, 2013
[Clinical phenotyping of acute aortic dissection patients: a latent class analysis based on a multicenter
Abudunaibi Balati1, W H Wang2, X W He1
1Division of Cardiology, Department of Internal Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hubei Provincial Engineering Research Center of Vascular Interventional Therapy, Wuhan 430030, China.
Insights
Latent class analysis identified two distinct clinical subtypes of acute aortic dissection (AAD). These subtypes exhibit different characteristics and responses to treatment, aiding in personalized patient care and prognosis.
Area of Science:
- Cardiovascular Medicine
- Medical Statistics
- Clinical Research
Background:
- Acute aortic dissection (AAD) is a life-threatening condition with varied clinical presentations.
- Current classification systems may not fully capture the heterogeneity of AAD.
- Understanding distinct patient subgroups is crucial for optimizing treatment and outcomes.
Purpose of the Study:
- To identify and characterize clinical subtypes of acute aortic dissection (AAD) using latent class analysis.
- To compare the clinical features and in-hospital mortality between identified AAD subtypes.
- To explore differential treatment responses based on the identified subtypes.
Main Methods:
- A multicenter retrospective cohort study involving 2,689 AAD patients.
- Latent class analysis was employed to classify patients based on clinical and biological characteristics.
- Model fitting evaluations determined the optimal number of latent classes.
- Clinical data and in-hospital mortality were analyzed and compared across subtypes.
Main Results:
- Latent class analysis identified two optimal subtypes of AAD.
- Clinical subtype 2, compared to subtype 1, showed higher rates of female patients, older age, ascending aorta involvement, organ dysfunction, and inflammatory response.
- Clinical subtype 2 had significantly higher in-hospital mortality, particularly among surgically treated patients.
Conclusions:
- Latent class analysis successfully identified two distinct clinical subtypes of AAD.
- These subtypes possess unique clinical profiles and differential responses to surgical intervention.
- Findings support individualized clinical decision-making and prognostic assessment for AAD patients.
Abstract:
Objective: To investigate the clinical subtypes of acute aortic dissection (AAD) through latent class analysis. Methods: This study was a multicenter retrospective cohort study. Patients with AAD admitted to five hospitals, including Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Henan Provincial People's Hospital, Central China Fuwai Hospital of Zhengzhou University (Fuwai Central China Cardiovascular Hospital), the Third Affiliated Hospital of Xinxiang Medical University and the Second Affiliated Hospital of Chongqing Medical University, between August 2010 and December 2021 were enrolled. Based on clinical and biological characteristics, latent class analysis (models with 2 to 5 latent classes) was conducted to classify the enrolled patients. The optimal classification scheme was determined using model fitting evaluations, including log-likelihood (LL), entropy, Lo-Mendell-Rubin adjusted likelihood ratio test and so on. Clinical data of different subtypes were compared, and in-hospital mortality was analyzed across the entire population and among subgroups receiving different treatments. Results: A total of 2 689 AAD patients, aged 54 (46, 63) years were included, with 1 305 (48.5%) having DeBakey type Ⅰ, 156 (5.8%) type Ⅱ, and 1 228 (45. 7%) type Ⅲ dissections. The cohort comprised 2 134 (79.4%) males. The overall in-hospital mortality rate was 22.8% (613/2 689). Latent class analysis indicated that a two-class model was optimal (LL=147 413.242, entropy=0.812, and PLMRT<0.001). Patients were classified into two subtypes, named clinical subtype 1 and clinical subtype 2. Compared to clinical subtype 1, clinical subtype 2 had a higher proportion of females, was older, had more dissections involving the ascending aorta, and exhibited higher rates of organ dysfunction (elevated alanine aminotransferase and creatinine levels) and inflammatory response (neutrophilia) (all P<0.05). Clinical subtype 2 also showed higher in-hospital mortality compared to subtype 1 (26.3% (238/905) vs. 21.0% (375/1 784), P=0.002). Among patients undergoing surgical treatment, clinical subtype 2 had higher mortality than subtype 1 (40.1% (67/167) vs. 30.0% (101/337), P=0.027). However, no significant differences in mortality were observed between the two subtypes among patients receiving medical therapy or endovascular and hybrid procedures (all P>0.05). Conclusions: Comprehensive latent class analysis identifies two subtypes of AAD with distinct clinical characteristics and treatment responses. These findings provide new insights into individualized clinical decision-making and prognostic evaluation for AAD patients.
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