Identifying different phenotypes in takotsubo cardiomyopathy by latent class analysis

Area of Science:

• Cardiology
• Medical Informatics
• Clinical Research

Background:

• Takotsubo cardiomyopathy (TCM) is a complex heart condition with poorly understood causes.
• TCM presents as a heterogeneous disorder, necessitating a deeper understanding of its varied clinical presentations.

Purpose of the Study:

• To identify distinct clinical clusters within takotsubo cardiomyopathy patient population.
• To better understand the heterogeneity of TCM through phenotyping.

Main Methods:

• Latent class analysis (LCA) was performed on a large sample of 3139 TCM patients from the National Inpatient Sample (NIS) database (2016-2017).
• Analysis utilized patient demographics and comorbidities including age, sex, hypertension, hyperlipidaemia, diabetes, obesity, smoking, COPD, and anxiety/depressive disorders.
• Results were validated using separate 2016 and 2017 NIS datasets, and in-hospital outcomes were compared across identified clusters.

Main Results:

• Four distinct clinical phenotypes (clusters) of TCM were identified.
• Cluster 1 (39.4%) showed high prevalence of hyperlipidaemia, hypertension, and diabetes, with lowest in-hospital mortality (1.0%) and shortest length of stay.
• Cluster 2 (14.0%) comprised patients with COPD and smoking history, exhibiting the highest in-hospital mortality (3.4%). Cluster 3 (11.8%) consisted of patients with anxiety and depressive disorders.
• Cluster 4 (34.8%) represented patients with isolated TCM and minimal comorbidities.

Conclusions:

• The identified clinical phenotypes may represent different underlying pathophysiological processes in TCM.
• These findings can aid in identifying specific treatment targets for TCM.
• The identified clusters can assist in patient selection for future clinical trials in takotsubo cardiomyopathy research.