Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Feb;8(1):555-565.
doi: 10.1002/ehf2.13117. Epub 2020 Nov 26.

Identifying different phenotypes in takotsubo cardiomyopathy by latent class analysis

Pengyang Li  1 , Qiying Dai  2 , Peng Cai  3 , Catherine Teng  4 , Su Pan  5 , Richard A F Dixon  5 , Qi Liu  5
Affiliations

Identifying different phenotypes in takotsubo cardiomyopathy by latent class analysis

Pengyang Li et al. ESC Heart Fail. 2021 Feb.

Abstract

Aims: This study sought to determine whether clinical clusters exist in takotsubo cardiomyopathy. Takotsubo cardiomyopathy (TCM) is a heterogeneous disorder with a complex, poorly understood pathogenesis. To better understand the heterogeneity of TCM, we identified different clinical phenotypes in a large sample of TCM patients by using latent class analysis (LCA).

Methods and results: Using the National Inpatient Sample (NIS) database, we identified 3139 patients admitted to hospitals in 2016-2017 with a primary diagnosis of TCM. We performed LCA based on several patient demographics and comorbidities: age, sex, hypertension, hyperlipidaemia, diabetes mellitus, obesity, current smoking, asthma, chronic obstructive pulmonary disease (COPD), and anxiety and depressive disorders. We then repeated LCA separately with the NIS 2016 and 2017 data sets and performed a robust test to validate our results. We also compared in-hospital outcomes among the different clusters identified by LCA. Four patient clusters were identified. C1 (n = 1228, 39.4%) had the highest prevalence of hyperlipidaemia (93.4%), hypertension (61.6%), and diabetes (34.3%). In C2 (n = 440, 14.0%), all patients had COPD, and many were smokers (45.8%). C3 (n = 376, 11.8%) largely comprised patients with anxiety disorders (98.4%) and depressive disorders (80.1%). C4 (n = 1097, 34.8%) comprised patients with isolated TCM and few comorbidities. Among all clusters, C1 had the lowest in-hospital mortality (1.0%) and the shortest length of stay (3.2 ± 3.1 days), whereas C2 had the highest in-hospital mortality (3.4%).

Conclusions: Using LCA, we identified four clinical phenotypes of TCM. These may reflect different pathophysiological processes in TCM. Our findings may help identify treatment targets and select patients for future clinical trials.

Keywords: Latent class analysis; Phenotype; Takotsubo cardiomyopathy.

PubMed Disclaimer

Conflict of interest statement

None declared.

Figures

Figure 1
Figure 1
Patient selection. Flowchart showing the process by which patients were selected for this study from the 2016 and 2017 National Inpatient Sample databases. Patients with takotsubo cardiomyopathy were identified by ICD‐10‐CM code I51.81. ICD‐10‐CM, International Classification of Diseases, Tenth Revision, Clinical Modification; TCM, takotsubo cardiomyopathy.
Figure 2
Figure 2
Risk factors in Cluster 1 (metabolic disease). (A) Combined 2016 and 2017 NIS data. (B) 2016 NIS data. (C) 2017 NIS data. (D) Distribution of variables. COPD, chronic obstructive pulmonary disease; HLD, hyperlipidaemia; HTN, hypertension; IRP, item response probabilities; NIS, National Inpatient Sample.
Figure 3
Figure 3
Risk factors in Cluster 2 (COPD and smoking). (A) Combined 2016 and 2017 NIS data. (B) 2016 NIS data. (C) 2017 NIS data. (D) Distribution of variables. COPD, chronic obstructive pulmonary disease; HLD, hyperlipidaemia; HTN, hypertension; IRP, item response probabilities; NIS, National Inpatient Sample.
Figure 4
Figure 4
Risk factors in Cluster 3 (psychiatric disorders). (A) Combined 2016 and 2017 NIS data. (B) 2016 NIS data. (C) 2017 NIS data. (D) Distribution of variables. COPD, chronic obstructive pulmonary disease; HLD, hyperlipidaemia; HTN, hypertension; IRP, item response probabilities; NIS, National Inpatient Sample.
Figure 5
Figure 5
Risk factors in Cluster 4 (minimal risk factors). (A) Combined 2016 and 2017 NIS data. (B) 2016 NIS data. (C) 2017 NIS data. (D). Distribution of variables. COPD, chronic obstructive pulmonary disease; HLD, hyperlipidaemia; HTN, hypertension; IRP, item response probabilities; NIS, National Inpatient Sample.
See this image and copyright information in PMC

References

    1. Gianni M, Dentali F, Grandi AM, Sumner G, Hiralal R, Lonn E. Apical ballooning syndrome or takotsubo cardiomyopathy: a systematic review. Eur Heart J 2006; 27: 1523–1529. - PubMed
    1. Medina de Chazal H, Del Buono MG, Keyser‐Marcus L, Ma L, Moeller FG, Berrocal D, Abbate A. Stress cardiomyopathy diagnosis and treatment: JACC state‐of‐the‐art review. J Am Coll Cardiol 2018; 72: 1955–1971. - PMC - PubMed
    1. Templin C, Ghadri JR, Diekmann J, Napp LC, Bataiosu DR, Jaguszewski M, Cammann VL, Sarcon A, Geyer V, Neumann CA, Seifert B, Hellermann J, Schwyzer M, Eisenhardt K, Jenewein J, Franke J, Katus HA, Burgdorf C, Schunkert H, Moeller C, Thiele H, Bauersachs J, Tschöpe C, Schultheiss HP, Laney CA, Rajan L, Michels G, Pfister R, Ukena C, Böhm M, Erbel R, Cuneo A, Kuck KH, Jacobshagen C, Hasenfuss G, Karakas M, Koenig W, Rottbauer W, Said SM, Braun‐Dullaeus RC, Cuculi F, Banning A, Fischer TA, Vasankari T, Airaksinen KEJ, Fijalkowski M, Rynkiewicz A, Pawlak M, Opolski G, Dworakowski R, MacCarthy P, Kaiser C, Osswald S, Galiuto L, Crea F, Dichtl W, Franz WM, Empen K, Felix SB, Delmas C, Lairez O, Erne P, Bax JJ, Ford I, Ruschitzka F, Prasad A, Lüscher TF. Clinical features and outcomes of takotsubo (stress) cardiomyopathy. N Engl J Med 2015; 373: 929–938. - PubMed
    1. Redfors B, Vedad R, Angerås O, Råmunddal T, Petursson P, Haraldsson I, Ali A, Dworeck C, Odenstedt J, Ioaness D, Libungan B, Shao Y, Albertsson P, Stone GW, Omerovic E. Mortality in takotsubo syndrome is similar to mortality in myocardial infarction—a report from the SWEDEHEART registry. Int J Cardiol 2015; 185: 282–289. - PubMed
    1. Naegele M, Flammer AJ, Enseleit F, Roas S, Frank M, Hirt A, Kaiser P, Cantatore S, Templin C, Fröhlich G, Romanens M, Lüscher TF, Ruschitzka F, Noll G, Sudano I. Endothelial function and sympathetic nervous system activity in patients with takotsubo syndrome. Int J Cardiol 2016; 224: 226–230. - PubMed