Impact of atrial fibrillation on outcome in Takotsubo syndrome: data from the international Takotsubo registry

Background Atrial fibrillation (AF) is a major risk factor for mortality. The prevalence, clinical correlates, and prognostic impact of AF in Takotsubo syndrome (TTS) have not yet been investigated in a large patient cohort. This study aimed to investigate the prevalence, clinical correlates, and prognostic impact of AF in patients with TTS. Methods and Results Patients with TTS were enrolled from the International Takotsubo Registry, which is a multinational network with 26 participating centers in Europe and the United States. Patients were dichotomized according to the presence or absence of AF at the time of admission. Of 1584 patients with TTS, 112 (7.1%) had AF. The mean age was higher (P<0.001), and there were fewer women (P=0.046) in the AF than in the non-AF group. Left ventricular ejection fraction was significantly lower (P=0.001), and cardiogenic shock was more often observed (P<0.001) in the AF group. Both in-hospital (P<0.001) and long-term mortality (P<0.001) were higher in the AF group. Multivariable Cox regression analysis revealed that AF was independently associated with higher long-term mortality (hazard ratio, 2.31; 95% CI, 1.50-3.55; P<0.001). Among patients with AF on admission, 42% had no known history of AF before the acute TTS event, and such patients had comparable in-hospital and long-term outcomes compared with those with a history of AF. Conclusions In patients presenting with TTS, AF on admission is significantly associated with increased in-hospital and long-term mortality rates. Whether antiarrhythmics and/or cardioversion are beneficial in TTS with AF should thus be tested in a future trial. Registration URL: ; Unique identifier: NCT01947621.Cardiolog

Prognostic impact of acute pulmonary triggers in patients with takotsubo syndrome: new insights from the International Takotsubo Registry

Aims Acute pulmonary disorders are known physical triggers of takotsubo syndrome (TTS). This study aimed to investigate prevalence of acute pulmonary triggers in patients with TTS and their impact on outcomes.Methods and results Patients with TTS were enrolled from the International Takotsubo Registry and screened for triggering factors and comorbidities. Patients were categorized into three groups (acute pulmonary trigger, chronic lung disease, and no lung disease) to compare clinical characteristics and outcomes.Of the 1670 included patients with TTS, 123 (7%) were identified with an acute pulmonary trigger, and 194 (12%) had a known history of chronic lung disease. The incidence of cardiogenic shock was highest in patients with an acute pulmonary trigger compared with those with chronic lung disease or without lung disease (17% vs. 10% vs. 9%, P = 0.017). In-hospital mortality was also higher in patients with an acute pulmonary trigger than in the other two groups, although not significantly (5.7% vs. 1.5% vs. 4.2%, P = 0.13). Survival analysis demonstrated that patients with an acute pulmonary trigger had the worst long-term outcome (P = 0.002). The presence of an acute pulmonary trigger was independently associated with worse long-term mortality (hazard ratio 2.12, 95% confidence interval 1.33-3.38; P = 0.002).Conclusions The present study demonstrates that TTS is related to acute pulmonary triggers in 7% of all TTS patients, which accounts for 21% of patients with physical triggers. The presence of acute pulmonary trigger is associated with a severe in-hospital course and a worse long-term outcome.Cardiolog

Ethnic comparison in takotsubo syndrome: novel insights from the International Takotsubo Registry

Background Ethnic disparities have been reported in cardiovascular disease. However, ethnic disparities in takotsubo syndrome (TTS) remain elusive. This study assessed differences in clinical characteristics between Japanese and European TTS patients and determined the impact of ethnicity on in-hospital outcomes.Methods TTS patients in Japan were enrolled from 10 hospitals and TTS patients in Europe were enrolled from 32 hospitals participating in the International Takotsubo Registry. Clinical characteristics and in-hospital outcomes were compared between Japanese and European patients.Results A total of 503 Japanese and 1670 European patients were included. Japanese patients were older (72.6 +/- 11.4 years vs. 68.0 +/- 12.0 years; p < 0.001) and more likely to be male (18.5 vs. 8.4%; p< 0.001) than European TTS patients. Physical triggering factors were more common (45.5 vs. 32.0%; p < 0.001), and emotional triggers less common (17.5 vs. 31.5%; p < 0.001), in Japanese patients than in European patients. Japanese patients were more likely to experience cardiogenic shock during the acute phase (15.5 vs. 9.0%; p < 0.001) and had a higher in-hospital mortality (8.2 vs. 3.2%; p< 0.001). However, ethnicity itself did not appear to have an impact on in-hospital mortality. Machine learning approach revealed that the presence of physical stressors was the most important prognostic factor in both Japanese and European TTS patients.Conclusion Differences in clinical characteristics and in-hospital outcomes between Japanese and European TTS patients exist. Ethnicity does not impact the outcome in TTS patients. The worse in-hospital outcome in Japanese patients, is mainly driven by the higher prevalence of physical triggers.Cardiolog

Multimodality imaging in takotsubo syndrome: a joint consensus document of the European Association of Cardiovascular Imaging (EACVI) and the Japanese Society of Echocardiography (JSE) (vol 21, pg 1184, 2020)

In the original publication of the article, the first and the second authors' names should be changed as follows.Cardiolog

Multimodality imaging in takotsubo syndrome: a joint consensus document of the European Association of Cardiovascular Imaging (EACVI) and the Japanese Society of Echocardiography (JSE)

Takotsubo syndrome (TTS) is a complex and still poorly recognized heart disease with a wide spectrum of possible clinical presentations. Despite its reversibility, it is associated with serious adverse in-hospital events and high complication rates during follow-up. Multimodality imaging is helpful for establishing the diagnosis, guiding therapy, and stratifying prognosis of TTS patients in both the acute and post-acute phase. Echocardiography plays a key role, particularly in the acute care setting, allowing for the assessment of left ventricular (LV) systolic and diastolic function and the identification of the typical apical-midventricular ballooning pattern, as well as the circumferential pattern of watt motion abnormalities. It is also useful in the early detection of complications (i.e. LV outflow tract obstruction, mitral regurgitation, right ventricular involvement, LV thrombi, and pericardial effusion) and monitoring of systolic function recovery. Left ventriculography allows the evaluation of LV function and morphology, identifying the typical US patterns when echocardiography is not available or wall motion abnormalities cannot be properly assessed with ultrasound. Cardiac magnetic resonance provides a more comprehensive depiction of cardiac morphology and function and tissue characterization and offers additional value to other imaging modalities for differential diagnosis (myocardial infarction and myocarditis). Coronary computed tomography angiography has a substantial role in the diagnostic workup of patients with acute chest pain and a doubtful US diagnosis to rule out other medical conditions. It can be considered as a non-invasive appropriate alternative to coronary angiography in several clinical scenarios. Although the rote of nuclear imaging in US has not yet been well established, the combination of perfusion and metabolic imaging may provide useful information on myocardial function in both the acute and post-acute phase.Cardiolog

Pathophysiology of Takotsubo syndrome - a joint scientific statement from the Heart Failure Association Takotsubo Syndrome Study Group and Myocardial Function Working Group of the European Society of Cardiology - Part 2: vascular pathophysiology, gender and sex hormones, genetics, chronic cardiovascular problems and clinical implications

While the first part of the scientific statement on the pathophysiology of Takotsubo syndrome was focused on catecholamines and the sympathetic nervous system, in the second part we focus on the vascular pathophysiology including coronary and systemic vascular responses, the role of the central and peripheral nervous systems during the acute phase and abnormalities in the subacute phase, the gender differences and integrated effects of sex hormones, genetics of Takotsubo syndrome including insights from microRNA studies and inducible pluripotent stem cell models of Takotsubo syndrome. We then discuss the chronic abnormalities of cardiovascular physiology in survivors, the limitations of current clinical and preclinical studies, the implications of the knowledge of pathophysiology for clinical management and future perspectives and directions of research

Assessment of Artificial Intelligence in Echocardiography Diagnostics in Differentiating Takotsubo Syndrome From Myocardial Infarction

IMPORTANCE Machine learning algorithms enable the automatic classification of cardiovascular diseases based on raw cardiac ultrasound imaging data. However, the utility of machine learning in distinguishing between takotsubo syndrome (TTS) and acute myocardial infarction (AMI) has not been studied.Objectives To assess the utility of machine learning systems for automatic discrimination of TTS and AMI.Design, Settings, and Participants This cohort study included clinical data and transthoracic echocardiogram results of patients with AMI from the Zurich Acute Coronary Syndrome Registry and patients with TTS obtained from 7 cardiovascular centers in the International Takotsubo Registry. Data from the validation cohort were obtained from April 2011 to February 2017. Data from the training cohort were obtained from March 2017 to May 2019. Data were analyzed from September 2019 to June 2021.Exposure Transthoracic echocardiograms of 224 patients with TTS and 224 patients with AMI were analyzed.Main Outcomes and Measures Area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity of the machine learning system evaluated on an independent data set and 4 practicing cardiologists for comparison. Echocardiography videos of 228 patients were used in the development and training of a deep learning model. The performance of the automated echocardiogram video analysis method was evaluated on an independent data set consisting of 220 patients. Data were matched according to age, sex, and ST-segment elevation/non-ST-segment elevation (1 patient with AMI for each patient with TTS). Predictions were compared with echocardiographic-based interpretations from 4 practicing cardiologists in terms of sensitivity, specificity, and AUC calculated from confidence scores concerning their binary diagnosis.Results In this cohort study, apical 2-chamber and 4-chamber echocardiographic views of 110 patients with TTS (mean [SD] age, 68.4 [12.1] years; 103 [90.4%] were female) and 110 patients with AMI (mean [SD] age, 69.1 [12.2] years; 103 [90.4%] were female) from an independent data set were evaluated. This approach achieved a mean (SD) AUC of 0.79 (0.01) with an overall accuracy of 74.8 (0.7%). In comparison, cardiologists achieved a mean (SD) AUC of 0.71 (0.03) and accuracy of 64.4 (3.5%) on the same data set. In a subanalysis based on 61 patients with apical TTS and 56 patients with AMI due to occlusion of the left anterior descending coronary artery, the model achieved a mean (SD) AUC score of 0.84 (0.01) and an accuracy of 78.6 (1.6%), outperforming the 4 practicing cardiologists (mean [SD] AUC, 0.72 [0.02]) and accuracy of 66.9 (2.8%).Conclusions and Relevance In this cohort study, a real-time system for fully automated interpretation of echocardiogram videos was established and trained to differentiate TTS from AMI. While this system was more accurate than cardiologists in echocardiography-based disease classification, further studies are warranted for clinical application

Assessment of Artificial Intelligence in Echocardiography Diagnostics in Differentiating Takotsubo Syndrome From Myocardial Infarction

IMPORTANCE Machine learning algorithms enable the automatic classification of cardiovascular diseases based on raw cardiac ultrasound imaging data. However, the utility of machine learning in distinguishing between takotsubo syndrome (TTS) and acute myocardial infarction (AMI) has not been studied.Objectives To assess the utility of machine learning systems for automatic discrimination of TTS and AMI.Design, Settings, and Participants This cohort study included clinical data and transthoracic echocardiogram results of patients with AMI from the Zurich Acute Coronary Syndrome Registry and patients with TTS obtained from 7 cardiovascular centers in the International Takotsubo Registry. Data from the validation cohort were obtained from April 2011 to February 2017. Data from the training cohort were obtained from March 2017 to May 2019. Data were analyzed from September 2019 to June 2021.Exposure Transthoracic echocardiograms of 224 patients with TTS and 224 patients with AMI were analyzed.Main Outcomes and Measures Area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity of the machine learning system evaluated on an independent data set and 4 practicing cardiologists for comparison. Echocardiography videos of 228 patients were used in the development and training of a deep learning model. The performance of the automated echocardiogram video analysis method was evaluated on an independent data set consisting of 220 patients. Data were matched according to age, sex, and ST-segment elevation/non-ST-segment elevation (1 patient with AMI for each patient with TTS). Predictions were compared with echocardiographic-based interpretations from 4 practicing cardiologists in terms of sensitivity, specificity, and AUC calculated from confidence scores concerning their binary diagnosis.Results In this cohort study, apical 2-chamber and 4-chamber echocardiographic views of 110 patients with TTS (mean [SD] age, 68.4 [12.1] years; 103 [90.4%] were female) and 110 patients with AMI (mean [SD] age, 69.1 [12.2] years; 103 [90.4%] were female) from an independent data set were evaluated. This approach achieved a mean (SD) AUC of 0.79 (0.01) with an overall accuracy of 74.8 (0.7%). In comparison, cardiologists achieved a mean (SD) AUC of 0.71 (0.03) and accuracy of 64.4 (3.5%) on the same data set. In a subanalysis based on 61 patients with apical TTS and 56 patients with AMI due to occlusion of the left anterior descending coronary artery, the model achieved a mean (SD) AUC score of 0.84 (0.01) and an accuracy of 78.6 (1.6%), outperforming the 4 practicing cardiologists (mean [SD] AUC, 0.72 [0.02]) and accuracy of 66.9 (2.8%).Conclusions and Relevance In this cohort study, a real-time system for fully automated interpretation of echocardiogram videos was established and trained to differentiate TTS from AMI. While this system was more accurate than cardiologists in echocardiography-based disease classification, further studies are warranted for clinical application.Cardiolog