Takotsubo cardiomyopathy (TCM), characterized by reversible ventricular dysfunction, has similar mortality to acute coronary syndrome. With the growing interest in the diagnosis of and interventions for TCM, many risk factors had been found to affect the prognosis of TCM patients, such as age, sex, and pre-existing diseases. Because of the incomplete understanding of the pathophysiologic mechanism in TCM, evidence-based medical therapy for this condition is lacking. Early intervention on risk factors may improve the outcomes of TCM. In this review, we sought to provide up-to-date evidence on risk factors and medical therapies that affect TCM outcome. We found that male sex, physical triggers, and certain comorbidities such as chronic kidney disease, malignant disease, higher body mass index, sepsis, chronic obstructive pulmonary disease, and anaemia were associated with poor TCM prognosis. In contrast, race, hyperlipidaemia, diabetes mellitus, and mood disorders were not clearly associated with TCM prognosis. We also reviewed the effect of medical therapies on TCM outcome, including angiotensin-converting enzyme inhibitors/angiotensin receptor blockers, β-blockers, calcium channel blockers, and statins. The evidence that these medications confer a survival benefit on TCM patients is limited. Understanding these prognostic factors could help develop risk-stratification tools for TCM and establish effective prevention and interventions for this notso-benign condition. Further multicentre clinical studies with large samples and meta-analyses of findings from previous studies are needed to address the inconsistent findings among the many potential risk factors for TCM.

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.

Background Recent studies suggest that non-alcoholic fatty liver disease (NAFLD) in lean (BMI<25 ​kg/m 2 ) individuals presents a distinct phenotype. We sought to determine the cardiometabolic consequences of lean NAFLD in a population cohort of relatively young asymptomatic individuals who participated in a voluntary routine health promotion evaluation in Brazil. Methods We analyzed data in our population collected from 2004 to 2016. Medical and demographic history, anthropometric measures, and fasting blood samples were obtained. Participants had ultrasonography to assess for fatty liver. We defined NAFLD as fatty liver in individuals scoring below 8 on the alcohol use disorders identification test (AUDIT). We included data from 9137 individuals who had complete data at baseline and at follow-up. Results The prevalence of lean NAFLD in our cohort was 3.8%. Over the median follow-up period of 2.4 years (range 0.5–9.9 years), lean individuals had 74% (HR: 1.74 (1.39–2.18)) and 67% (1.67 (1.29–2.15)) greater risk of developing elevated BP and elevated glucose, and nearly 3 times the risk of atherogenic dyslipidemia (HR: 2.98 (2.10–4.24)) compared to lean individuals without NAFLD. Lean NAFLD individuals also had higher risk of developing elevated glucose (HR: 1.37 (1.07–1.75)) and atherogenic dyslipidemia (1.46 (1.05–2.01)) compared to non-lean individuals without NAFLD. However, there was no significant difference in the risk of elevated BP, elevated glucose or atherogenic dyslipidemia between lean NAFLD and non-lean individuals with NAFLD in fully adjusted models. Conclusion Lean NAFLD is not metabolically benign. Further cardiovascular risk stratification and appropriate preventive measures should be considered in lean individuals who present with NAFLD.

Chronic obstructive pulmonary disease (COPD) is a known comorbidity of takotsubo cardiomyopathy (TCM), and COPD exacerbation is a potential triggering factor of TCM. The association between COPD and in-hospital outcomes and complications among TCM patients is not well established. We sought to assess the effect of COPD on hospitalized patients with a primary diagnosis of TCM. Methods: We conducted a retrospective cohort study in patients with a primary diagnosis of TCM with or without COPD using the latest National Inpatient Sample from 2016-2017. We identified 3139 patients admitted with a primary diagnosis of TCM by the ICD-10-CM coding system; 684 of those patients also had a diagnosis of COPD. We performed propensity score matching in a 1:2 ratio (n=678 patients, matched COPD group; n=1070, matched non-COPD group) and compared in-hospital outcomes and complications between TCM patients with and without a COPD diagnosis. Results: Before matching, the COPD group had worse outcomes compared with the non-COPD group in inpatient death (2.9% vs 1.3%, p=0.006), length of stay (LOS) (4.02±2.99 days vs 3.27±3.39 days, p<0.001), hospitalization charges ($55,242.68±47,637.40 vs $48,316.97±47,939.84, p=0.001), and acute respiratory failure (ARF) (22.5% vs 7.7%, p<0.001), respectively. After propensity score matching, the matched COPD group, compared with the matched non-COPD group, had a higher inpatient mortality rate (2.9% vs1.0%, p=0.005), longer LOS (4.02±3.00 days vs 3.40±3.54 days, p<0.001), higher hospitalization charges ($55,409.23±47,809.13 vs $46,469.60±42,209.10, p<0.001), and a higher incidence of ARF (22.6% vs 8.2%, p<0.001) and cardiogenic shock (5.6% vs 3.3%, p=0.024), respectively. Conclusion: Patients with COPD who are hospitalized for TCM have higher rates of inpatient mortality, ARF, cardiogenic shock, as well as a longer LOS, and higher charges of stay than those without COPD. Prospective studies are warranted to examine the effect of early intervention or treatment of COPD on short-and long-term outcomes of TCM.

Background Coronavirus disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or COVID-19) is a heterogeneous disorder with a complex pathogenesis. Recent studies from Spain and France have indicated that underlying phenotypes may exist among patients admitted to the hospital with COVID-19. Whether those same phenotypes exist in the United States (US) remains unclear. Using latent class analysis (LCA), we sought to determine whether clinical phenotypes exist among patients admitted for COVID-19. Methods We reviewed the charts of adult patients who were hospitalized primarily for COVID-19 at Greenwich Hospital and performed LCA using variables based on patient demographics and comorbidities. To further examine the reliability and replicability of the clustering results, we repeated LCA on the cohort of patients who died during hospitalization for COVID-19. Results Two phenotypes were identified in patients admitted for COVID-19 (N = 483). According to phenotype, patients were designated as cluster 1 (C1) or cluster 2 (C2). C1 (n = 193) consisted of older individuals with more comorbidities and a higher mortality rate (25.4% vs 8.97%, p < 0.001) than patients in C2. C2 (n = 290) consisted of younger individuals who were more likely to be obese, male, and nonwhite, with higher levels of the inflammatory markers C-reactive protein and alanine aminotransferase. When we performed LCA on the cohort of patients who died during hospitalization for COVID-19 (n = 75), we found that the distribution of patient baseline characteristics and comorbidities was similar to that of the entire cohort of patients admitted for COVID-19. Conclusion Using LCA, we identified two clinical phenotypes of patients who were admitted to our hospital for COVID-19. These findings may reflect different pathophysiologic processes that lead to moderate to severe COVID-19 and may be useful for identifying treatment targets and selecting patients with severe COVID-19 disease for future clinical trials.