An unusual left ventricular outflow tract mass in a patient with systemic lupus erythematosus.

A 25-year-old female, with systemic lupus erythematosus and antiphospholipid antibody syndrome, presented with exertional dyspnoea. Echocardiography showed a large (2.0 cm × 1.1 cm), echogenic, heterogeneous mass in the left ventricular outflow tract, under the aortic valve, attached to the ventricular aspect of the anterior mitral leaflet. Tiny flagellar, frond-like structures were seen attached to the surface of the mass. There was mitral regurgitation. These echocardiographic features were suggestive of a papillary fibroelastoma, but the histopathology of the excised mass revealed it to be a thrombus, which was consistent with a diagnosis of non-bacterial thrombotic endocarditis (NBTE). This case represents a rare histopathologically confirmed NBTE presenting as an unusually large mass in the left ventricular outflow tract.

Development of ST-elevation Myocardial Infarction Programs in Developing Countries: Global Challenges and Solutions.

Cardiovascular disease (CVD) is the leading cause of death worldwide; approximately 80% of CVD deaths occur in low-income and middle-income countries (LMICs). The epidemiologic transition to a high burden of ischemic heart disease (IHD) has happened with greater rapidity in LMICs than in high-income countries. The absolute number of individuals with premature IHD has increased substantially. Higher event rates are observed compared with high-income countries. The technological capability to do extraordinary things for patients has increased, as has patient demand, in a setting of constrained resources and expensive health care of variable quality.

Predictive Model Based on Health Data Analysis for Risk of Readmission in Disease-Specific Cohorts.

Background: Intervention planning to reduce 30-day readmission post-acute myocardial infarction (AMI) in an environment of resource scarcity can be improved by readmission prediction score. The aim of study is to derive and validate a prediction model based on routinely collected hospital data for identification of risk factors for all-cause readmission within zero to 30 days post discharge from AMI. Methods: Our study includes 2,849 AMI patient records (January 2005 to December 2014) from a tertiary care facility in India. EMR with ICD-10 diagnosis, admission, pathological, procedural and medication data is used for model building. Model performance is analyzed for different combination of feature groups and diabetes sub-cohort. The derived models are evaluated to identify risk factors for readmissions. Results: The derived model using all features has the highest discrimination in predicting readmission, with AUC as 0.62; (95 percent confidence interval) in internal validation with 70/30 split for derivation and validation. For the sub-cohort of diabetes patients (1359) the discrimination is slightly better with AUC 0.66; (95 percent CI;). Some of the positively associated predictive variables, include age group 80-90, medicine class administered during index admission (Anti-ischemic drugs, Alpha 1 blocker, Xanthine oxidase inhibitors), additional procedure in index admission (Dialysis). While some of the negatively associated predictive variables, include patient demography (Male gender), medicine class administered during index admission (Betablocker, Anticoagulant, Platelet inhibitors, Anti-arrhythmic). Conclusions: Routinely collected data in the hospital's clinical and administrative data repository can identify patients at high risk of readmission following AMI, potentially improving AMI readmission rate.

Confronting system barriers for ST- elevation MI in low and middle income countries with a focus on India.

Our previous research found seven specific factors that cause system delays in ST-elevation Myocardial infarction management in developing countries. These delays, in conjunction with a lack of organized STEMI systems of care, result in inefficient processes to treat AMI in developing countries. In our present opinion paper, we have specifically explored the three most pertinent causes that afflict the seven specific factors responsible for system delays. In doing so, we incorporated a unique strategy of global STEMI expertise. With this methodology, the recommendations were provided by expert Indian cardiologist and final guidelines were drafted after comprehensive discussions by the entire group of submitting authors. We expect these recommendations to be utilitarian in improving STEMI care in developing countries.