Is Left Ventricular Global Longitudinal Strain by Two-Dimensional Speckle Tracking Echocardiography in Sepsis Cardiomyopathy Ready for Prime Time Use in the ICU

Myocardial deformation imaging (strain imaging) is a technique to directly quantify the extent of myocardial contractility and overcomes several of the limitations of ejection fraction. The application of the most commonly used strain imaging method; speckle-tracking echocardiography to patients with sepsis cardiomyopathy heralds an exciting development to the field. However; the body of evidence and knowledge on the utility, feasibility and prognostic value of left ventricular global longitudinal strain in sepsis cardiomyopathy is still evolving. We conducted a review of literature on utility of left ventricular global longitudinal strain in sepsis cardiomyopathy. We discuss the role of left ventricular global longitudinal strain in mortality prediction, utility and limitations of the technique in the context of sepsis cardiomyopathy

Circulating Cell and Plasma microRNA Profiles Differ between Non-ST-Segment and ST-Segment-Elevation Myocardial Infarction

BACKGROUND: Differences in plasma and whole blood expression microRNAs (miRNAs) in patients with an acute coronary syndrome (ACS) have been determined in both in vitro and in vivo studies. Although most circulating miRNAs are located in the cellular components of whole blood, little is known about the miRNA profiles of whole blood subcomponents, including plasma, platelets and leukocytes in patients with myocardial ischemia. METHODS: Thirteen patients with a ST-segment-elevation (STEMI) or non-ST-segment elevation (NSTEMI) myocardial infarction were identified in the University of Massachusetts Medical Center Emergency Department (ED) or cardiac catheterization laboratory between February and June of 2012. Whole blood was obtained from arterial blood samples at the time of cardiac catheterization and cell-specific miRNA profiling was performed. Expression of 343 miRNAs was quantified from whole blood, plasma, platelets, and peripheral blood mononuclear cells using a high-throughput, quantitative Real-Time polymerase-chain reaction system (qRT-PCR). RESULTS: MiRNAs associated with STEMI as compared to NSTEMI patients included miR-25-3p, miR-221-3p, and miR-374b-5p. MiRNA 30d-5p was associated with plasma, platelets, and leukocytes in both STEMI and NSTEMI patients; miRNAs 221-3p and 483-5p were correlated with plasma and platelets only in NSTEMI patients. CONCLUSIONS: Cell-specific miRNA profiles differed between patients with STEMI and NSTEMI. The miRNA distribution is also unique amongst plasma, platelets, and leukocytes in patients with ischemic heart disease or ACS. Our findings suggest unique miRNA profiles among the circulating subcomponents in patients presenting with myocardial ischemia

Recent Trends in the Incidence, Treatment, and Prognosis of Patients With Heart Failure and Atrial Fibrillation (the Worcester Heart Failure Study)

Atrial fibrillation (AF) and heart failure (HF) are common cardiovascular diseases and the co-occurrence of AF and HF has been associated with reduced survival. Data are needed on the potentially changing trends in the characteristics, treatment, and prognosis of patients with acute decompensated HF (ADHF) and AF. The study population consisted of 9,748 patients hospitalized with ADHF at 11 hospitals in the Worcester, Massachusetts, metropolitan area during 4 study years (1995, 2000, 2002, and 2004). Of the 9,748 patients admitted with ADHF, 3,868 (39.7%) had a history of AF and 449 (4.6%) developed new-onset AF during hospitalization. The rates of new-onset AF remained stable (4.9% in 1995; 5.0% in 2004), but the proportion of patients with pre-existing AF (34.5% in 1995; 41.6% in 2004) increased over time. New-onset and pre-existing AF were associated with older age, but pre-existing AF was more closely linked to a greater co-morbid disease burden. The use of HF therapies did not differ greatly by AF status. Despite this, new-onset AF was associated with a longer length of stay (7.5 vs 6.1 days) and greater in-hospital death rates (11.4% vs 6.6%). In contrast, pre-existing AF was associated with lower rates of postdischarge survival compared to patients with no AF (p In conclusion, AF was common among patients with ADHF, and the proportion of ADHF patients with co-occurring AF increased during the study period. Despite improving trends in survival, patients with ADHF and AF are at increased risk of in-hospital and postdischarge mortality

A novel application for the detection of an irregular pulse using an iPhone 4S in patients with atrial fibrillation

BACKGROUND: Atrial fibrillation (AF) is common and associated with adverse health outcomes. Timely detection of AF can be challenging using traditional diagnostic tools. Smartphone use is increasing and may provide an inexpensive and user-friendly means to diagnose AF. OBJECTIVE: To test the hypothesis that a smartphone-based application could detect an irregular pulse from AF. METHODS: Seventy-six adults with persistent AF were consented for participation in our study. We obtained pulsatile time series recordings before and after cardioversion using an iPhone 4S camera. A novel smartphone application conducted real-time pulse analysis using 2 statistical methods: root mean square of successive RR difference (RMSSD/mean) and Shannon entropy (ShE). We examined the sensitivity, specificity, and predictive accuracy of both algorithms using the 12-lead electrocardiogram as the gold standard. RESULTS: RMSDD/mean and ShE were higher in participants in AF than in those with sinus rhythm. The 2 methods were inversely related to AF in regression models adjusting for key factors including heart rate and blood pressure (beta coefficients per SD increment in RMSDD/mean and ShE were-0.20 and-0.35; P CONCLUSIONS: In a prospectively recruited cohort of 76 participants undergoing cardioversion for AF, we found that a novel algorithm analyzing signals recorded using an iPhone 4S accurately distinguished pulse recordings during AF from sinus rhythm. Data are needed to explore the performance and acceptability of smartphone-based applications for AF detection