A Deep Learning Approach to Examine Ischemic ST Changes in Ambulatory ECG Recordings.

Patients with suspected acute coronary syndrome (ACS) are at risk of transient myocardial ischemia (TMI), which could lead to serious morbidity or even mortality. Early detection of myocardial ischemia can reduce damage to heart tissues and improve patient condition. Significant ST change in the electrocardiogram (ECG) is an important marker for detecting myocardial ischemia during the rule-out phase of potential ACS. However, current ECG monitoring software is vastly underused due to excessive false alarms. The present study aims to tackle this problem by combining a novel image-based approach with deep learning techniques to improve the detection accuracy of significant ST depression change. The obtained convolutional neural network (CNN) model yields an average area under the curve (AUC) at 89.6% from an independent testing set. At selected optimal cutoff thresholds, the proposed model yields a mean sensitivity at 84.4% while maintaining specificity at 84.9%

Electrocardiographic indicators of acute coronary syndrome are more common in patients with ambulance transport compared to those who self-transport to the emergency department journal of electrocardiology

The American Heart Association recommends individuals with symptoms suggestive of acute coronary syndrome (ACS) activate the Emergency Medical Services’ (EMS) 911 system for ambulance transport to the emergency department (ED), which enables treatment to begin prior to hospital arrival. Despite this recommendation, the majority of patients with symptoms suspicious of ACS continue to self-transport to the ED. The IMMEDIATE AIM study was a prospective study that enrolled individuals who presented to the ED with ischemic symptoms

Patient characteristics associated with false arrhythmia alarms in intensive care

A high rate of false arrhythmia alarms in the intensive care unit (ICU) leads to alarm fatigue, the condition of desensitization and potentially inappropriate silencing of alarms due to frequent invalid and nonactionable alarms, often referred to as false alarms

Gender-Specific Characteristics of Individuals With Depressive Symptoms and Coronary Heart Disease

Objective In individuals with depressive symptoms and coronary heart disease (CHD), little is known about gender-specific characteristics that may inform treatments and outcomes. This study sought to identify characteristics that distinguish men from women with both conditions. Methods By cross-sectional design, 1951 adults with CHD and elevated depressive symptoms completed questionnaires to measure anxiety, hostility, perceived control, and knowledge, attitudes, and beliefs about CHD. Gender differences were evaluated by multivariable logistic regression. Results Women were more likely to be single (odds ratio [OR] 3.61, P \u3c .001), to be unemployed (OR 2.52, P \u3c .001), to be poorly educated (OR 2.52, P \u3c .001), to be anxious (OR 1.14, P \u3c .01), and to perceive lower control over health (OR 1.34, P \u3c .01) than men. Conclusion Women with CHD and depressive symptoms have fewer resources, greater anxiety, and lower perceived control than men. In women, targeting modifiable factors, such as anxiety and perceived control, is warranted

Rapid 5 lb Weight Gain Is Not Associated with Readmission in Patients with Heart Failure

Aims Heart failure (HF) patients are taught to identify a rapid 5 lb body‐weight gain for early detection of cardiac decompensation. Few data support this common advice. The study aim was to determine whether a 5 lb weight gain in 1 week and signs and symptoms of HF increased risk for unplanned physician or emergency department (ED) visits or hospital admission in rural HF patients. Methods and results This was a secondary analysis of a randomized trial. Patients tracked body weight and HF symptoms using diaries. We included patients adherent to daily diaries \u3e 50% over 24 months (N = 119). Mean age was 69 ± 11 years; 77% (65) were male, and 67% completed diaries. A weight gain of 5 lb over 7 days was associated with a greater risk for ED visits but not hospital admission [hazard ratio (HR) 1.06, 95% confidence interval (CI) 1.04, 1.08; P \u3c 0.0001 vs. HR 1.01, 95% CI 0.88, 1.16; P = 0.79]. Increased dyspnoea over 7 days was associated with a greater risk of ED visits and hospital admissions (HR 9.64, 95% CI 3.68, 25.22; P \u3c 0.0001 vs. HR 5.89, 95% CI 1.73, 20.04; P = 0.01). Higher diary adherence was associated with older age, non‐sedentary behaviour, lower depression, and HF knowledge. Conclusions Heart failure patients are counselled to observe for body‐weight gain. Our data do not support that a 5 lb weight gain was associated with hospital admission. Dyspnoea was a better predictor of ED visits and hospital admissions. Daily tracking of dyspnoea symptoms may be an important adjunct to daily weight to prevent hospitalization