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

Introduction 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. Objective The aim of this study was to identify patient characteristics, such as gender, age, body mass index, and diagnosis associated with frequent false arrhythmia alarms in the ICU. Methods This descriptive, observational study prospectively enrolled patients who were consecutively admitted to one of five adult ICUs (77 beds) at an urban medical center over a period of 31 days in 2013. All monitor alarms and continuous waveforms were stored on a secure server. Nurse scientists with expertise in cardiac monitoring used a standardized protocol to annotate six clinically important types of arrhythmia alarms (asystole, pause, ventricular fibrillation, ventricular tachycardia, accelerated ventricular rhythm, and ventricular bradycardia) as true or false. Total monitoring time for each patient was measured, and the number of false alarms per hour was calculated for these six alarm types. Medical records were examined to acquire data on patient characteristics. Results A total of 461 unique patients (mean age =60±17 years) were enrolled, generating a total of 2,558,760 alarms, including all levels of arrhythmia, parameter, and technical alarms. There were 48,404 hours of patient monitoring time, and an average overall alarm rate of 52 alarms/hour. Investigators annotated 12,671 arrhythmia alarms; 11,345 (89.5%) were determined to be false. Two hundred and fifty patients (54%) generated at least one of the six annotated alarm types. Two patients generated 6,940 arrhythmia alarms (55%). The number of false alarms per monitored hour for patients’ annotated arrhythmia alarms ranged from 0.0 to 7.7, and the duration of these false alarms per hour ranged from 0.0 to 158.8 seconds. Patient characteristics were compared in relation to 1) the number and 2) the duration of false arrhythmia alarms per 24-hour period, using nonparametric statistics to minimize the influence of outliers. Among the significant associations were the following: age ≥60 years (P=0.013; P=0.034), confused mental status (P\u3c0.001 for both comparisons), cardiovascular diagnoses (P\u3c0.001 for both comparisons), electrocardiographic (ECG) features, such as wide ECG waveforms that correspond to ventricular depolarization known as QRS complex due to bundle branch block (BBB) (P=0.003; P=0.004) or ventricular paced rhythm (P=0.002 for both comparisons), respiratory diagnoses (P=0.004 for both comparisons), and support with mechanical ventilation, including those with primary diagnoses other than respiratory ones (P\u3c0.001 for both comparisons). Conclusion Patients likely to trigger a higher number of false arrhythmia alarms may be those with older age, confusion, cardiovascular diagnoses, and ECG features that indicate BBB or ventricular pacing, respiratory diagnoses, and mechanical ventilatory support. Algorithm improvements could focus on better noise reduction (eg, motion artifact with confused state) and distinguishing BBB and paced rhythms from ventricular arrhythmias. Increasing awareness of patient conditions that apparently trigger a higher rate of false arrhythmia alarms may be useful for reducing unnecessary noise and improving alarm management

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

ƴ-Selective directed catalytic asymmetric hydroboration of 1,1-disubstituted alkenes

Directed catalytic asymmetric hydroborations of 1,1-disubstituted alkenes afford ƴ -dioxaborato amides and esters in high enantiomeric purity (90–95% ee)

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