Journal of electrocardiology
-
For the past several years ECRI Institute has published a list of Top Ten Health Technology Hazards. This list is based on ECRI's extensive research in health technology safety and on data provided to its problemreporting systems. For every year that the Top Ten list has been published, Alarm Hazards have been at or near the top of the list. ⋯ It also requires careful selection of alarm setting criteria for each clinical care area. This article will overview the clinical alarm problems that have been identified through ECRI Institute's research and analysis of various problem reporting databases, including those operated by ECRI Institute. It will also highlight suggestions for improvement, particularly from a technology design and technology management perspective.
-
Classic symptoms of long QT syndrome (LQTS) include prolongation of QT interval on electrocardiograph, syncope, and cardiac arrest due to a distinctive form of polymorphic ventricular tachycardia, known as Torsade de Pointes. We assessed occurrence of LQTS signs in individuals from 30 Czech families with mutations in KCNQ1 and KCNH2 genes. ⋯ Incidence of classical signs of LQTS was not high in Czech carriers of KCNQ1 and KCNH2 mutations. Therefore, proper diagnosis relies on detection of symptoms at presentation. The exercise test may be beneficial owing to its high sensitivity and specificity for LQTS diagnosis.
-
Due to a lack of integration between different sensors, false alarms (FA) in the intensive care unit (ICU) are frequent and can lead to reduced standard of care. We present a novel framework for FA reduction using a machine learning approach to combine up to 114 signal quality and physiological features extracted from the electrocardiogram, photoplethysmograph, and optionally the arterial blood pressure waveform. ⋯ For the ventricular tachycardia alarms, the best FA suppression performance was 30.5% with a TA suppression rate below 1%. To reduce the TA suppression rate to zero, a reduction in FA suppression performance to 19.7% was required.
-
A statistical modelling study investigated whether incorporating the curvatures of QT/RR patterns into the individual-specific QT heart rate correction increases QTc data accuracy. ⋯ The differences in the curvatures of QT/RR patterns should be considered in the optimisation of subject-specific heart rate corrections. Forcing an arbitrary simple regression model on the QT/RR patterns of different subjects may lead to appreciable errors in QTc estimates. The frequently used linear and log-linear regression models were among the least precise if used without checking their appropriateness in individual subjects.