Journal of clinical monitoring and computing
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J Clin Monit Comput · Aug 2013
Predictive data mining on monitoring data from the intensive care unit.
The widespread implementation of computerized medical files in intensive care units (ICUs) over recent years has made available large databases of clinical data for the purpose of developing clinical prediction models. The typical intensive care unit has several information sources from which data is electronically collected as time series of varying time resolutions. ⋯ On the one hand we examine short and medium term predictions, which have as ultimate goal the development of early warning or decision support systems. On the other hand we examine long term outcome prediction models and evaluate their performance with respect to established scoring systems based on static admission and demographic data.
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J Clin Monit Comput · Aug 2013
A simple model of the right atrium of the human heart with the sinoatrial and atrioventricular nodes included.
Existing atrial models with detailed anatomical structure and multi-variable cardiac transmembrane current models are too complex to allow to combine an investigation of long time dycal properties of the heart rhythm with the ability to effectively simulate cardiac electrical activity during arrhythmia. Other ways of modeling need to be investigated. Moreover, many state-of-the-art models of the right atrium do not include an atrioventricular node (AVN) and only rarely--the sinoatrial node (SAN). ⋯ Our simulations support the hypothesis that the alternans of the conduction time between the atria and the ventricles in the AV orthodromic reciprocating tachycardia can occur within a single pathway. In the atrial parasystole simulation, we found a mathematical condition which allows for a rough estimation of the location of the parasystolic source within the atrium, both for simplified (planar) and the cylindrical geometry of the atrium. The planar and the cylindrical geometry yielded practically the same results of simulations.
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J Clin Monit Comput · Aug 2013
Observational StudyReduced complexity of intracranial pressure observed in short time series of intracranial hypertension following traumatic brain injury in adults.
Physiological parameters, such as intracranial pressure (ICP), are regulated by interconnected feedback loops, resulting in a complex time course. According to the decomplexification theory, disease is characterised by a loss of feedback loops resulting in a reduced complexity of the time course of physiological parameters. We hypothesized that complexity of the ICP time series is decreased during periods of intracranial hypertension (IHT) following adult traumatic brain injury. ⋯ In addition, MSE revealed a significantly (p < 0.05) decreased entropy at scaling factors ranging from 1 to 10. Both the increase in α as well as the decrease in SampEn and MSE indicate a loss of ICP complexity. Therefore following traumatic brain injury, periods of IHT seem to be characterised by a decreased complexity of the ICP waveform.
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J Clin Monit Comput · Aug 2013
The use of heart rate variability for the early detection of treatable complications after aneurysmal subarachnoid hemorrhage.
High-grade aneurysmal subarachnoid hemorrhage patients are monitored in the ICU for up to 21 days, as they are at risk for complications such as vasospasm of cerebral arteries, cardiac arrhythmias and neurogenic stress cardiomyopathy. The diagnosis of these treatable complications is often delayed by the limitations of monitoring capabilities. We applied computational analysis to a cohort of 24 aneurysmal subarachnoid hemorrhage patients, to identify heart rate variability and ECG frequency profiles that may be potential biomarkers of severe vasospasm, reversible cardiomyopathy and death.
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J Clin Monit Comput · Aug 2013
ReviewConnecting the dots: rule-based decision support systems in the modern EMR era.
The intensive care unit (ICU) environment is rich in both medical device and electronic medical record (EMR) data. The ICU patient population is particularly vulnerable to medical error or delayed medical intervention both of which are associated with excess morbidity, mortality and cost. ⋯ False alerts and alert fatigue remain prevalent. In the coming era of widespread EMR implementation novel medical informatics methods may be adaptable to the development of next generation, rule-based DSS.