Journal of clinical monitoring and computing
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J Clin Monit Comput · Oct 2013
Heart rate variability indices for very short-term (30 beat) analysis. Part 2: validation.
Heart rate variability (HRV) analysis over shorter periods may be useful for monitoring dynamic changes in autonomic nervous system activity where steady-state conditions are not maintained (e.g. during drug administration, or the start or end of exercise). This study undertakes a validation of 70 HRV indices that have previously been identified as possible for short-term use. The indices were validated over 10 × 30 beat windows using PhysioNet databases with physiological states of rest, active, exercising, sleeping, and meditating (N from 12 to 20). ⋯ Spectral indices using the Lomb-Scargle algorithm were able to correctly identify paradoxical shifts in power with meditation and reduced power in exercise. Some less-known indices gave interesting results: PolVar20 identified the higher sympathetic activity of exercise with the largest positive magnitude. These indices should now be considered for rigorous gold standard tests with pharmacological blockade.
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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.
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J Clin Monit Comput · Aug 2013
ReviewPotential of surface acoustic wave biosensors for early sepsis diagnosis.
Early diagnosis of sepsis is a difficult problem for intensivists and new biomarkers for early diagnosis have been difficult to come by. Here we discuss the potential of adapting a technology from the electronics industry, surface acoustic wave (SAW) sensors, for diagnosis of multiple markers of sepsis in real time, using non-invasive assays of exhaled breath condensate. The principles and advantages of the SAW technology are reviewed as well as a proposed plan for adapting this flexible technology to early sepsis detection.
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J Clin Monit Comput · Aug 2013
Impaired cerebrovascular reactivity after acute traumatic brain injury can be detected by wavelet phase coherence analysis of the intracranial and arterial blood pressure signals.
The objective of the study was to evaluate the wavelet spectral energy of oscillations in the intracranial pressure (ICP) signal in patients with acute traumatic brain injury (TBI). The wavelet phase coherence and phase shift in the 0.006-2 Hz interval between the ICP and the arterial blood pressure (ABP) signals were also investigated. Patients were separated into normal or impaired cerebrovascular reactivity, based on the pressure reactivity index (PRx). ⋯ We conclude that the wavelet transform of the ICP signal shows spectral peaks at the cardiac, respiratory and 0.03 Hz frequencies. Normal cerebrovascular reactivity seems to be manifested as increased spectral energy in the frequency interval <0.14 Hz. A phase shift between the ICP and ABP signals in the interval 0.07-0.14 Hz indicates normal cerebrovascular reactivity, while a phase shift in the interval 0.006-0.07 Hz indicates altered cerebrovascular reactivity.
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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.