Journal of clinical monitoring and computing
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J Clin Monit Comput · Aug 2023
Towards autoregulation-oriented management after traumatic brain injury: increasing the reliability and stability of the CPPopt algorithm.
CPPopt denotes a Cerebral Perfusion Pressure (CPP) value at which the Pressure-Reactivity index, reflecting the global state of Cerebral Autoregulation, is best preserved. CPPopt has been investigated as a potential dynamically individualised CPP target in traumatic brain injury patients admitted in intensive care unit. The prospective bedside use of the concept requires ensured safety and reliability of the CPP recommended targets based on the automatically-generated CPPopt. We aimed to: Increase stability and reliability of the CPPopt automated algorithm by fine-tuning; perform outcome validation of the adjusted algorithm in a multi-centre TBI cohort. ⋯ The CPPopt calculation algorithm was fine-tuned and adapted for prospective use with acceptable lower yield, improved stability and maintained prognostic power.
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J Clin Monit Comput · Aug 2023
Multisensory alarm to benefit alarm identification and decrease workload: a feasibility study.
The poor design of conventional auditory medical alarms has contributed to alarm desensitization, and eventually, alarm fatigue in medical personnel. This study tested a novel multisensory alarm system which aims to help medical personnel better interpret and respond to alarm annunciation during periods of high cognitive load such as those found within intensive care units. We tested a multisensory alarm that combined auditory and vibrotactile cues to convey alarm type, alarm priority, and patient identity. ⋯ The Half multisensory phase produced the lowest mental demand, temporal demand, and overall perceived workload score. These data suggest that implementation of a multisensory alarm with alarm and patient information may decrease perceived workload without significant changes in alarm identification performance. Additionally, a ceiling effect may exist for multisensory stimuli, with only part of an alarm benefitting from multisensory integration.
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J Clin Monit Comput · Aug 2023
Tracheal sound-based apnea detection using hidden Markov model in sedated volunteers and post anesthesia care unit patients.
The current method of apnea detection based on tracheal sounds is limited in certain situations. In this work, the Hidden Markov Model (HMM) algorithm based on segmentation is used to classify the respiratory and non-respiratory states of tracheal sounds, to achieve the purpose of apnea detection. Three groups of tracheal sounds were used, including two groups of data collected in the laboratory and a group of patient data in the post anesthesia care unit (PACU). ⋯ For the laboratory test data, apnea detection sensitivity, specificity, and accuracy were 96.9%, 95.5%, and 95.7%, respectively. For the clinical test data, apnea detection sensitivity, specificity, and accuracy were 83.1%, 99.0% and 98.6%. Apnea detection based on tracheal sound using HMM is accurate and reliable for sedated volunteers and patients in PACU.
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J Clin Monit Comput · Aug 2023
Behaviour and stability of thermodilution signals in a closed extracorporeal circuit: a bench study.
Thermodilution is the gold standard for cardiac output measurement in critically ill patients. Its application in extracorporeal therapy is limited, as a portion of the thermal indicator is drawn into the extracorporeal circuit. The behaviour of thermodilution signals in extracorporeal circuits is unknown. ⋯ The distance to the injection port increased peak temperature and rise time and decreased exponential time constant significantly. The distance to the injection port did not influence catheter constants, but the properties of the thermodilution signal itself. This may influence measurements that depend on the exponential decay of the thermodilution signal such as right ventricular ejection fraction.