Journal of clinical monitoring and computing
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J Clin Monit Comput · Aug 2019
Randomized Controlled Trial Comparative StudyPropofol versus sevoflurane anaesthesia: effect on cognitive decline and event-related potentials.
Postoperative cognitive dysfunction (POCD) is diagnosed in up to 30% patients after anaesthesia. The causative role of anaesthetic toxicity remains unclear. Using clinical tests, no clear-cut differences have been observed between anaesthetics so far. ⋯ In our study, sevoflurane and propofol anaesthesia was associated with the similar incidence of POCD. Cognitive decline, mainly affecting executive functions, was temporary in most of the patients. Prolonged ERPs alterations after the anaesthesia seem not to have any relationship with the impairment registered by the neuropsychological examination and may represent subclinical changes.
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J Clin Monit Comput · Aug 2019
Impact of predictive analytics based on continuous cardiorespiratory monitoring in a surgical and trauma intensive care unit.
Predictive analytics monitoring, the use of patient data to provide continuous risk estimation of deterioration, is a promising new application of big data analytical techniques to the care of individual patients. We tested the hypothesis that continuous display of novel electronic risk visualization of respiratory and cardiovascular events would impact intensive care unit (ICU) patient outcomes. In an adult tertiary care surgical trauma ICU, we displayed risk estimation visualizations on a large monitor, but in the medical ICU in the same institution we did not. ⋯ Following implementation, the incidence of septic shock fell by half (p < 0.01 in a multivariate model that included age and APACHE) in the surgical trauma ICU, where the data were continuously on display, but by only 10% (p = NS) in the control Medical ICU. There were no significant changes in the other outcomes. Display of a predictive analytics monitor based on continuous cardiorespiratory monitoring was followed by a reduction in the rate of septic shock, even when controlling for age and APACHE score.
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J Clin Monit Comput · Aug 2019
Machine learning based framework to predict cardiac arrests in a paediatric intensive care unit : Prediction of cardiac arrests.
A cardiac arrest is a life-threatening event, often fatal. Whilst clinicians classify some of the cardiac arrests as potentially predictable, the majority are difficult to identify even in a post-incident analysis. Changes in some patients' physiology when analysed in detail can however be predictive of acute deterioration leading to cardiac or respiratory arrests. ⋯ A positive predictive value of 11% and negative predictive value of 98% was obtained with a prevalence of 5% by our method of prediction. While clinicians predicted 4 out of the 69 cardiac arrests (6%), the prediction system predicted 63 (91%) cardiac arrests. Prospective validation of the automated system remains.
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J Clin Monit Comput · Aug 2019
Selection of cuffed endotracheal tube for children with congenital heart disease based on an ultrasound-based linear regression formula.
It remains to be discovered whether a formula predicting the subglottic transverse diameter measured by ultrasound (SGDformula) for the selection of an appropriate endotracheal tube (ETT) for children without congenital heart disease (CHD) is useful for children with CHD. A formula for predicting SGD was established after assessing 60 children ≤ 8 years without CHD and validated on 60 children with CHD. We selected the cuffed ETT size based on the SGD by ultrasound (SGDultra). ⋯ And the mean bias (SGDformula-ETT size and SGDultra-ETT size) was 0.21 mm (95% confidence interval, - 0.59 to 1.01 mm) and 0.00 mm (- 0.79 to 0.84 mm). For the CHD group, the ultrasound-based method yielded a 78% success rate of ETT size choice, while the formula-based method permitted an appropriate ETT size in only 32% of subjects (P < 0.001). Our analysis showed that measuring the SGDultra was more accurate in predicting the correct OD of the ETT in children with CHD undergoing cardiovascular surgery, based on the correlation and agreement with ETT OD.
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J Clin Monit Comput · Aug 2019
Comparative Study Observational StudyA comparison of propofol-to-BIS post-operative intensive care sedation by means of target controlled infusion, Bayesian-based and predictive control methods: an observational, open-label pilot study.
We evaluated the feasibility and robustness of three methods for propofol-to-bispectral index (BIS) post-operative intensive care sedation, a manually-adapted target controlled infusion protocol (HUMAN), a computer-controlled predictive control strategy (EPSAC) and a computer-controlled Bayesian rule-based optimized control strategy (BAYES). ⋯ Both computer-based control systems are feasible to be used during ICU sedation with overall tighter control than HUMAN and even with lower required CePROP. EPSAC control required higher CeREMI than BAYES or HUMAN to maintain stable control. Clinical trial number: NCT00735631.