Journal of clinical monitoring and computing
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J Clin Monit Comput · Feb 2017
A systematic database-derived approach to improve indexation of transpulmonary thermodilution-derived global end-diastolic volume.
Global end-diastolic volume (GEDV) has been indexed to body surface area (BSA). However, data validating this indexation of GEDV are scarce. Furthermore, it has been suggested to index GEDV to "predicted BSA" based on predicted body weight. ⋯ GEDV was independently associated with older age, male sex, height, and actual body weight. In a regression model for the estimation of GEDV, age and height were the most important parameters: Each year in age and each cm in height increased GEDV by 9 and 15 mL, respectively. In addition to height and weight also age and sex should be considered for indexation of GEDV.
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J Clin Monit Comput · Feb 2017
ReviewUsing the features of the time and volumetric capnogram for classification and prediction.
Quantitative features derived from the time-based and volumetric capnogram such as respiratory rate, end-tidal PCO2, dead space, carbon dioxide production, and qualitative features such as the shape of capnogram are clinical metrics recognized as important for assessing respiratory function. Researchers are increasingly exploring these and other known physiologically relevant quantitative features, as well as new features derived from the time and volumetric capnogram or transformations of these waveforms, for: (a) real-time waveform classification/anomaly detection, (b) classification of a candidate capnogram into one of several disease classes, (c) estimation of the value of an inaccessible or invasively determined physiologic parameter, (d) prediction of the presence or absence of disease condition, (e) guiding the administration of therapy, and (f) prediction of the likely future morbidity or mortality of a patient with a presenting condition. The work to date with respect to these applications will be reviewed, the underlying algorithms and performance highlighted, and opportunities for the future noted.
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J Clin Monit Comput · Feb 2017
ReviewJournal of clinical monitoring and computing 2016 end of year summary: anesthesia.
Clinical monitoring and computing are essential during general anesthesia. As a result it would be impossible to review all the articles published in the Journal of Clinical Monitoring and Computing that are relevant to anesthesia. We therefore will limit this summary to those articles that are uniquely related to anesthesia. The topics include: anesthesia machines; ensuring the airway; anesthetic depth; neuromuscular transmission monitoring; locoregional anesthesia; ultrasound; and pain.
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J Clin Monit Comput · Feb 2017
Monitoring sleep depth: analysis of bispectral index (BIS) based on polysomnographic recordings and sleep deprivation.
The assessment and management of sleep are increasingly recommended in the clinical practice. Polysomnography (PSG) is considered the gold standard test to monitor sleep objectively, but some practical and technical constraints exist due to environmental and patient considerations. Bispectral index (BIS) monitoring is commonly used in clinical practice for guiding anesthetic administration and provides an index based on relationships between EEG components. ⋯ BIS scores were able to discriminate properly between deep (N3) and light (N1, N2) sleep. BIS values during REM overlapped those of other sleep stages, although EMG activity provided by the BIS monitor could help to identify REM sleep if needed. In conclusion, BIS monitors could provide a useful measure of sleep depth in especially particular situations such as intensive care units, and they could be used as an alternative for sleep monitoring in order to reduce PSG-derived costs and to increase capacity in ambulatory care.
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J Clin Monit Comput · Feb 2017
Reduction of clinically irrelevant alarms in patient monitoring by adaptive time delays.
The problem of high rates of false alarms in patient monitoring in anesthesiology and intensive care medicine is well known but remains unsolved. False alarms desensitize the medical staff, leading to ignored true alarms and reduced quality of patient care. A database of intra-operative monitoring data was analyzed to find characteristic alarm patterns. ⋯ The implementation of this algorithm may be able to suppress a large percentage of false alarms. The effect of this approach has not been demonstrated but shows promise for reducing alarm fatigue. Its safety needs to be proven in a prospective study.