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
Randomized Controlled Trial Comparative StudyComparison of intraoperative volume and pressure-controlled ventilation modes in patients who undergo open heart surgery.
Respiratory problems occur more frequently in patients who undergo open heart surgery. Intraoperative and postoperative ventilation strategies can prevent these complications and reduce mortality. We hypothesized that PCV would have better effects on gas exchange, lung mechanics and hemodynamics compared to VCV in CABG surgery. ⋯ The hemodynamic effects of both ventilation modes were found to be similar. PVC may be preferable to VCV in patients who undergo open heart surgery. However, it would be convenient if our findings are supported by similar studies.
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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
Dynamic prediction of the need for renal replacement therapy in intensive care unit patients using a simple and robust model.
We aimed at identifying a model that dynamically predicts future need for renal replacement therapy (RRT) in intensive care unit (ICU) patients and can easily be implemented for online monitoring at the bedside. 7290 interdisciplinary ICU admissions were investigated. Patients with <3 days of stay or RRT in the first 2 days were excluded. 1624 of the remaining 2625 patients had a normal serum creatinine at admission. Every second of these 1624 patients was used for model calibration whereas the other half and, in addition, the 1001 patients with elevated serum creatinine were exclusively used for validation. ⋯ Moreover, the model's predictive value extended to at least 5 days prior to initiation of RRT and exceeded that of the RIFLE classification at all investigated prediction intervals. We identified a robust model that dynamically predicts the future need for RRT successfully. This tool may help improve timing of therapy and prognosis in ICU patients.