Critical care : the official journal of the Critical Care Forum
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Intensive care unit (ICU) patients are known to experience severely disturbed sleep, with possible detrimental effects on short- and long- term outcomes. Investigation into the exact causes and effects of disturbed sleep has been hampered by cumbersome and time consuming methods of measuring and staging sleep. We introduce a novel method for ICU depth of sleep analysis, the ICU depth of sleep index (IDOS index), using single channel electroencephalography (EEG) and apply it to outpatient recordings. A proof of concept is shown in non-sedated ICU patients. ⋯ Besides the most satisfying visual resemblance with manually scored normal PSG recordings, the established face-validity of the IDOS index as an estimator of depth of sleep was excellent. This technique enables real-time, automated, single channel visualization of depth of sleep, facilitating the monitoring of sleep in the ICU.
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Observational Study
Prediction of mortality in adult patients with severe acute lung failure receiving veno-venous extracorporeal membrane oxygenation: a prospective observational study.
Veno-venous extracorporeal membrane oxygenation (vvECMO) can be a life-saving therapy in patients with severe acute lung failure refractory to conventional therapy. Nevertheless, vvECMO is a procedure associated with high costs and resource utilization. The aim of this study was to assess published models for prediction of mortality following vvECMO and optimize an alternative model. ⋯ While pre-ECMO mortality prediction remains a challenge due to large patient heterogeneity, evaluation one day after ECMO initiation may improve the ability to separate lower- and higher-risk patients. Our findings support the clinical perception that chronic health condition, high comorbidity and reduced functional reserves are strongly related to survival during and following ECMO support. Renewed evaluation the first day after ECMO initiation may provide enhanced guidance for further handling of ECMO patients. Despite the usefulness of prediction models, thorough clinical evaluation should always represent the cornerstone in decision for ECMO.
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Risk factor analyses for nosocomial infections (NIs) are complex. First, due to competing events for NI, the association between risk factors of NI as measured using hazard rates may not coincide with the association using cumulative probability (risk). Second, patients from the same intensive care unit (ICU) who share the same environmental exposure are likely to be more similar with regard to risk factors predisposing to a NI than patients from different ICUs. We aimed to develop an analytical approach to account for both features and to use it to evaluate associations between patient- and ICU-level characteristics with both rates of NI and competing risks and with the cumulative probability of infection. ⋯ A combination of competing risks and multilevel models is required to understand direct and indirect risk factors for NI and distinguish patient-level from ICU-level factors.