Journal of clinical monitoring and computing
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J Clin Monit Comput · Dec 2016
Capnodynamic assessment of effective lung volume during cardiac output manipulations in a porcine model.
A capnodynamic calculation of effective pulmonary blood flow includes a lung volume factor (ELV) that has to be estimated to solve the mathematical equation. In previous studies ELV correlated to reference methods for functional residual capacity (FRC). The aim was to evaluate the stability of ELV during significant manipulations of cardiac output (CO) and assess the agreement for absolute values and trending capacity during PEEP changes at different lung conditions. ⋯ ELV trending capability between PEEP steps, showed a concordance rate of 100 %. ELV was closely related to FRC and remained stable during significant changes in CO. The trending capability was excellent both before and after surfactant depletion.
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J Clin Monit Comput · Dec 2016
Adaptive online monitoring for ICU patients by combining just-in-time learning and principal component analysis.
Offline general-type models are widely used for patients' monitoring in intensive care units (ICUs), which are developed by using past collected datasets consisting of thousands of patients. However, these models may fail to adapt to the changing states of ICU patients. Thus, to be more robust and effective, the monitoring models should be adaptable to individual patients. ⋯ The proposed method was compared with the traditional PCA and fast moving-window PCA (Fast MWPCA). The experimental results demonstrated that the fault detection rates respectively increased by 20 % and 47 % compared with PCA and Fast MWPCA. L-PCA is first introduced into ICU patients monitoring and achieves the best monitoring performance in terms of adaptability to changes in patient status and sensitivity for abnormality detection.
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J Clin Monit Comput · Dec 2016
Case ReportsUltrasound-guided spinal anesthesia for cesarean section in a parturient with spinal metastases.
Preprocedural spinal ultrasound appears to decrease the failure rate and complications of neuraxial anesthesia compared to the conventional landmark technique. It is especially beneficial in difficult cases where conventional palpation technique may fail. ⋯ We used spinal ultrasound to define the appropriate intervertebral space and measure the distance to the ligamentum flavum-dura mater complex. This greatly helped in administering a safe spinal anesthetic and avoiding general anesthesia which might have been hazardous in this patient.
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J Clin Monit Comput · Dec 2016
Effect of using a Planecta™ port with a three-way stopcock on the natural frequency of blood pressure transducer kits.
Blood pressure transducer kits are equipped with two types of Planecta™ ports-the flat-type Planecta™ port (FTP) and the Planecta™ port with a three-way stopcock (PTS). We reported that FTP application decreased the natural frequency of the kits. However, Planecta™ is an invaluable tool as it prevents infection, ensures technical simplicity, and excludes air. ⋯ The insertion of ≥2 FTPs in pressure transducer kits should be avoided, as they markedly decrease the natural frequency and lead to underdamping. However, the effect of PTS insertion in pressure transducer kits on the frequency characteristics is minimal. Thus, we found that the use of PTS markedly improved the frequency characteristics as compared to the use of FTP.
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J Clin Monit Comput · Dec 2016
Sensor fusion methods for reducing false alarms in heart rate monitoring.
Automatic patient monitoring is an essential resource in hospitals for good health care management. While alarms caused by abnormal physiological conditions are important for the delivery of fast treatment, they can be also a source of unnecessary noise because of false alarms caused by electromagnetic interference or motion artifacts. One significant source of false alarms is related to heart rate, which is triggered when the heart rhythm of the patient is too fast or too slow. ⋯ Twenty recordings selected from the MIMIC database were used to validate the system. The results showed that neural networks fusion had the best false alarm reduction of 92.5 %, while the Bayesian technique had a reduction of 84.3 %, fuzzy logic 80.6 %, majority voter 72.5 % and the heart rate variability index 67.5 %. Therefore, the proposed algorithms showed good performance and could be useful in bedside monitors.