Journal of clinical monitoring and computing
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J Clin Monit Comput · Dec 2022
A model-based approach to generating annotated pressure support waveforms.
Large numbers of asynchronies during pressure support ventilation cause discomfort and higher work of breathing in the patient, and are associated with an increased mortality. There is a need for real-time decision support to detect asynchronies and assist the clinician towards lung-protective ventilation. Machine learning techniques have been proposed to detect asynchronies, but they require large datasets with sufficient data diversity, sample size, and quality for training purposes. ⋯ Experienced clinicians were not able to differentiate between the simulated waveforms and clinical data (P = 0.44 by Fisher's exact test). The detection performance of the machine learning trained on clinical data gave an overall comparable true positive rate on clinical data and on simulated data (an overall true positive rate of 94.3% and positive predictive value of 93.5% on simulated data and a true positive rate of 98% and positive predictive value of 98% on clinical data). Our findings demonstrate that it is possible to generate labeled pressure and flow waveforms with different types of asynchronies.
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J Clin Monit Comput · Dec 2022
Clinical TrialFeasibility of non-invasive neuromonitoring in general intensive care patients using a multi-parameter transcranial Doppler approach.
To assess the feasibility of Transcranial Doppler ultrasonography (TCD) neuromonitoring in a general intensive care environment, in the prognosis and outcome prediction of patients who are in coma due to a variety of critical conditions. ⋯ Preliminary results from the trial indicate that multi-parameter TCD neuromonitoring increases outcome-predictive power and TCD-based indices can be applied to general intensive care monitoring.
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J Clin Monit Comput · Dec 2022
Case ReportsRegional respiratory sound abnormalities in pneumothorax and pleural effusion detected via respiratory sound visualization and quantification: case report.
Assessment of respiratory sounds by auscultation with a conventional stethoscope is subjective. We developed a continuous monitoring and visualization system that enables objectively and quantitatively visualizing respiratory sounds. We herein present two cases in which the system showed regional differences in the respiratory sounds. ⋯ Chest X-rays showed a large amount of pleural effusion on the right side. The continuous monitoring and visualization system visually and quantitatively revealed a decreased respiratory volume in the lower right lung field compared with that in the lower left lung field. Our newly developed continuous monitoring and visualization system enabled quantitatively and visually detecting regional differences in respiratory sounds in patients with pneumothorax and pleural effusion.