Journal of clinical monitoring and computing
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J Clin Monit Comput · Jun 2022
Observational StudyIs lung ultrasound score a useful tool to monitoring and handling moderate and severe COVID-19 patients in the general ward? An observational pilot study.
Lung ultrasound is a well-established diagnostic tool in acute respiratory failure, and it has been shown to be particularly suited for the management of COVID-19-associated respiratory failure. We present exploratory analyses on the diagnostic and prognostic performance of lung ultrasound score (LUS) in general ward patients with moderate-to-severe COVID-19 pneumonia receiving O2 supplementation and/or noninvasive ventilation. From March 10 through May 1, 2020, 103 lung ultrasound exams were performed by our Forward Intensive Care Team (FICT) on 26 patients (18 males and 8 females), aged 62 (54 - 76) and with a Body Mass Index (BMI) of 30.9 (28.7 - 31.5), a median 6 (5 - 9) days after admission to the COVID-19 medical unit of the University Hospital of Parma, Italy. ⋯ The initial LUS was 16 (11 - 21), which did not significantly correlate with initial CT scans, probably due to rapid progression of the disease and time between CT scan on admission and first FICT evaluation; conversely, LUS was significantly correlated with PaO2/FiO2 ratio throughout patient follow-up [R = - 4.82 (- 6.84 to - 2.80; p < 0.001)]. The area under the receiving operating characteristics curve of LUS for the diagnosis of moderate-severe disease (PaO2/FiO2 ratio ≤ 200 mmHg) was 0.73, with an optimal cutoff value of 11 (positive predictive value: 0.98; negative predictive value: 0.29). Patients who eventually needed invasive ventilation and/or died during admission had significantly higher LUS throughout their stay.
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J Clin Monit Comput · Jun 2022
Accuracy of noncontact surface imaging for tidal volume and respiratory rate measurements in the ICU.
Tidal volume monitoring may help minimize lung injury during respiratory assistance. Surface imaging using time-of-flight camera is a new, non-invasive, non-contact, radiation-free, and easy-to-use technique that enables tidal volume and respiratory rate measurements. The objectives of the study were to determine the accuracy of Time-of-Flight volume (VTTOF) and respiratory rate (RRTOF) measurements at the bedside, and to validate its application for spontaneously breathing patients under high flow nasal canula. ⋯ Tidal volume monitoring using time-of-flight camera (VTTOF) is correlated to reference values. Time-of-flight camera enables continuous and non-contact respiratory monitoring under high-flow nasal canula, and enables to detect tidal volume and respiratory rate changes, while modifying flow. It enables respiratory monitoring for spontaneously patients, especially while using high-flow nasal oxygenation.
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J Clin Monit Comput · Jun 2022
Machine learning applied to a Cardiac Surgery Recovery Unit and to a Coronary Care Unit for mortality prediction.
Most established severity-of-illness systems used for prediction of intensive care unit (ICU) mortality were developed targeted at the general ICU population, based on logistic regression (LR). To date, no dynamic predictive tool for ICU mortality has been developed targeted at the Cardiac Surgery Recovery Unit (CSRU) and Coronary Care Unit (CCU) using machine learning (ML). CSRU and CCU adult patients from the MIMIC-III critical care database were studied. ⋯ The accuracy statistics less sensitive to unbalanced cohorts were higher for all the ML models. In conclusion, the predictive power of XGB was excellent, substantially outperforming the conventional systems and LR. The ML models developed in this work offer promising results that could benefit CSRU and CCU.
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J Clin Monit Comput · Jun 2022
ReviewPower spectrum and spectrogram of EEG analysis during general anesthesia: Python-based computer programming analysis.
The commonly used principle for measuring the depth of anesthesia involves changes in the frequency components of the electroencephalogram (EEG) under general anesthesia. Therefore, it is essential to construct an effective spectrum and spectrogram to analyze the relationship between the depth of anesthesia and the EEG frequency during general anesthesia. This paper reviews the computer programming techniques for analyzing the spectrum and spectrogram derived from a single-channel EEG recorded during general anesthesia. ⋯ Finally, the multitaper method, which can suppress artifacts caused by the edges of the analysis segments, suppress noise, and probabilistically infer values that are close to the real power spectral density, is explained using practical examples of the analysis. All analyses were performed and all graphs plotted using Python under Jupyter Notebook. The analyses demonstrated the effectiveness of Python-based programming under the integrated development environment Jupyter Notebook for constructing an effective spectrum and spectrogram for analyzing the relationship between the depth of anesthesia and EEG frequency analysis in general anesthesia.
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J Clin Monit Comput · Jun 2022
Bioreactance and fourth-generation pulse contour methods in monitoring cardiac index during off-pump coronary artery bypass surgery.
The pulmonary artery catheter (PAC) is considered the gold standard for cardiac index monitoring. Recently new and less invasive methods to assess cardiac performance have been developed. The aim of our study was to assess the reliability of a non-invasive monitor utilizing bioreactance (Starling SV) and a non-calibrated mini-invasive pulse contour device (FloTrac/EV1000, fourth-generation software) compared to bolus thermodilution technique with PAC (TDCO) during off-pump coronary artery bypass surgery (OPCAB). ⋯ In comparison with TDCO, FloTrac was associated with a bias of 0.01 L min-1 m-2 (95% CI - 0.05 to 0.06), wide LOA (- 1.27 to 1.29 L min-1 m-2), a PE of 56.8% and poor trending ability. Both Starling SV and fourth-generation FloTrac showed acceptable mean bias but imprecision due to wide LOA and high PE, and poor trending ability. These findings indicate limited reliability in monitoring cardiac index in patients undergoing OPCAB.