Journal of clinical monitoring and computing
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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.
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J Clin Monit Comput · Jun 2022
ReviewDescription of the validity of the Analgesia Nociception Index (ANI) and Nociception Level Index (NOL) for nociception assessment in anesthetized patients undergoing surgery: a systematized review.
Maintaining optimum analgesia in anesthetized patients is challenging due to the inability to self-report pain or exhibit pain-related behaviours. The Analgesia Nociception Index (ANI) (based on heart rate variability [HRV]) and the Nociception Level Index (NOL) (based on HRV, photoplethysmography, skin conductance, and temperature) both include HRV and provide continuous index monitoring for nociception assessment. The research question was: "What are the validation strategies of the NOL and ANI for nociception assessment in anesthetized patients?". ⋯ Both technologies performed superiorly in detecting nociceptive stimuli compared to individual monitoring of HR and blood pressure. Although the aforementioned validation strategies are deemed appropriate, in the absence of a gold standard, criterion validation findings should be interpreted with caution. Moreover, reliability could be examined using test-retest with consistent ANI/NOL values during a stable time-interval.
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J Clin Monit Comput · Jun 2022
Volatile anesthetic gas concentration sensing using flow sensor fusion for use in Austere settings.
Flow sensors are often sensitive to the presence of volatile anesthetics. However, this sensitivity provides a unique opportunity to combine flow sensors of differing technological principles as an alternative to measuring volatile anesthetic gas concentration, particularly for austere settings. To determine the feasibility of flow sensor fusion for volatile anesthetic concentrations monitoring, eight flow sensors were tested with isoflurane, sevoflurane, and desflurane, ranging in concentrations from 0-4.5%, 0-3.5%, and 0-18%, respectively. ⋯ Conclusion: Measuring volatile anesthetic gases using flow sensor fusion is a feasible low-cost, low-maintenance alternative to infrared spectroscopy. In this study, testing was done under steady-state conditions in 100% oxygen. Further testing is necessary to ensure sensor fusion performance under conditions that are more reflective of the clinical use case.
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J Clin Monit Comput · Jun 2022
The effect of COVID-19 epidemic on vital signs in hospitalized patients: a pre-post heat-map study from a large teaching hospital.
The Lombardy SARS-CoV-2 outbreak in February 2020 represented the beginning of COVID-19 epidemic in Italy. Hospitals were flooded by thousands of patients with bilateral pneumonia and severe respiratory, and vital sign derangements compared to the standard hospital population. We propose a new visual analysis technique using heat maps to describe the impact of COVID-19 epidemic on vital sign anomalies in hospitalized patients. ⋯ COVID-19 epidemic profoundly affected the incidence of severe derangements in vital signs in a large academic hospital. We validated heat maps as a method to analyze the clinical stability of hospitalized patients. This method may help to improve resource allocation according to patient characteristics.