Journal of clinical monitoring and computing
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J Clin Monit Comput · Aug 2024
ReviewNon-invasive technology for brain monitoring: definition and meaning of the principal parameters for the International PRactice On TEChnology neuro-moniToring group (I-PROTECT).
Technologies for monitoring organ function are rapidly advancing, aiding physicians in the care of patients in both operating rooms (ORs) and intensive care units (ICUs). Some of these emerging, minimally or non-invasive technologies focus on monitoring brain function and ensuring the integrity of its physiology. Generally, the central nervous system is the least monitored system compared to others, such as the respiratory, cardiovascular, and renal systems, even though it is a primary target in most therapeutic strategies. ⋯ The clinical utility of the key parameters available in each of these tools is summarized and explained. This comprehensive review was conducted by a panel of experts who deliberated on the included topics until a consensus was reached. Images and tables are utilized to clarify and enhance the understanding of the clinical significance of non-invasive neuromonitoring devices within these medical settings.
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J Clin Monit Comput · Aug 2024
Perfusion tomography in early follow-up of acute traumatic subdural hematoma: a case series.
Perfusion Computed Tomography (PCT) is an alternative tool to assess cerebral hemodynamics during trauma. As acute traumatic subdural hematomas (ASH) is a severe primary injury associated with poor outcomes, the aim of this study was to evaluate the cerebral hemodynamics in this context. Five adult patients with moderate and severe traumatic brain injury (TBI) and ASH were included. ⋯ One patient died with the highest preoperative MTT (9.97 s) and CBV (4.51 ml/100 g). CBF seems to increase after surgery, especially when evaluated together with the MTT values. It is suggested that the improvement in postoperative brain hemodynamics correlates to favorable outcome.
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J Clin Monit Comput · Aug 2024
EditorialTowards the automatic detection and correction of abnormal arterial pressure waveforms.
Both over and underdamping of the arterial pressure waveform are frequent during continuous invasive radial pressure monitoring. They may influence systolic blood pressure measurements and the accuracy of cardiac output monitoring with pulse wave analysis techniques. ⋯ In case of overdamping, air bubbles, kinking, and partial obstruction of the arterial catheter should be suspected and eliminated. In the case of underdamping, resonance filters may be necessary to normalize the arterial pressure waveform and ensure accurate hemodynamic measurements.
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J Clin Monit Comput · Aug 2024
Optimal bispectral index exists in healthy patients undergoing general anesthesia: A validation study.
Continuous cerebrovascular reactivity monitoring in both neurocritical and intra-operative care has gained extensive interest in recent years, as it has documented associations with long-term outcomes (in neurocritical care populations) and cognitive outcomes (in operative cohorts). This has sparked further interest into the exploration and evaluation of methods to achieve an optimal cerebrovascular reactivity measure, where the individual patient is exposed to the lowest insult burden of impaired cerebrovascular reactivity. Recent literature has documented, in neural injury populations, the presence of a potential optimal sedation level in neurocritical care, based on the relationship between cerebrovascular reactivity and quantitative depth of sedation (using bispectral index (BIS)) - termed BISopt. The presence of this measure outside of neural injury patients has yet to be proven. ⋯ Findings here carry implications for the adaptation of the individualized physiologic BISopt concept to non-neural injury populations, both within critical care and the operative theater. However, this work is currently exploratory, and future work is required.
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J Clin Monit Comput · Aug 2024
LetterAlgor-ethics: charting the ethical path for AI in critical care.
The integration of Clinical Decision Support Systems (CDSS) based on artificial intelligence (AI) in healthcare is groundbreaking evolution with enormous potential, but its development and ethical implementation, presents unique challenges, particularly in critical care, where physicians often deal with life-threating conditions requiring rapid actions and patients unable to participate in the decisional process. Moreover, development of AI-based CDSS is complex and should address different sources of bias, including data acquisition, health disparities, domain shifts during clinical use, and cognitive biases in decision-making. In this scenario algor-ethics is mandatory and emphasizes the integration of 'Human-in-the-Loop' and 'Algorithmic Stewardship' principles, and the benefits of advanced data engineering. The establishment of Clinical AI Departments (CAID) is necessary to lead AI innovation in healthcare, ensuring ethical integrity and human-centered development in this rapidly evolving field.