Journal of clinical monitoring and computing
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J Clin Monit Comput · Apr 2021
Observational StudyUltrasonography for predicting a difficult laryngoscopy. Getting closer.
Our objective was to evaluate the usefulness of five ultrasound measurements to predict a difficult laryngoscopy (DL). Prospective observational study. 50 patients underwent scheduled surgery under general anesthesia with orotracheal intubation with classical laryngoscopy at the University Hospital of Jaén (Spain). Sociodemographic variables, classic preintubation screening tests and ultrasound measurements of the neck soft tissue from skin to hyoid (DSH), epiglottis (DSE) and glottis (DSG) were obtained, as well as two measurements derived from the above: DSH + DSE and DSE - DSG. ⋯ It was established that DSE ≥ 3 cm, could predict a DL with a positive predictive value (PPV) of 69.23% [95%CI 40.3-98.2], and DSE - DSG ≥ 1.9 cm would do so with a PPV of 78.57% [95%CI 53.31-100%]. The multivariate analysis endorsed that DSE and DSE - DSG combined with classic tests (the Modified Mallampati score, the thyromental distance and the upper lip bite test) improved the preoperative detection of a DL. The inclusion of DSE and DSE - DSG in a multivariate model with classic parameters may offer the anesthesiologist better information for detecting a DL preoperatively.
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J Clin Monit Comput · Apr 2021
A physiology-based mathematical model for the selection of appropriate ventilator controls for lung and diaphragm protection.
Mechanical ventilation is used to sustain respiratory function in patients with acute respiratory failure. To aid clinicians in consistently selecting lung- and diaphragm-protective ventilation settings, a physiology-based decision support system is needed. To form the foundation of such a system, a comprehensive physiological model which captures the dynamics of ventilation has been developed. ⋯ Finally, the model is seen to be able to provide robust predictions of esophageal pressure, transpulmonary pressure and blood pH for patient parameters with realistic variability. The LDPV model is a robust physiological model which produces outputs which directly target and reflect the risk of ventilator-induced lung and diaphragm injury. Ventilation and sedation parameters are seen to modulate the model outputs in accordance with what is currently known in literature.
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J Clin Monit Comput · Apr 2021
Artifacts annotations in anesthesia blood pressure data by man and machine.
Physiologic data from anesthesia monitors are automatically captured. Yet erroneous data are stored in the process as well. While this is not interfering with clinical care, research can be affected. ⋯ Artifact detection in physiologic data collected during anesthesia could be automated, but the performance of the learning algorithms in the present study remained moderate. Future research should focus on optimization and finding ways to apply them with minimal manual work. The present study underlines the importance of an explicit definition for artifacts in database research.
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J Clin Monit Comput · Apr 2021
Continuous and entirely non-invasive method for cerebrovascular reactivity assessment: technique and implications.
Continuous cerebrovascular reactivity assessment in traumatic brain injury (TBI) has been limited by the need for invasive monitoring of either cerebral physiology or arterial blood pressure (ABP). This restricts the application of continuous measures to the acute phase of care, typically in the intensive care unit. It remains unknown if ongoing impairment of cerebrovascular reactivity occurs in the subacute and long-term phase, and if it drives ongoing morbidity in TBI. ⋯ Recent advances in continuous high-frequency non-invasive ABP measurement, combined with NIRS or rTCD, can be employed to derive continuous and entirely non-invasive cerebrovascular reactivity metrics. Such non-invasive measures can be obtained during any aspect of patient care post-TBI, and even during outpatient follow-up, avoiding classical intermittent techniques and costly neuroimaging based metrics obtained only at specialized centers. This combination of technology and signal analytic techniques creates avenues for future investigation of the long-term consequences of cerebrovascular reactivity, integrating high-frequency non-invasive cerebral physiology, neuroimaging, proteomics and clinical phenotype at various stages post-injury.