Journal of clinical monitoring and computing
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J Clin Monit Comput · Oct 2022
High-flow nasal cannula therapy, factors affecting effective inspired oxygen fraction: an experimental adult bench model.
Oxygenation through High Flow Delivery Systems (HFO) is described as capable of delivering accurate FiO2. Meanwhile, peak inspiratory flow [Formula: see text] ) of patients with acute hypoxemic respiratory failure can reach up to 120 L/min, largely exceeding HFO flow. Currently, very few data on the reliability of HFO devices at these high [Formula: see text] are available. ⋯ The present bench study did expose a weakness of HFO devices in reliability of delivering accurate FIO2 at high [Formula: see text] as well as, to a lesser extent, at [Formula: see text] below equivalent set HFO Flows. Moreover, set HFO flow and set FIO2 did influence the variability of effective inspired oxygen fraction. The adjunction of a dead space in the experimental set-up significantly amended this variability and should thus be further studied in order to improve success rate of HFO therapy.
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J Clin Monit Comput · Oct 2022
A capaciflector provides continuous and accurate respiratory rate monitoring for patients at rest and during exercise.
Respiratory rate (RR) is a marker of critical illness, but during hospital care, RR is often inaccurately measured. The capaciflector is a novel sensor that is small, inexpensive, and flexible, thus it has the potential to provide a single-use, real-time RR monitoring device. We evaluated the accuracy of continuous RR measurements by capaciflector hardware both at rest and during exercise. ⋯ Accuracy and continuity of monitoring were upheld even during vigorous CPET exercise, often with narrower limits of agreement than those reported for comparable technologies. We provide a unique clinical demonstration of the capaciflector as an accurate breathing monitor, which may have the potential to become a simple and affordable medical device. Clinical trial number: NCT03832205 https://clinicaltrials.gov/ct2/show/NCT03832205 registered February 6th, 2019.
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The current grading of facial nerve function is based on subjective impression with the established assessment scale of House and Brackmann (HB). Especially for research a more objective method is needed to lower the interobserver variability to a minimum. We developed a semi-automated grading system based on (facial) surface EMG-data measuring the facial nerve function of 28 patients with vestibular schwannoma surgery. ⋯ Lateralization indices were calculated and multivariant machine learning analysis was performed according to three scenarios [differentiation of normal (1) and slight (2) vs. impaired facial nerve function and classification of HB 1-3 (3)]. The calculated AUC for each scenario showed overall good differentiation capability with a median AUC of 0.72 for scenario 1, 0.91 for scenario 2 and multiclass AUC of 0.74 for scenario 3. This study approach using sEMG and machine learning shows feasibility regarding facial nerve grading in perioperative VS-surgery setting. sEMG may be a viable alternative to House Brackmann regarding objective evaluation of facial function especially for research purposes.
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J Clin Monit Comput · Oct 2022
EditorialSample size determination in method comparison and observer variability studies.
The comparison of two quantitative measuring devices is often performed with the Limits of Agreement proposed by Bland and Altman in their seminal Lancet paper back in 1986. Sample size considerations were rare for such agreement analyses in the past, but recently several proposals have been made depending on how agreement is to be assessed and the number of replicates to be used. ⋯ These include current state-of-the-art analysis of and reporting guidelines for agreement studies. General recommendations close the paper.
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J Clin Monit Comput · Oct 2022
Accuracy of pulse pressure variations for fluid responsiveness prediction in mechanically ventilated patients with biphasic positive airway pressure mode.
The accuracy of pulse pressure variation (PPV) to predict fluid responsiveness using pressure-controlled (PC) instead of volume-controlled modes is under debate. To specifically address this issue, we designed a study to evaluate the accuracy of PPV to predict fluid responsiveness in severe septic patients who were mechanically ventilated with biphasic positive airway pressure (BIPAP) PC-ventilation mode. 45 patients with sepsis or septic shock and who were mechanically ventilated with BIPAP mode and a target tidal volume of 7-8 ml/kg were included. PPV was automatically assessed at baseline and after a standard fluid challenge (Ringer's lactate 500 ml). ⋯ Using a gray zone approach, we identified that PPV values comprised between 5 and 15% do not allow a reliable fluid responsiveness prediction. In critically ill septic patients ventilated under BIPAP mode, PPV appears to be an accurate method for fluid responsiveness prediction. However, PPV values comprised between 5 and 15% constitute a gray zone that does not allow a reliable fluid responsiveness prediction.