Journal of clinical monitoring and computing
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J Clin Monit Comput · Oct 2024
Comparative Study Observational StudyAgreement between three noninvasive temperature monitoring devices during spinal anaesthesia for caesarean delivery: a prospective observational study.
Hypothermia during obstetric spinal anaesthesia is a common and important problem, yet temperature monitoring is often not performed due to the lack of a suitable, cost-effective monitor. This study aimed to compare a noninvasive core temperature monitor with two readily available peripheral temperature monitors during obstetric spinal anaesthesia. We undertook a prospective observational study including elective and emergency caesarean deliveries, to determine the agreement between affordable reusable surface temperature monitors (Welch Allyn SureTemp® Plus oral thermometer and the Braun 3-in-1 No Touch infrared thermometer) and the Dräger T-core© (using dual-sensor heat flux technology), in detecting thermoregulatory changes during obstetric spinal anaesthesia. ⋯ Error grid analysis highlighted a large amount of clinical disagreement between methods. While monitoring of core temperature during obstetric spinal anaesthesia is clinically important, agreement between monitors was below clinically acceptable limits. Future research with gold-standard temperature monitors and exploration of causes of sensor divergence is needed.
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J Clin Monit Comput · Oct 2024
Observational StudyMachine learning based analysis and detection of trend outliers for electromyographic neuromuscular monitoring.
Neuromuscular monitoring is frequently plagued by artefacts, which along with the frequent unawareness of the principles of this subtype of monitoring by many clinicians, tends to lead to a cynical attitute by clinicians towards these monitors. As such, the present study aims to derive a feature set and evaluate its discriminative performance for the purpose of Train-of-Four Ratio (TOF-R) outlier analysis during continuous intraoperative EMG-based neuromuscular monitoring. ⋯ Engineered TOF-R trend features and the resulting Cost-Sensitive Logistic Regression (CSLR) models provide useful insights and serve as a potential first step towards the automated removal of outliers for neuromuscular monitoring devices.
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J Clin Monit Comput · Oct 2024
Observational StudyCentral venous pressure waveform analysis during sleep/rest: a novel approach to enhance intensive care unit post-extubation monitoring of extubation failure.
This pilot study aimed to investigate the relation between cardio-respiratory parameters derived from Central Venous Pressure (CVP) waveform and Extubation Failure (EF) in mechanically ventilated ICU patients during post-extubation period. This study also proposes a new methodology for analysing these parameters during rest/sleep periods to try to improve the identification of EF. We conducted a prospective observational study, computing CVP-derived parameters including breathing effort, spectral analyses, and entropy in twenty critically ill patients post-extubation. ⋯ We also identified a possible improvement in the differentiation between the two groups of patients when assessed during rest/sleep states. Although with caveats regarding the sample size, the results of this pilot study may suggest that CVP-derived cardio-respiratory parameters are valuable for monitoring respiratory failure during post-extubation, which could aid in managing non-invasive interventions and possibly reduce the incidence of EF. Our findings also indicate the possible importance of considering sleep/rest state when assessing cardio-respiratory parameters, which could enhance respiratory failure detection/monitoring.
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J Clin Monit Comput · Oct 2024
Continuity with caveats in anesthesia: state and response entropy of the EEG.
The growing use of neuromonitoring in general anesthesia provides detailed insights into the effects of anesthetics on the brain. Our study focuses on the processed EEG indices State Entropy (SE), Response Entropy (RE), and Burst Suppression Ratio (BSR) of the GE EntropyTM Module, which serve as surrogate measures for estimating the level of anesthesia. While retrospectively analyzing SE and RE index values from patient records, we encountered a technical anomaly with a conspicuous distribution of index values. ⋯ This phenomenon occurs independently of the BSR distribution. SE and RE index values do not adhere to a continuous distribution, instead displaying prominent pillar indices with a consistent pattern of occurrence across all age groups. The specific features of the underlying algorithm responsible for this pattern remain elusive.
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J Clin Monit Comput · Oct 2024
Bayesian networks for Risk Assessment and postoperative deficit prediction in intraoperative neurophysiology for brain surgery.
To this day there is no consensus regarding evidence of usefulness of Intraoperative Neurophysiological Monitoring (IONM). Randomized controlled trials have not been performed in the past mainly because of difficulties in recruitment control subjects. In this study, we propose the use of Bayesian Networks to assess evidence in IONM. ⋯ Bayesian Networks are an effective way to audit clinical practice within IONM. We have found that IONM warnings can serve to prevent neurological deficits in patients, especially when corrective surgical action is taken to attempt to revert signals changes back to baseline properties. We show that Bayesian Networks could be used as a mathematical tool to calculate the utility of conducting IONM, which could save costs in healthcare when performed.