Journal of clinical monitoring and computing
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J Clin Monit Comput · Jun 2022
Observational StudyUltrasonic cardiac output monitor provides effective non-invasive bedside measurements of neonatal cardiac output.
This study determined the accuracy and validity for the haemodynamic parameters of haemodynamically stable neonates after postnatal circulatory adaptation using the ultrasonic cardiac output monitor (USCOM) in comparison with echocardiography. We conducted a prospective, observational study of neonates born at 23-41 weeks of gestation. They all underwent both echocardiography and USCOM assessments for comparison purposes. ⋯ A larger bias was observed in cases with higher left ventricular output. Bland-Altman analysis confirmed no significant bias, with acceptable limits of agreement between these two methods. There was a very good correlation between the USCOM and echocardiographic methods when we used them to measure cardiac output in neonates.
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J Clin Monit Comput · Jun 2022
Observational StudyAssociation of transcutaneous CO2 with respiratory support: a prospective double blind observational study in children with bronchiolitis and reactive airway disease.
The use of clinical scoring to assess for severity of respiratory distress and respiratory failure is challenging due to subjectivity and interrater variability. Transcutaneous Capnography (TcpCO2) can be used as an objective tool to assess a patient's ventilatory status. This study was designed to assess for any correlation of continuous monitoring of TcpCO2 with the respiratory clinical scores and deterioration in children admitted for acute respiratory distress. ⋯ No difference was found in bronchiolitis score or PEW score in subjects with normal and abnormal TcpCO2. A small but statistically significant increase in TcpCO2 was observed at the escalation of care. Even though odds of escalation of care are higher with abnormal TcpCO2 (OR 1.92), this difference did not reach statistical significance. pCO2 can provide additive information for non-invasive clinical monitoring of children requiring varying respiratory support; however, it does not provide predictive value for escalation or de-escalation of care.
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The BIS and Entropy systems are used as indicators of anaesthetic drug effect, and can also record EEGs in digital form. A number of studies have used such recordings for analysis, even though information about bandwidth and fidelity has not been provided by the manufacturers. In this study we consider these systems purely as EEG recording devices, and evaluate their suitability for quantitative analysis. ⋯ The Entropy 100 Hz recording in the Datex-Ohmeda S/5 monitor has a flawed implementation, leading to aliasing of signals over 50 Hz and potential distortion of the recording, while in the GE Carescape it has an uneven response and a narrowed bandwidth. Consequently, it is important to know which specific host monitor was used when an Entropy 100 Hz recording was made. In summary, the choice of recording device and host monitor may affect the results of some quantitative EEG analysis, and some previously published studies may need to be re-evaluated.
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J Clin Monit Comput · Jun 2022
Intraoperative impaired cerebrovascular autoregulation and delayed neurocognitive recovery after major oncologic surgery: a secondary analysis of pooled data.
Cerebral blood flow is tightly regulated by cerebrovascular autoregulation (CVA), and intraoperative impairment of CVA has been linked with perioperative neurocognitive disorders. We aim to assess whether impairment of CVA during major oncologic surgery is associated with delayed neurocognitive recovery (DNCR) postoperatively. We performed a secondary analysis of prospectively collected data. ⋯ Intraoperative impairment of CVA is associated with postoperative neurocognitive function early after oncologic surgery. Therefore, intraoperative monitoring of CVA may be a target for neuroprotective interventions. The initial studies were retrospectively registered with primary clinical trial registries recognized by the World Health Organization (ClinicalTrials.gov Identifiers: DRKS00010014, 21.03.2016 and NCT04101006, 24.07.2019).
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J Clin Monit Comput · Jun 2022
Machine learning applied to a Cardiac Surgery Recovery Unit and to a Coronary Care Unit for mortality prediction.
Most established severity-of-illness systems used for prediction of intensive care unit (ICU) mortality were developed targeted at the general ICU population, based on logistic regression (LR). To date, no dynamic predictive tool for ICU mortality has been developed targeted at the Cardiac Surgery Recovery Unit (CSRU) and Coronary Care Unit (CCU) using machine learning (ML). CSRU and CCU adult patients from the MIMIC-III critical care database were studied. ⋯ The accuracy statistics less sensitive to unbalanced cohorts were higher for all the ML models. In conclusion, the predictive power of XGB was excellent, substantially outperforming the conventional systems and LR. The ML models developed in this work offer promising results that could benefit CSRU and CCU.