Journal of clinical monitoring and computing
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J Clin Monit Comput · Jun 2024
A novel adaptive filter with a heart-rate-based reference signal for esophageal pressure signal denoising.
Esophageal pressure (Peso) is one of the most common and minimally invasive methods used to assess the respiratory and lung mechanics in patients receiving mechanical ventilation. However, the Peso measurement is contaminated by cardiogenic oscillations (CGOs), which cannot be easily eliminated in real-time. The field of study dealing with the elimination of CGO from Peso signals is still in the early stages of its development. ⋯ The CGO can be efficiently suppressed when the constructional reference signal contains the fundamental, and second and third harmonic frequencies of the heart rate signal. The analysis of the data of 8 patients with controlled mechanical ventilation reveals that the standard deviation/mean of the QUOTE is reduced by 28.4-79.2% without changing the QUOTE and the △Pes measurement is more accurate, with the use of our proposed technique. The proposed technique can effectively eliminate the CGOs from the measured Peso signals in real-time without requiring additional equipment to collect the reference signal.
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J Clin Monit Comput · Jun 2024
Comparative StudyCerebral oxygenation saturation in childhood: difference by age and comparison of two cerebral oximetry algorithms.
Few reports are available on the monitoring of regional cerebral oxygen saturation (rSO2) in pediatric patients undergoing non-cardiac surgical procedures. In addition, no study has examined the rSO2 levels in children of a broad age range. In this study, we aimed to assess and compare rSO2 levels in pediatric patients of different age groups undergoing non-cardiac surgery. ⋯ The values in INVOS 5100C and tNIRS-1 were affected by blood pressure and the minimum alveolar concentration of sevoflurane, respectively. In pediatric patients undergoing non-cardiac surgery, rSO2 values differed across the three age groups, and the pattern of these differences varied between the two oximeters employing different algorithms. Further research must be conducted to clarify cerebral oxygenation in children.
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J Clin Monit Comput · Jun 2024
Observational StudyUse of near infrared spectroscopy for the prediction of perioperative complications in patients undergoing elective microsurgical resection of cerebral arteriovenous malformations- a prospective observational trial (NIRSCAM trial).
Cerebral arteriovenous malformations (AVM) represent focal abnormal areas of low resistance circulation which render the peri-nidal neuronal tissue susceptible to ischemia. The post-excision cerebral perfusion surge can result in hyperaemic complications.We hypothesised that Near Infrared Spectroscopy (NIRS)-guided perioperative management can aid in the prediction and prevention of perioperative complications in patients presenting for surgical excision of cerebral AVMs. We also intended to identify a threshold value of regional cerebral oxygen saturation (rScO2) to predict the incidence of perioperative complications. ⋯ In patients undergoing cerebral AVM resection, a post-resection ipsilateral rScO2 increase by > 12% with a drift ratio of > 1.3 could signify cerebral hyperemia. A postoperative ipsilateral rScO2 drift > 14.5% with a drift ratio of 2.1 from the baseline is associated with postoperative complications in our study. Further multi-centric randomized control trials are needed to support our research findings.
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J Clin Monit Comput · Jun 2024
Quantitative electroencephalogram in term neonates under different sleep states.
Electroencephalogram (EEG) can be used to assess depth of consciousness, but interpreting EEG can be challenging, especially in neonates whose EEG undergo rapid changes during the perinatal course. EEG can be processed into quantitative EEG (QEEG), but limited data exist on the range of QEEG for normal term neonates during wakefulness and sleep, baseline information that would be useful to determine changes during sedation or anesthesia. We aimed to determine the range of QEEG in neonates during awake, active sleep and quiet sleep states, and identified the ones best at discriminating between the three states. ⋯ Entropy beta and SEF50 were best at discriminating between awake and sleep states. QEEG were not as good at discriminating between quiet and active sleep. In the future, QEEG with high discriminatory power can be combined to further improve ability to differentiate between states of consciousness.