Journal of clinical monitoring and computing
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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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J Clin Monit Comput · Jun 2022
Bayesian hierarchical modeling of operating room times for surgeries with few or no historic data.
In this work it is proposed a modeling for operating room times based on a Bayesian Hierarchical structure. Specifically, it is employed a Bayesian generalized linear mixed model with an additional hierarchical level on the random effects. This configuration allows the estimation of operating room times (ORT) with few or no historical observations, without requiring a prior surgeon's estimate. ⋯ We find that lognormal models outperform the gamma models in estimating upper prediction bounds (UB). Especially, the best ORT predictions for cases with few or no historical data (i.e., between 0 and 3 historical cases) are obtained with the [Formula: see text], SBeta2 model. With a deviation of less than 1% with respect to the nominal coverage of the upper bound predictions UB80% and UB90% and an average absolute percentage error of 38.5% in the point estimate.
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J Clin Monit Comput · Jun 2022
Predicting the mortality risk of acute respiratory distress syndrome: radial basis function artificial neural network model versus logistic regression model.
To predict the mortality of acute respiratory distress syndrome (ARDS) by using a radial basis function (RBF) artificial neural network (ANN) model. This study included 217 patients who were admitted between June 2013 and November 2019. The RBF ANN model and logistic regression (LR) model were based on twelve factors related to ARDS. ⋯ LDH, organ failure, SP-D and PaO2/FiO2 were the most important independent variables. The RBF ANN model was more likely to predict the mortality of ARDS than the LR model. In addition, it can extract informative risk factors for ARDS.
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J Clin Monit Comput · Jun 2022
Fire safety study on high-flow nasal oxygen in shared-airway surgeries with diathermy and laser: simulation based on a physical model.
High-flow nasal oxygen (HFNO) has been used in "tubeless" shared-airway surgeries but whether HFNO increased the fire hazard is yet to be examined. We used a physical model for simulation to explore fire safety through a series of ignition trials. An HFNO device was attached to a 3D-printed nose with nostrils connected to a degutted raw chicken. ⋯ The factors found to be related to a significantly increased chance of ignition included laser application, lower gas flow, and higher FiO2. The native tissue and smoke can ignite and turn into violent self-sustained fires under HFNO and continuous laser strikes, even in the absence of combustible materials. The results suggest that airway surgeries must be performed safely with HFNO if only a short intermittent laser is used in low FiO2.
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J Clin Monit Comput · Jun 2022
Development of an automated closed-loop β-blocker delivery system to stably reduce myocardial oxygen consumption without inducing circulatory collapse in a canine heart failure model: a proof of concept study.
Beta-blockers are well known to reduce myocardial oxygen consumption (MVO2) and improve the prognosis of heart failure (HF) patients. However, its negative chronotropic and inotropic effects limit their use in the acute phase of HF due to the risk of circulatory collapse. In this study, as a first step for a safe β-blocker administration strategy, we aimed to develop and evaluate the feasibility of an automated β-blocker administration system. ⋯ We demonstrated the feasibility of an automated β-blocker administration system in a canine model of acute HF. The system controlled AP and PLA to avoid circulatory collapse, and reduced MVO2 significantly. As the system can help the management of patients with HF, further validations in larger samples and development for clinical applications are warranted.