Journal of clinical monitoring and computing
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J Clin Monit Comput · Oct 2022
Multicenter StudyPredicting hypoglycemia in critically Ill patients using machine learning and electronic health records.
Hypoglycemia is a common occurrence in critically ill patients and is associated with significant mortality and morbidity. We developed a machine learning model to predict hypoglycemia by using a multicenter intensive care unit (ICU) electronic health record dataset. Machine learning algorithms were trained and tested on patient data from the publicly available eICU Collaborative Research Database. ⋯ The best-performing predictive model was the eXtreme gradient boosting model (XGBoost), which achieved an area under the received operating curve (AUROC) of 0.85, a sensitivity of 0.76, and a specificity of 0.76. The machine learning model developed has strong discrimination and calibration for the prediction of hypoglycemia in ICU patients. Prospective trials of these models are required to evaluate their clinical utility in averting hypoglycemia within critically ill patient populations.
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J Clin Monit Comput · Oct 2022
Clinical TrialEfficacy of sonorheometry point of the care device in determining low fibrinogen levels in pregnant blood: an invitro dilution and reconstitution study.
Quantra® Hemostasis Analyzer is a Point of the care device that uses ultrasound technology to assess clot formation. In this study, we establish how Quantra® system performs compared to conventional coagulation tests at low levels of fibrinogen in the blood obtained from pregnant women. 24 mL blood was obtained from each healthy parturient. Blood was analyzed for Quantra® variables (Q): Clot time (CT), Clot stiffness (CS), platelet contribution to CS (PCS), fibrinogen contribution to CS (FCS), and conventional coagulation (CL) tests: PT, aPTT, INR, Factor VIII and fibrinogen. 6 ml blood were centrifuged to obtain pregnant plasma. 30 mL of saline was added to 10 mL of blood to simulate crystalloid resuscitation (DB) and was evaluated for Q and CL. ⋯ An FCS value 2.45 (sensitivity of 79.2 and specificity of 97.3%), and CS value 10.85 hPa (sensitivity of 83% and specificity of 100%) predicted fibrinogen of 200 mg/dL. This study demonstrates a good correlation between Quantra® CS, FCS and serum fibrinogen. Clinical Trial Number: NCT04301193.
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J Clin Monit Comput · Oct 2022
Observational StudyComparison of zero heat flux and double sensor thermometers during spinal anaesthesia: a prospective observational study.
Because of the difficulties involved in the invasive monitoring of conscious patients, core temperature monitoring is frequently neglected during neuraxial anaesthesia. Zero heat flux (ZHF) and double sensor (DS) are non-invasive methods that measure core temperature from the forehead skin. Here, we compare these methods in patients under spinal anaesthesia. ⋯ DS temperatures were mostly lower than ZHF temperatures. The mean difference between ZHF and DS temperatures increased when the core temperature decreased. Trial registration: The study was registered in ClinicalTrials.gov on 13th May 2019, Code NCT03408197.
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J Clin Monit Comput · Oct 2022
Mathematically arterialised venous blood is a stable representation of patient acid-base status at steady state following acute transient changes in ventilation.
Hyper- or hypoventilation are commonly occurring stress responses to arterial puncture around the time of blood sampling and have been shown to rapidly alter arterial blood acid-base parameters. This study aimed to evaluate a physiology-based mathematical method to transform peripheral venous blood acid-base values into mathematically arterialised equivalents following acute, transient changes in ventilation. Data from thirty patients scheduled for elective surgery were analysed using the physiology-based method. ⋯ Percentage of values considered not different from baseline were calculated at each sampling timepoint following hyper- and hypoventilation. For the physiological method, bias and limits of agreement for pH and PCO2 were -0.001 (-0.022 to 0.020) and -0.02 (-0.37 to 0.33) kPa at baseline, respectively. 60 s following a change in ventilation, 100% of the mathematically arterialised values of pH and PCO2 were not different from baseline, compared to less than 40% of the measured arterial values at the same timepoint. In clinical situations where transient breath-holding or hyperventilation may compromise the accuracy of arterial blood samples, arterialised venous blood is a stable representative of steady state arterial blood.