Journal of clinical monitoring and computing
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Four recent cases utilizing transabdominal motor-evoked potentials (TaMEPs) are presented as illustrative of the monitoring technique during lumbosacral fusion, sciatic nerve tumor resection, cauda equina tumor resection, and lumbar decompression. Case 1: In a high-grade lumbosacral spondylolisthesis revision fusion, both transcranial motor-evoked potentials (TcMEPs) and TaMEPs detected a transient focal loss of left tibialis anterior response in conjunction with L5 nerve root decompression. ⋯ Case 4: TaMEPs were successfully acquired with little anesthetic fade utilizing an anesthetic regimen of 1.1 MAC Sevoflurane during a lumbar decompression. While the first two cases present TaMEPs and TcMEPs side-by-side, demonstrating TaMEPs correlating to TcMEPs (Case 1) or a more accurate reflection of patient outcome (Case 2), no inference regarding the accuracy of TaMEPs to monitor nerve elements during cauda equina surgery (Cases 3) or the lumbar decompression presented in Case 4 should be made as these are demonstrations of technique, not utility.
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J Clin Monit Comput · Apr 2023
Reliability of submaximal stimulation for the train-of-four test using acceleromyography and electromyography with individualized stimulation currents.
The supramaximal stimulation (SMS) of the TOF test causes uncomfortable sensations in patients. We aimed to determine whether the submaximal stimulation would be reliable in TOF tests with reduced painful sensation. ⋯ The TOF test with submaximal stimulation is still reliable and can reduce stimulation pain. Considering the importance of the TOF results in determining extubation, the authors suggest the minimal current for the TOF test as 70% SMS.
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Recent publications have suggested that pulse oximeters exhibit reduced accuracy in dark-skinned patients during periods of hypoxemia. Masimo SET® (Signal Extraction Technology®) has been designed, calibrated, and validated using nearly equal numbers of dark and light skinned subjects, with the goal of eliminating differences between pulse oximetry saturation (SpO2) and arterial oxygen saturation (SaO2) values due to skin pigmentation. The accuracy concerns reported in dark-skinned patients led us to perform a retrospective analysis of healthy Black and White volunteers. ⋯ Occult hypoxemia was rare and did not occur in Black subjects. Masimo RD SET® can be used with equal assurance in people with dark or light skin. These laboratory results were obtained in well-controlled experimental conditions in healthy volunteers-not reflecting actual clinical conditions/patients.
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J Clin Monit Comput · Apr 2023
A machine learning approach to predicting early and late postoperative reintubation.
Accurate estimation of surgical risks is important for informing the process of shared decision making and informed consent. Postoperative reintubation (POR) is a severe complication that is associated with postoperative morbidity. Previous studies have divided POR into early POR (within 72 h of surgery) and late POR (within 30 days of surgery). ⋯ The scoring systems developed from the logistic regression models demonstrated strong performance in terms of both accuracy and discrimination across the different POR outcomes (Average Brier score, 0.172; Average c-statistic, 0.852). These results were only marginally worse than prediction using the full set of risk variables (Average Brier score, 0.145; Average c-statistic, 0.870). While more work needs to be done to identify clinically relevant differences between the early and late POR outcomes, the scoring systems provided here can be used by surgeons and patients to improve the quality of care overall.
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J Clin Monit Comput · Apr 2023
Development and usage of an anesthesia data warehouse: lessons learnt from a 10-year project.
This paper describes the development and implementation of an anesthesia data warehouse in the Lille University Hospital. We share the lessons learned from a ten-year project and provide guidance for the implementation of such a project. Our clinical data warehouse is mainly fed with data collected by the anesthesia information management system and hospital discharge reports. ⋯ We reported the main concerns and barriers during the development of this project and we provided 8 tips to handle them. We have implemented our data warehouse into the OMOP common data model as a complementary downstream data model. The next step of the project will be to disseminate the use of the OMOP data model for anesthesia and critical care, and drive the trend towards federated learning to enhance collaborations and multicenter studies.