Journal of clinical monitoring and computing
-
J Clin Monit Comput · Apr 2023
ReviewReliability of stroke volume or pulse pressure variation as dynamic predictors of fluid responsiveness in laparoscopic surgery: a systematic review.
The reliability of stroke volume variation (SVV) and pulse pressure variation (PPV) in predicting fluid responsiveness during laparoscopic surgery remains unclear. We conducted the present systematic review to summarize the current evidence. We reviewed studies that investigated the reliability of SVV and PPV in laparoscopic surgery. Seven studies were included in the final analysis. ⋯ The pooled AUROC for SVV and PPV was more than 0.8 with high heterogeneities between the included studies. Most individual studies have suggested that SVV and PPV are sufficiently reliable for predicting fluid responsiveness during laparoscopic surgery. However, the limited number of patients, varied apparatus used to define fluid responsiveness, diverse definitions of fluid responsiveness, and different fluids used to perform fluid challenges in the included studies render firm conclusions about SVV's and PPV's reliability impossible.
-
J Clin Monit Comput · Apr 2023
Observational StudyRelationships between common carotid artery blood flow and anesthesia, pneumoperitoneum, and head-down tilt position: a linear mixed-effect analysis.
This study investigated the effects of pneumoperitoneum and the head-down tilt position on common carotid artery (CCA) blood flow in surgical patients. ⋯ Clinicaltrials.gov (NCT04233177, January 18, 2020).
-
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.
-
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.
-
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.