Journal of clinical monitoring and computing
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J Clin Monit Comput · Oct 2024
Predictive value of TCCD and regional cerebral oxygen saturation for detecting early postoperative brain injury.
This study aims to analyze the risk factors for early postoperative brain injury in patients undergoing cardiovascular surgery and explore the predictive value of transcranial color Doppler (TCCD) and regional cerebral oxygen saturation (rSO2) for detecting early postoperative brain injury in cardiovascular surgery patients. ⋯ The decreased rSO2 and cerebral blood flow levels, aorta occlusion time, and history of atrial fibrillation were independent risk factors for early postoperative brain injury. TCCD and rSO2 could effectively monitor brain metabolism and cerebral blood flow and predict early postoperative brain injury.
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J Clin Monit Comput · Oct 2024
Observational StudyMechanical power during robotic-assisted laparoscopic prostatectomy: an observational study.
Robotic-assisted laparoscopic radical prostatectomy (RALP) requires pneumoperitoneum and steep Trendelenburg position. Our aim was to investigate the influence of the combination of pneumoperitoneum and Trendelenburg position on mechanical power and its components during RALP. ⋯ Mechanical power in healthy patients undergoing RALP significantly increased both during the pneumoperitoneum and Trendelenburg position and in supine position after surgery. PEEP always increased mechanical power without ameliorating the respiratory system elastance.
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J Clin Monit Comput · Oct 2024
Bayesian networks for Risk Assessment and postoperative deficit prediction in intraoperative neurophysiology for brain surgery.
To this day there is no consensus regarding evidence of usefulness of Intraoperative Neurophysiological Monitoring (IONM). Randomized controlled trials have not been performed in the past mainly because of difficulties in recruitment control subjects. In this study, we propose the use of Bayesian Networks to assess evidence in IONM. ⋯ Bayesian Networks are an effective way to audit clinical practice within IONM. We have found that IONM warnings can serve to prevent neurological deficits in patients, especially when corrective surgical action is taken to attempt to revert signals changes back to baseline properties. We show that Bayesian Networks could be used as a mathematical tool to calculate the utility of conducting IONM, which could save costs in healthcare when performed.
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J Clin Monit Comput · Oct 2024
Video-based automatic hand hygiene detection for operating rooms using 3D convolutional neural networks.
Hand hygiene among anesthesia personnel is important to prevent hospital-acquired infections in operating rooms; however, an efficient monitoring system remains elusive. In this study, we leverage a deep learning approach based on operating room videos to detect alcohol-based hand hygiene actions of anesthesia providers. Videos were collected over a period of four months from November, 2018 to February, 2019, at a single operating room. Additional data was simulated and added to it. ⋯ Optical flow was calculated and utilized as an additional input modality. Accuracy, sensitivity and specificity were evaluated hand hygiene detection. Evaluations of the binary classification of hand-hygiene actions revealed an accuracy of 0.88, a sensitivity of 0.78, a specificity of 0.93, and an area under the operating curve (AUC) of 0.91. A 3D CNN-based algorithm was developed for the detection of hand hygiene action. The deep learning approach has the potential to be applied in practical clinical scenarios providing continuous surveillance in a cost-effective way.
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J Clin Monit Comput · Oct 2024
Effect of vertical stopcock position on start-up fluid delivery in syringe pumps used for microinfusions.
The purpose of this in vitro study was to evaluate the impact of the vertical level of the stopcock connecting the infusion line to the central venous catheter on start-up fluid delivery in microinfusions. Start-up fluid delivery was measured under standardized conditions with the syringe outlet and liquid flow sensors positioned at heart level (0 cm) and exposed to a simulated CVP of 10 mmHg at a set flow rate of 1 ml/h. Flow and intraluminal pressures were measured with the infusion line connected to the stopcock primarily placed at vertical levels of 0 cm, + 30 cm and - 30 cm or primarily placed at 0 cm and secondarily, after connecting the infusion line, displaced to + 30 cm and - 30 cm. Start-up fluid delivery 10 s after opening the stopcock placed at zero level and after opening the stopcock primarily connected at zero level and secondary displaced to vertical levels of + 30 cm and - 30 cm were similar (- 10.52 [- 13.85 to - 7.19] µL; - 8.84 [- 12.34 to - 5.33] µL and - 11.19 [- 13.71 to - 8.67] µL (p = 0.469)). ⋯ Start-up fluid delivery with the stopcock primarily placed at + 30 cm and - 30 cm resulted in large anterograde and retrograde fluid volumes of 34.39 [33.43 to 35.34] µL and - 24.90 [- 27.79 to - 22.01] µL at 10 s, respectively (p < 0.0001). Fluid delivered with the stopcock primarily placed at + 30 cm and - 30 cm resulted in 140% and 35% of calculated volume at 360 s, respectively (p < 0.0001). Syringe infusion pumps should ideally be connected to the stopcock positioned at heart level in order to minimize the amounts of anterograde and retrograde fluid volumes after opening of the stopcock.