Background: When a difficult airway is unanticipatedly encountered and the initial laryngoscopic intubation fails, a supraglottic airway device (SAD) may be placed to aid ventilation and oxygenation, and act as a conduit for intubation. SaCoVLM™, as new SAD, can offer a direct vision to guide intubation. However, no study has evaluated the performance of SaCoVLM™ video laryngeal mask (VLM) intubation and i-gel combined with flexible bronchoscopy (FB)-guided intubation in airway management during general anesthesia.
Methods: A total of 120 adult patients were randomly allocated into the SaCoVLM™ group (Group S) and i-gel group (Group I). After induction of general anesthesia, guided tracheal intubation under direct vision of the SaCoVLM™ was conducted in Group S, while Group I received FB-guided tracheal intubation using the i-gel. The success rate of SAD placement, first-pass success rate of guided tracheal tube placement, and total success rate in both groups were recorded. The time for SAD placement, time for guided tracheal intubation, total intubation time (time for SAD placement and intubation), glottic exposure grading and postoperative intubation complications (i.e., dysphagia, hoarseness, pharyngalgia, etc.) of both groups were also compared.
Results: The first-time success rate of SAD placement was 98% in two groups. The first-pass success rate of guided endotracheal intubation was 92% in Group S and 93% in Group I (P = 0.74 > 0.05). The total intubation time was 30.8(± 9.7) s and 57.4(± 16.6) s (95% CI = -31.5 to -21.7) in Group S and Group I, respectively (P < 0.01). The total complication rate was 8% in Group S and 22% in Group I (P < 0.05). The laryngeal inlet could be observed in the S group through the visual system of SaCoVLM™. No dysphagia or hoarseness was reported.
Conclusion: SaCoVLM™ can reveal the position of laryngeal inlet, thus providing direct vision for tracheal intubation. SaCoVLM™ -guided intubation is faster, and does not rely on FB, compared to i-gel combined with FB-guided intubation. Besides, SaCoVLM™ has a lower post-intubation complication rate.
Trial Registration: Chinese Clinical Trials Registry (ChiCTR2100043443); Date of registration: 18/02/2021.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9494909 | PMC |
http://dx.doi.org/10.1186/s12871-022-01843-x | DOI Listing |
Vaccines (Basel)
December 2024
Laboratory of Molecular Studies and Experimental Therapy-LEMTE, Department of Genetics, Federal University of Pernambuco, Recife 50670-901, Brazil.
Background/objectives: DNA vaccines are rapidly produced and adaptable to different pathogens, but they face considerable challenges regarding stability and delivery to the cellular target. Thus, effective delivery methods are essential for the success of these vaccines. Here, we evaluated the efficacy of capsules derived from the cell wall of the yeast as a delivery system for DNA vaccines.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Shanghai Research Institute of Microelectronics, Peking University, Shanghai 201203, China.
Despite the accuracy and robustness attained in the field of object tracking, algorithms based on Siamese neural networks often over-rely on information from the initial frame, neglecting necessary updates to the template; furthermore, in prolonged tracking situations, such methodologies encounter challenges in efficiently addressing issues such as complete occlusion or instances where the target exits the frame. To tackle these issues, this study enhances the SiamRPN algorithm by integrating the convolutional block attention module (CBAM), which enhances spatial channel attention. Additionally, it integrates the kernelized correlation filters (KCFs) for enhanced feature template representation.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Deanship of Preparatory Year and Supporting Studies, Imam Abdulrahman Bin Faisal University, Dammam 31441, Saudi Arabia.
Effective monitoring of road conditions is crucial for ensuring safe and efficient transportation systems. By leveraging the power of crowd-sourced smartphone sensor data, road condition monitoring can be conducted in real-time, providing valuable insights for transportation planners, policymakers, and the general public. Previous studies have primarily focused on the use of pre-trained machine learning models and threshold-based methods for anomaly classification, which may not be suitable for real-world scenarios that require incremental detection and classification.
View Article and Find Full Text PDFSensors (Basel)
December 2024
Qualcomm, San Jose, CA 95110, USA.
With the development of Internet of Vehicles (IoV) technology, the need for real-time data processing and communication in vehicles is increasing. Traditional request-based methods face challenges in terms of latency and bandwidth limitations. Mode 4 in cellular vehicle-to-everything (C-V2X), also known as autonomous resource selection, aims to address latency and overhead issues by dynamically selecting communication resources based on real-time conditions.
View Article and Find Full Text PDFSensors (Basel)
December 2024
College of Engineering, Huaqiao University, Quanzhou 362021, China.
Grasping objects of irregular shapes and various sizes remains a key challenge in the field of robotic grasping. This paper proposes a novel RGB-D data-based grasping pose prediction network, termed Cascaded Feature Fusion Grasping Network (CFFGN), designed for high-efficiency, lightweight, and rapid grasping pose estimation. The network employs innovative structural designs, including depth-wise separable convolutions to reduce parameters and enhance computational efficiency; convolutional block attention modules to augment the model's ability to focus on key features; multi-scale dilated convolution to expand the receptive field and capture multi-scale information; and bidirectional feature pyramid modules to achieve effective fusion and information flow of features at different levels.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!