Development and validation of an artificial intelligence algorithm for detecting vocal cords in video laryngoscopy.

Airway procedures in life-threatening situations are vital for saving lives. Video laryngoscopy (VL) is commonly performed during endotracheal intubation (ETI) in the emergency department. Artificial intelligence (AI) is widely used in the medical field, particularly to detect anatomical structures. This study aimed to develop an AI algorithm that detects vocal cords from VL images acquired during emergent situations. This retrospective study used VL images acquired in the emergency department to facilitate the ETI. The vocal cord image was labeled with a ground-truth bounding box. The dataset was divided into training and validation datasets. The algorithm was developed from a training dataset using the YOLOv4 model. The performance of the algorithm was evaluated using a test set. The test set was further divided into specific environments during the ETI for clinical subgroup analysis. In total, 20,161 images from 84 patients were used in this study. A total of 10,287, 5766, and 4108 images were used for the model training, validation, and test sets, respectively. The developed algorithm achieved F1 score 0.906, sensitivity 0.963, and specificity 0.842 in the validation set. The performance in the test set was F1 score 0.808, sensitivity 0.823, and specificity 0.804. We developed and validated an AI algorithm to detect vocal cords in VL. This algorithm demonstrated a high performance. The algorithm can be used to determine the vocal cord to ensure safe ETI.

Mask R-CNN based multiclass segmentation model for endotracheal intubation using video laryngoscope.

Objective: Endotracheal intubation (ETI) is critical to secure the airway in emergent situations. Although artificial intelligence algorithms are frequently used to analyze medical images, their application to evaluating intraoral structures based on images captured during emergent ETI remains limited. The aim of this study is to develop an artificial intelligence model for segmenting structures in the oral cavity using video laryngoscope (VL) images. Methods: From 54 VL videos, clinicians manually labeled images that include motion blur, foggy vision, blood, mucus, and vomitus. Anatomical structures of interest included the tongue, epiglottis, vocal cord, and corniculate cartilage. EfficientNet-B5 with DeepLabv3+, EffecientNet-B5 with U-Net, and Configured Mask R-Convolution Neural Network (CNN) were used; EffecientNet-B5 was pretrained on ImageNet. Dice similarity coefficient (DSC) was used to measure the segmentation performance of the model. Accuracy, recall, specificity, and F1 score were used to evaluate the model's performance in targeting the structure from the value of the intersection over union between the ground truth and prediction mask. Results: The DSC of tongue, epiglottis, vocal cord, and corniculate cartilage obtained from the EfficientNet-B5 with DeepLabv3+, EfficientNet-B5 with U-Net, and Configured Mask R-CNN model were 0.3351/0.7675/0.766/0.6539, 0.0/0.7581/0.7395/0.6906, and 0.1167/0.7677/0.7207/0.57, respectively. Furthermore, the processing speeds (frames per second) of the three models stood at 3, 24, and 32, respectively. Conclusions: The algorithm developed in this study can assist medical providers performing ETI in emergent situations.

Usability testing of a blind intubation device for intubation novices: a randomized crossover simulation study.

OBJECTIVE: A new blind intubation device (BID) has been developed for endotracheal intubation. This study aimed to test the usability of the BID in comparison to direct laryngoscopy (DL) and video laryngoscopy (VL) with inexperienced healthcare providers for endotracheal intubation. METHODS: This was a randomized crossover simulation study. Participants who had conducted fewer than five live intubation sessions were included in the study. The manikin simulation was conducted using a Laerdal trainer airway manikin. Participants performed intubation using all three devices, DL, VL, and BID. The primary outcome was intubation success rate in the first pass the secondary outcome was intubation time to first ventilation, and the tertiary outcome was dental injury. RESULTS: A total of 45 healthcare workers who were novices in intubation participated in this study, including 13 physicians (interns), 14 emergency medical technicians, and 18 nurses. The intubation success rates in the first pass with BID, DL, and VL were 93.3%, 91.1%, and 97.8%, respectively (P=0.53). The intubation times to first ventilation with BID, DL, and VL were 13.15±6.16, 19.07±7.71, and 17.31±6.57 seconds, respectively (P<0.01). The proportions of dental injuries associated with BID, DL, and VL were 0% for physicians; 28.6%, 14.3%, and 0%, respectively for emergency medical technicians; and 27.8%, 11.1%, and 16.7%, respectively for nurses. CONCLUSION: We performed a pilot study to test the usability of the new BID. There was no significant difference in intubation success rate in the first pass among BID, DL, and VL. The intubation time to first ventilation was shorter with the BID compared to DL and VL.

Evaluation of the conventional and modified aerosol boxes during tracheal intubation in normal and difficult airways: a randomized, crossover, manikin simulation study.

The aim of this study was to evaluate conventional and modified aerosol boxes in terms of intubation time, first-pass intubation success, and mouth-to-mouth distance between the laryngoscopist and patient during tracheal intubation in simulated patients with normal and difficult airways. Sixteen anesthesiologists performed tracheal intubations with direct laryngoscope or three different videolaryngoscopes (McGRATH MAC videolaryngoscope, C-MAC videolaryngoscope, and Pentax-AWS) without an aerosol box or with a conventional or a modified aerosol boxes in simulated manikins with normal and difficult airways. Intubation time, first-pass intubation success, and mouth-to-mouth distance during tracheal intubation were recorded. Compared to no aerosol box, the use of a conventional aerosol box significantly increased intubation time in both normal and difficult airways (Bonferroni-corrected P-value (Pcorrected) = 0.005 and Pcorrected = 0.003, respectively). Intubation time was significantly shorter with the modified aerosol box than with the conventional one for both normal and difficult airways (Pcorrected = 0.003 and Pcorrected = 0.011, respectively). However, no significant differences were found in intubation time between no aerosol box and the modified aerosol box for normal and difficult airways (Pcorrected = 0.336 and Pcorrected = 0.112, respectively). The use of conventional or modified aerosol boxes significantly extended the mouth-to-mouth distances compared to not using an aerosol box during tracheal intubation with each laryngoscope (all Pcorrected < 0.05), and the distances were not different between the conventional and modified boxes in normal and difficult airways. The use of modified aerosol box did not increase intubation time and could help maintain a distance from the simulated patients with normal and difficult airways.

Impact of crowding in local ambulance demand on call-to-ambulance scene arrival in out-of-hospital cardiac arrest.

BACKGROUND: Rapid emergency medical service (EMS) response is an important prognostic factor in out-of-hospital cardiac arrest (OHCA). This study aims to evaluate the association between local hourly EMS demand and ambulance response in OHCA. METHODS: OHCA occurring in 24 districts of Seoul from 2013 to 2018 was analyzed. Hourly ambulance demand per ambulance in each local district of patient location at the hour of cardiac arrest was calculated as the crowding index. The crowding index was categorized according to quartiles (1Q: ≤0.43, 2Q: 0.44-0.67, 3Q: 0.68-0.99, 4Q: ≥1.0 calls/h\r/ambulance). The primary outcome was ambulance dispatched within 1 km of the OHCA scene. Multivariable logistic regression analysis was performed to test the association between the local hourly ambulance demand and outcomes. RESULTS: A total of 26,479 patients were analyzed. The rate of ambulance dispatched within 1 km decreased according to the crowding quartile (1Q: 31.3%, 2Q: 30.0%, 3Q: 28.8%, and 4Q: 26.6%). Compared to 1Q, adjusted odds ratios (95% CIs) of dispatch distance within 1 km in 2Q, 3Q, and 4Q were 0.92 (0.86-0.99), 0.86 (0.80-0.94), and 0.77 (0.71-0.84), respectively. CONCLUSION: Crowding in local ambulance demand was associated with less ambulance dispatched within 1 km and delayed response to the scene in OHCA. Strategies to mitigate and adjust to ambulance demand crowding may be considered for better EMS response performance.

Association between prehospital field to emergency department delta shock index and in-hospital mortality in patients with torso and extremity trauma: A multinational, observational study.

Hemorrhage, a main cause of mortality in patients with trauma, affects vital signs such as blood pressure and heart rate. Shock index (SI), calculated as heart rate divided by systolic blood pressure, is widely used to estimate the shock status of patients with hemorrhage. The difference in SI between the emergency department and prehospital field can indirectly reflect urgency after trauma. We aimed to determine the association between delta SI (DSI) and in-hospital mortality in patients with torso or extremity trauma. Patients with DSI >0.1 are expected to be associated with high mortality. This retrospective, observational study used data from the Pan-Asian Trauma Outcomes Study. Patients aged 18-85 years with abdomen, chest, upper extremity, lower extremity, or external injury location were included. Patients from China, Indonesia, Japan, Philippines, Thailand, and Vietnam; those who were transferred from another facility; those who were transferred without the use of emergency medical service; those with prehospital cardiac arrest; those with unknown exposure and outcomes were excluded. The exposure and primary outcome were DSI and in-hospital mortality, respectively. The secondary and tertiary outcome was intensive care unit (ICU) admission and massive transfusion, respectively. Multivariate logistic regression analysis was performed to test the association between DSI and outcome. In total, 21,534 patients were enrolled according to the inclusion and exclusion criteria. There were 3,033 patients with DSI >0.1. The in-hospital mortality rate in the DSI >0.1 and ≤0.1 groups was 2.0% and 0.8%, respectively. In multivariate logistic regression analysis, the DSI ≤0.1 group was considered the reference group. The unadjusted and adjusted odds ratios of in-hospital mortality in the DSI >0.1 group were 2.54 (95% confidence interval [CI] 1.88-3.42) and 2.82 (95% CI 2.08-3.84), respectively. The urgency of traumatic hemorrhage can be determined using DSI, which can help hospital staff to provide proper trauma management, such as early trauma surgery or embolization.

Place-provider-matrix of bystander cardiopulmonary resuscitation and outcomes of out-of-hospital cardiac arrest: A nationwide observational cross-sectional analysis.

AIMS: This study aims to test the association between the place-provider-matrix (PPM) of bystander cardiopulmonary resuscitation (CPR) and outcomes of out-of-hospital cardiac arrest (OHCA). METHODS: Adult patients with OHCA with a cardiac etiology from 2012 to 2017 in Korea were analyzed, excluding patients who had unknown information on place, type of bystander, or outcome. The PPM was categorized into six groups by two types of places (public versus home) and three types of providers (trained responder (TR), family bystander, and layperson bystander). Outcomes were survival to discharge and good cerebral performance category (CPC) of 1 or 2. Multivariable logistic regression analysis was performed to test the association between PPM group and outcomes with adjustment for potential confounders to calculate adjusted odds ratios (AORs) and 95% confidence intervals (CIs) (reference = Public-TR). RESULTS: A total of 73,057 patients were analyzed and were categorized into Public-TR (0.6%), Home-TR (0.3%), Public-Family (1.8%), Home-Family (79.8%), Public-Layperson (9.9%), and Home-Layperson (7.6%) groups. Compared with the Public-TR group, the AORs (95% CIs) for survival to discharge were 0.61 (0.35-1.05) in the Home-TR group, 0.85 (0.62-1.17) in the Public-Family group, 0.38 (0.29-0.50) in the Home-Family group, 1.12 (0.85-1.49) in the Public-Layperson group, and 0.42 (0.31-0.57) in the Home-Layperson group. The AORs (95% CIs) for good CPC were 0.58 (0.27-1.25) in the Home-TR group, 0.88 (0.61-1.27) in the Public-Family group, 0.38 (0.28-0.52) in the Home-Family group, 1.20 (0.87-1.65) in the Public-Layperson group, and 0.42 (0.30-0.59) in the Home-Layperson group. CONCLUSION: The OHCA outcomes of the Home-Family and Home-Layperson groups were worse than those of the Public-TR group. This finding suggests that OHCA occurring in private places with family or layperson bystanders requires a new strategy, such as dispatching trained responders to the scene to improve CPR outcomes.