Clinical Research Directory

Intubation Conditions During ERCP With Lidocaine Aerosol Plus Low-dose Cisatracurium or Conventional-dose Cisatracurium

This clinical study investigates the effects of lidocaine aerosol as an adjunct to low-dose cisatracurium for endotracheal intubation during ERCP (Endoscopic Retrograde Cholangiopancreatography) procedures. The aim is to assess whether lidocaine aerosol can improve the clinical conditions of intubation to a level comparable to the standard dose of cisatracurium, while reducing the amount of muscle relaxant required. The study also seeks to evaluate the impact of this approach on intubation success, extubation time, and recovery time in the operating room, ultimately improving the efficiency of the operating room. Participants will be randomly assigned to either the low-dose cisatracurium group with lidocaine aerosol or the standard-dose cisatracurium group. The primary outcome is the incidence of clinically acceptable intubation conditions, defined by the Cooper's grading system.

Pediatric Airway: Noninferiority Trial of Devices for Intubation Assessment

The goal of this clinical trial is to find out whether the BESDATA BD-DF videolaryngoscope works as well as the McGRATH™ MAC videolaryngoscope for placing a breathing tube in infants during surgery. The study will also compare the costs associated with using each device. The main questions this study aims to answer are: Is the BESDATA BD-DF videolaryngoscope as effective as the McGRATH™ MAC videolaryngoscope for successful placement of a breathing tube on the first attempt in infants? Are there differences between the two devices in terms of procedure time, number of attempts, airway-related complications, and overall costs? Researchers will compare infants who are intubated using the BESDATA BD-DF videolaryngoscope with infants who are intubated using the McGRATH™ MAC videolaryngoscope to see whether the two devices perform similarly and whether one is more cost-effective than the other. Participants will: Be randomly assigned to have a breathing tube placed using one of the two videolaryngoscopes; Receive standard general anesthesia for an elective surgical procedure; Have information collected during and after the procedure to assess safety, effectiveness, and costs.

Evaluation of Anterior Neck Ultrasound in Predicting Difficult Airway in Obese Patients

Obese patients are at increased risk of difficult airway management due to anatomical changes in the anterior neck soft tissues. Accurate preoperative prediction of difficult airway remains challenging using conventional clinical airway assessment tests alone. This prospective observational study aims to evaluate the role of ultrasound assessment of anterior neck soft tissue thickness in predicting difficult airway risk in overweight and obese adult patients undergoing elective surgery under general anesthesia. Ultrasound-based anterior neck measurements will be compared with standard clinical airway assessment parameters to determine their diagnostic accuracy for difficult laryngoscopy and intubation. The results of this study may contribute to improved preoperative airway risk stratification and safer airway management in obese patients.

Classification and Prediction of Difficult Awake Tracheal Intubation With Flexible Bronchoscopes

Airway management problems are key drivers for anesthesia-related adverse events. Awake tracheal intubation using flexible bronchoscopes with preserved spontaneous breathing (ATI:FB) is a recommended technique to manage difficult tracheal intubation in anesthesia, intensive care and emergency medicine. However, a prospective developed classification for this type of airway management is lacking. Due to the absence of a specifically tailored, validated classification for awake intubation with flexible bronchoscopes, many airway operators and institutions use classification tools that were originally developed for direct laryngoscopy, such as the percentage of glottic opening (POGO) score or Cormack-Lehane classification, although their diagnostic performance for the classification of ATI:FB is unknown. This prospective model development and validation study aims to develop two multivariable prediction models: a diagnostic prediction model to classify difficult ATI:FB after ATI:FB has been performed and a second prognostic prediction model to predict the risk for difficult ATI:FB before ATI:FB is performed. An additional aim is to develop a machine learning algorithm to evaluate ATI:FB.