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NCT06986187
A difficult airway is a clinical condition that occurs when one or more of the components of difficult mask ventilation, difficult laryngoscopy, difficult endotracheal intubation, difficult supraglottic airway device (SGA) placement, and inability to intubate-oxygenate are present. Data concerning incidence of difficult airway in patients undergoing cardiovascular surgery is controversial. Unwanted hemodynamic changes that may occur in patients undergoing cardiovascular surgery, combined with hemodynamic changes caused by underlying cardiac pathologies, may also lead to a physiologically difficult airway situation. Since all these interactions, combined with the hemodynamic changes caused by difficult airway interventions, may lead to catastrophic outcomes, it is vital to predict difficult airway in this patient population.
NCT07278232
1. Study Purpose This research aims to develop a novel, non-invasive, and simple method to predict difficult intubation before surgery. The core idea is that the anatomy of a person's throat and mouth, which determines the ease of intubation, also uniquely shapes their voice. By analyzing the acoustic features of specific vowel sounds using machine learning, we seek to identify voice patterns associated with difficult airways. The ultimate goal is to create a tool that allows for a quick, painless pre-operative risk assessment, enhancing patient safety by better preparing anesthesiologists. 2. Study Design This is a prospective, observational, single-center study. It is purely observational and does not involve any changes to standard medical care or anesthesia procedures. 3. Participants We plan to enroll 300 patients. Who can join: Patients aged 15-70 scheduled for elective surgery requiring general anesthesia with tracheal intubation. Who cannot join: Individuals with speech/hearing impairments, significant neurological diseases affecting speech, or conditions contraindicating standard laryngoscopy. 4. Study Procedures For participants, the study involves one key procedure in addition to standard care:Voice Recording: Before surgery, participants will be asked to lie down and pronounce the vowels "a," "e," and "i" steadily for 1-2 seconds. This will be done twice: once with the head in a normal position and once with the head tilted back. A high-quality recorder will capture the sounds. This process is painless and takes only a few minutes. Standard anesthesia and intubation will then proceed as usual. The anesthesiologist will record the laryngeal view obtained during intubation, which will be used to classify the case as "difficult" or "non-difficult" for analysis. 5. Data Analysis The primary goal is to determine if there are statistically significant differences in the key voice resonance frequencies (F1, F2, F3) between the difficult and non-difficult intubation groups. Advanced machine learning models will be built to create the predictive algorithm. 6. Risks and Benefits Benefits: There is no direct medical benefit to participants. The contribution is to future medical knowledge and patient safety. Risks: The study involves minimal risk. The voice recording is non-invasive and safe. The main risk is the potential loss of confidentiality, which is mitigated by strict data protection protocols. 7. Confidentiality \& Ethics All patient data will be de-identified and stored securely. The study protocol and informed consent form have been approved by the Institutional Ethics Committee of Shanghai Sixth People's Hospital. Participation is voluntary, and participants may withdraw at any time without affecting their medical care. Written informed consent will be obtained from every participant before any study procedures.
NCT06683599
Tracheal intubation in neonates can be technically challenging, even for experienced pediatric anesthesiologists, with a high first-attempt success rate crucial to ensure safety. Intubation, while life-saving for children with circulatory shock or respiratory failure, carries risks of severe desaturation that can lead to hypoxic encephalopathy, cardiac arrest, or death. Neonates, especially, are prone to hypoxemia due to high oxygen consumption, low functional residual capacity, small closing capacity, and increased risk of airway collapse, which is exacerbated under anesthesia and neuromuscular paralysis. Rapid desaturation occurs after cessation of ventilation, with neonates facing shorter apnea times before desaturation. Studies show that about two-thirds of neonates undergoing non-emergency nasotracheal intubation experience desaturation (SpO₂ \<80% for over 60 seconds), although low-flow oxygen supplementation (0.2 L/kg/min) can extend safe apnea time. This study aims to investigate apneic oxygenation with VL (using Miller or Macintosh blades size 0 or 1) in operating rooms or intensive care units. We hypothesize that supplemental oxygen and standardized VL use will improve first-pass success rates and reduce adverse events.
NCT07152093
This prospective observational study aims to develop an artificial intelligence model that can automatically determine the Cormack-Lehane classification from video laryngoscopy images in patients undergoing elective surgery. It also aims to predict the risk of difficult intubation based on this classification. The resulting data will evaluate the applicability of AI-supported decision support systems in clinical airway management.
NCT04212156
Difficult airway management is a major concern for anesthetists and contributes to perioperative morbidity and mortality. The incidence of difficult intubation in the obese population with a BMI of greater than 30 has been reported to be 15.8%. Thyromental height test (TMHT) is a new bedside test for difficult airway, it is a measure of the height between the anterior borders of the mentum and thyroid cartilage. TMHT can act as a surrogate for amount of mandibular protrusion; dimensions of submandibular space; and anterior position of the larynx. It appears promising as a single anatomical measure to predict the risk of difficult laryngoscopy.
NCT04140981
In this study, anthropometric measurements (clinical measurements) will be applied in all patient groups; expected (to be difficult to provide airway patency as a result of detailed history, physical examination and evaluation tests performed by an experienced anesthesiologist), and unexpected (although it was not predicted that a difficulty was encountered). And ultrasounographic measurements will be applied in all patients. The aim of this study is to evaluate the predictive accuracy of ultrasonographic measurements.