Obesity Difficult Airway Airway Management

The OBESIAL (Obesity Structured Intervention in Algeria) study aims to evaluate the clinical, metabolic, and organisational impact of a structured multidisciplinary obesity care pathway implemented under real-world conditions.

The aim of this prospective study is to evaluate the accuracy of artificial intelligence (AI) and machine learning algorithms in predicting difficult airways in patients undergoing bariatric surgery. Preoperative airway assessments, including the Upper Lip Bite Test (UBLT), Mallampati score, Body Mass Index (BMI), thyromental distance (TMD), and sternomental distance (SMD), will be recorded. The study investigates whether AI models can provide higher sensitivity and specificity in predicting difficult intubation compared to traditional clinical scoring systems in the obese patient population.

This study aims to evaluate whether the Left Head Rotation (LeHeR) maneuver improves visualization of the vocal cords during video laryngoscopy in obese adult patients undergoing general anesthesia. Obesity is associated with increased difficulty in airway management due to excess upper airway soft tissue and altered anatomy, which may impair visualization during intubation. In this prospective observational study, 50 adult patients with a body mass index (BMI) ≥30 kg/m² will undergo video laryngoscopy using a C-MAC D-blade. The glottic view will be assessed using the Percentage of Glottic Opening (POGO) score in the standard sniffing position and after rotating the head 45 degrees to the left (LeHeR maneuver). A difference in POGO score between the two positions will be analyzed. Secondary outcomes include ease of intubation, number of attempts, time to successful intubation, and occurrence of complications such as desaturation or airway trauma. The study is expected to determine whether the LeHeR maneuver is a simple and effective technique to improve airway visualization in obese patients.