Machine learning models based on ultrasound and physical examination for airway assessment.

Purpose: To demonstrate the utility of machine learning models for predicting difficult airways using clinical and ultrasound parameters.

Methods: This is a prospective non-consecutive cohort of patients undergoing elective surgery. We collected as predictor variables age, sex, BMI, OSA, Mallampatti, thyromental distance, bite test, cervical circumference, cervical ultrasound measurements, and Cormack-Lehanne class after laryngoscopy.

Erector spinae plane block for thoracoscopy in a paediatric patient.

We present the case of a 9 year old patient with a clinical history of epilepsy and various hospitalizations due to aspirative broncopneumonia among others, who was admitted to our hospital because of septic shock secondary to pneumonia of the lower left lobule associated with a parapneumonic pleural effusion and a complicated clinical course. During her stay, the patient undergoes surgical debridement using video assisted thoracoscopic surgery (VATS) under general anaesthesia and the hydropneumothorax is drained. For the procedure an ecoguided erector spinae plane block is performed and combined with general anaesthesia.

Paralemmin-1 is expressed in lymphatic endothelial cells and modulates cell migration, cell maturation and tumor lymphangiogenesis.

The lymphatic system, the network of lymphatic vessels and lymphoid organs, maintains the body fluid balance and ensures the immunological surveillance of the body. In the adult organism, the de novo formation of lymphatic vessels is mainly observed in pathological conditions. In contrast to the molecular mechanisms governing the generation of the lymphatic vasculature during embryogenesis, the processes underlying pathological lymphangiogenesis are less well understood.