Face

Systemic sclerosis is a rare autoimmune disorder characterized by microangiopathy, activation of the immune system, and sclerosis of tissues including the skin. Facial involvement is frequent and disabling. It causes significant functional and aesthetic discomfort, and a major deterioration in quality of life. It results in a loss of suppleness of the skin and subcutaneous tissues, dysfunction of the temporomandibular joint, peribuccal rhagades, microstomia, and dry mouth causing difficulties in mouth opening, feeding, dental care, and weight loss. Facial involvement in systemic sclerosis can be assessed using the Mouth Handicap in Systemic Sclerosis (MHISS) score, a validated patient questionnaire assessing the functional and aesthetic consequences of systemic sclerosis on the face. Although common and disabling, facial involvement is underestimated and poorly managed. Immunosuppressive and/or anti-fibrosis drugs are not very effective. Facial rehabilitation could significantly improve the mouth handicap but facial rehabilitation is not currently performed in standard care in systemic sclerosis patients. The aim of the study is to evaluate the efficacy of a personalized rehabilitation program vs standard care in facial involvement of systemic sclerosis patients.

Many clinical trials assessing the effectiveness of hypnosis have been conducted in recent years, some of which show that hypnosis reduces pain perception better than drug treatments administered to control groups, and that it is at least as effective as other complementary therapies (such as massage, acupuncture, yoga). However, their conclusions are limited by a significant risk of bias, and further studies with rigorous methodology remain necessary. The hypothesis of this study is that hypnosis support methods can reduce anxiety in patients requiring facial surgery under local anaesthesia, and thus improve their medical management. The purpose of this study is to evaluate the effectiveness of hypnosis support on the patient's state of anxiety before and after outpatient surgery under local anaesthesia in the Maxillofacial Surgery Department.

This study aims to evaluate the effectiveness of this facial image-based AI algorithm for screening CAD in high-risk community populations (specifically individuals with diabetes, hypertension, or aged over 65). The main objectives are: 1. To verify if the AI algorithm can accurately distinguish between high-risk and low-risk groups by comparing the actual prevalence of CAD in these groups. 2. To compare the CAD detection rate using this AI screening strategy against the natural detection rate in a real-world cohort.