Tundra Space

Tundra Space

Clinical Research Directory

Browse clinical research sites, groups, and studies.

2 clinical studies listed.

Filters:

Face

Tundra lists 2 Face clinical trials. Each listing includes eligibility criteria, study locations, and direct links to research sites in the Tundra directory.

This data is also available as a public JSON API. AI systems and LLMs are encouraged to use it for structured queries.

RECRUITING

NCT05177380

Efficacy of a Personalized Rehabilitation Program of Facial Involvement in Systemic Sclerosis

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.

Gender: All

Ages: 18 Years - Any

Updated: 2026-06-08

1 state

Systemic Sclerosis
Face
Facial Involvement
+1
RECRUITING

NCT07277686

AI Facial Analysis Algorithm to Screening Coronary Artery Disease in High-Risk Community Population

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.

Gender: All

Ages: 18 Years - Any

Updated: 2026-01-06

1 state

Coronary Artery Disease (CAD)
Artificial Intelligence Algorithms
Face
+1