View clinical trials related to Rare Diseases.
Filter by:The field of artificial intelligence is booming in medicine and in the field of diagnosis. The data can be varied: x-rays, pathology sections, or photographs. It is considered that 30 to 40% of the 7000 rare diseases described to date cause craniofacial dysmorphia. Their detection sometimes requires the trained eye of a geneticist, because certain phenotypic traits are subtle. These diagnostic difficulties and the fact that certain diseases are extremely uncommon lead to considerable diagnostic delays
Primary Study Objective The primary objective of the study is the definition of distinct vocal phenotypes and the development of an Explained Decision Support System (DSS) for the automatic detection of vocal patterns in relation to the syndrome from which the patients suffer Secondary: 1. Perceptual and acoustic analysis of voice recordings 2. Development of a voice recording collection system.
There are more than 7000 known genetic disorders, and the number of affected is estimated to be about 6-10% of the population. Around 30 to 40% of genetic disorders have physical changes in the face and skull such as Down's syndrome or Fragile X syndrome. Therefore, the known facial phenotype of many genetic disorders is highly informative to clinical diagnosis. Since a large number of genetic diseases are associated with special facial phenotypes that are difficult to remember, automated facial analysis such as Face2Gene and GestaltMatcher can assist in the identification and diagnosis of facial phenotypes related to various genetic diseases. Although the current advances in whole exome sequencing (whole exome sequencing) or whole genome sequencing (whole genome sequencing) have greatly improved the diagnostic rate of genetic diseases, about half of the patients are still undiagnosed. For patients with special facial phenotypes, the investigators believe that by combining automated facial analysis and whole exome sequencing data, it should be possible to provide a fast and accurate diagnostic model of genetic mutations for genetic diseases. GestaltMatcher Database is a medical imaging database of rare diseases developed by Professor Peter Krawitz of the University of Bonn, Germany. The database's artificial intelligence module will infer a patient's possible diagnosis based on the patient's photo, age, gender, race, and clinical description. The database will be open to medical researchers in related fields to improve the diagnosis of rare diseases. The investigators will use GestaltMatcher to assist in the diagnosis of patients, and compare the accuracy and significant differences in facial deformities between Taiwanese patients and patients from different countries. And use Eye Tracker to analyze how doctors diagnose patients through facial photos, and compare whether there are significant differences between foreign patients and Taiwanese patients in the diagnosis literature of Taiwanese doctors. The project will also analyze how genetic doctors at the University of Bonn in Germany diagnose patients, and compare it with Taiwanese doctors to better understand the differences in the process of doctors diagnosing patients and ethnic backgrounds.
This is a pilot, open-label, phase II study. The main objective of the study is to demonstrate that Cannabidiol (CBD), used in addition to current anti-seizure medications (ASMs) reduces the number and/or severity of motor (generalized, focal, or both) seizures in children and young adults with rare disease-associated severe epilepsy. Secondary objectives include assessment of safety and tolerability, changes in behaviour, cognition and sleep, pharmacokinetic interaction with concurrent ASMs.
Primary Central Nervous System Lymphoma (PCNSL) have a specific mutational profile in comparison to systemic diffuse large cells lymphoma (DLBCLs) that can be related to the expression of immunohistochemical markers as cyclon, NPM1, CD30, and P53 which could be predictive factor for prognosis and/or chemotherapy response. The main objective of this study is to identify new prognostic factors and new potential therapeutic targets. The secondary objectives are to correlate the histological, the radiological and the clinical's informations of these patients.
Factors associated with severe forms of COVID-19 infection in patients with inflammatory rheumatic diseases (IRD) or Autoimmune Diseases (AID) are unknown. This unprecedented situation leads to empirical and potentially erroneous advice and recommendations for care. Identifying factors associated with severity, in the context of this pandemic, which is expected to last many months, and possibly years, is crucial for future patients. The objective of this work is to identify the factors associated with the occurrence of severe forms of COVID-19 infection in patients with IRD or AID, by combining analysis of 2 large databases.
30 months, multicentre, prospective observational study on adult (>18 years) patients with a diagnosis of rare and complex connective tissue diseases (rCTDs) who will be given the vaccine during the period from January 2021 and January 2022. Patients with the following diagnosis will be included: - antiphospholipid syndrome (APS), - Ehlers-Danlos syndrome (EDS), - idiopathic inflammatory myopathies (IIM), - IgG4-related disease (IgG4), - mixed connective tissue disease (MCTD), - relapsing polychondritis (RP), - Sjogren's syndrome (SS), - systemic lupus erythematosus (SLE), - systemic sclerosis (SSc) - undifferentiated connective tissue disease (UCTD)
The recent implementation of European Reference Networks for Rare Diseases (ERNs) is an unprecedented move to improve the care of patients suffering from rare health disorders by transnational collaboration. ERN-RND, the ERN for Rare Neurological Diseases, oversees more than 35,000 patients in 31 specialist centers in 13 countries. The ERN-RND registry aims to gather information on patient cohorts in the multiple specialist centers and to provide an overview on patient numbers principally accessible for translational studies.
The project aims to improve the understanding of a significant group of rare diseases both from a genetic/diagnostic and clinical/experimental point of view and aims to develop one or more diagnostic protocols. The study will be conducted through the application of complementary experimental strategies, ranging from the clinical, genetic and molecular characterization of the pathology to the search for rare variants and the development of cellular disease models.