During Your Child’s Hospital Stay | NYU Langone Health
We offer tips on what to expect during your child’s stay at Hassenfeld Children’s Hospital at NYU Langone.
Dysautonomia Center | NYU Langone Health
NYU Langone’s Dysautonomia Center is dedicated to improving the lives of people with autonomic disorders, offering a range of treatment options.
Dysautonomia Center Doctors | NYU Langone Health
Find a doctor at the Dysautonomia Center at NYU Langone.
Ear, Nose, Throat & Mouth Conditions | NYU Langone Health
NYU Langone ear, nose, throat, and mouth (ENT) specialists provide children and adults with comprehensive services for a range of conditions.
Early Access Program with Arimoclomol for the Treatment of Niemann-Pick disease Type C in the US
In alignment with Orphazyme’s Early Access Policy, Orphazyme has launched a Single Patient Early Access Program (EAP) due to the urgent unmet medical need of patients with NPC and the fact that not all patients are able to participate in clinical trials for various reasons. In addition, Orphazyme will provide Early Access to arimoclomol on group level to bridge the time gap until the product becomes commercially available with this EAP.
Early Childhood Services at Family Health Centers at NYU Langone | NYU Langone Health
Early childhood services are provided through Family Health Centers at NYU Langone’s Community-Based Programs.
EARLY DETECTION OF ALPHA-SYNUCLEIN DISEASE Single-center cross-sectional and longitudinal non-interventional observational study of biomarkers in prodromal synucleinopathy
Single-center, cross-sectional and longitudinal exploratory observational study of approximately 80 patients with diagnoses of pure autonomic failure (PAF), Parkinson´s Disease, Multiple System Atrophy, Lewy Body Dementia and prodromal patients with or without REM-sleep behavior disorder (RBD), early motor signs of parkinsonism and autonomic abnormalities without definitive diagnosis, who are considered prodromal forms a-synuclein disease. We will use novel a-synuclein seed amplification assays (SAA) to detect pathologic a-synuclein conformers in skin biopsies of patients with PD, MSA LBD or PAF, to validate these assays for early detection of a-synuclein. Also, the study will characterize early disease in patients with suggestive early neurologic symptoms prior to significant neurodegeneration. Finally, the assay will inform as to a-synuclein strain identity that can differentiate risk of PD/DLB vs. MSA. These assays will be complemented by clinical, cognitive, olfactory, assessments, and Brain imaging with dopamine transporter (DAT)-SPECT and brain MRI if available in the chart. Eligible patients will be followed with annual clinical assessments, with single additional collection of biomarkers and imaging if they demonstrate conversion to major degenerative synucleinopathy.
Early Intervention for Cerebral Palsy in Children | NYU Langone Health
Doctors at Hassenfeld Children’s Hospital at NYU Langone offer immediate care for newborns with neurological disorders such as cerebral palsy.
Early Intervention for Newborns with Spina Bifida | NYU Langone Health
Neonatal specialists at Hassenfeld Children’s Hospital at NYU Langone provide immediate care for newborns with severe forms of spina bifida.
Early Signs: digital phenotyping to identify digital biomarkers for predicting burnout and cognitive functioning in ED clinicians
Our overall goal is to enhance the ability to assess and understand the development of burnout amongst ED staff using objective, ecologically valid, economical, and accurate digital biomarkers of burnout as a potential alternative to self-report measures for burnout. We are asking ED staff & clinicians who works full-time in the emergency departments to participate. The purpose of this study is to test the feasibility of collecting and analyzing video-recorded semi-structured interviews about experiences at work of Emergency Department (ED) staff to identify digital biomarkers of burnout using Machine Learning methods. As part of the study, we will video-record 15-minute interviews about experiences at work, collect hair samples, blood samples and conduct a neurocognitive test battery (CANTAB®). Afterward, we will use a computer algorithm to test if we can predict work-related well-being (i.e., symptoms of job stress) and neurocognitive functioning based on the information from the video-recording including facial emotion expression, voice prosody, and other factors captured on video. In more technical terms, we apply Transfer Learning for feature extraction from raw video and audio recordings to develop digital biomarkers in order to test whether digital biomarkers can reliably predict future burnout symptom scores. The predictive value of candidate features is evaluated using supervised machine learning using the well-established, validated, and reliable Maslach Burnout Inventory (MBI9) as an outcome to predict.