Background:

Nerve conduction studies are routinely used to assess peripheral nerve function. To interpret the results from these studies, reliable reference limits are essential. Traditionally, such reference limits have been established by examining healthy volunteers, a process that is both time-consuming and logistically demanding. Therefore, many neurophysiological laboratories adopt reference limits from literature or other laboratories. This practice may lead to misclassification and erroneous diagnoses, as reference limits can be sensitive to differences in procedures, equipment, and patient populations.

What we do:

In this study, we use historical data already available in our laboratory to derive new, laboratory-specific reference limits for carpal tunnel syndrome and polyneuropathy. We further assess how the use of these reference limits will affect the diagnosis of carpal tunnel syndrome and polyneuropathy in a clinical setting.
In the second part of the project, we investigate key prerequisites for the successful implementation of indirect methods for calculating reference values. We conduct a qualitative study involving interviews with health care personnel working in neurophysiological departments to identify barriers and facilitators to implementation.

Aims:

Our aim is to improve the diagnostic accuracy of the two most common disorders encountered in clinical neurophysiological practice: carpal tunnel syndrome and polyneuropathy. We will do this by applying methods that derive reference limits from historical data. These reference limits are laboratory-specific and stratified by age, sex, and height. Insights gained from the implementation study will further guide strategies for integrating these new methods into routine clinical practice

Contact:
Nora Hognestad Haaland, M.D., PhD candidate in this project.

• EPIC-AI (epic-ai.org)
  Enhancing Prognostication and Improving reliability of EEG assessments in Coma after Cardiac Arrest with Artificial Intelligence
  
  
• The VIKING project
  The world’s largest database for clinical neurophysiological studies. And a study of the trust to AI decision support systems among patients and health care professionals
  External homepage: https://viking-project.org/
  
  
• The ENTRAPME project – Improved diagnostics for nerve entrapments using machine learning
   
• The DIGMINE project - Digital gold mining in historical neurophysiological data for more precise diagnostics
  
  • NEUDAG (part of the DIGMINE+ research group)
    Implementing new methods for neurophysiological diagnostics by using and implementing historical data to create reference limits and validate these against the most commonly encountered diseases
     
• Neurological home hospital
  Innovation study funded by South-Eastern Health Authority. 2022 – 2024
   
• Can People with Charcot-Marie-Tooth Disease improve their balance with added haptic input? (CIBAHI)
  Investigating the role of haptic input on improving balance in people with Charcot Marie Tooth (CMT) disease.
   
• Innovation studies
  • Wearable Electrophysiology Mobility Solutions in Parkinson’s Disease (WEBSPD)
  • Innovation project developing wearable electrophysiology solutions for improving walking and balance in people with Parkinson’s Disease.
  • EEG learning platform

• Motor neurons – can they be counted? (MUNE and NI study)
  Study of new methods for diagnostics and follow-up of neuromuscular disease
   
• Tak-861
  Clinical Studies of Treatment of Narcolepsy
   
• NEUDAG: Implementing New Methods for Neurophysiological Diagnostics
  Improved diagnostics of carpal tunnel syndrome and polyneuropathy
   
• EBION
  Advancing Translation of Electrophysiology Biomarkers for Muscle Changes in Neuropathic Disorders [EBION]
   
• PETRA
  Multicenter randomized controlled study (PETRA-NMD) evaluating personalized exercise-based treatment for people with rare neuromuscular disorders, assessing effects on clinical outcomes and exploratory biomarkers.
   
• Identifying Novel Imaging biomarkers in epileptogenesis post traumatic brain injury
  Studying the glymphatic system and its abnormalities as potential predictor for epilepsi after traumatic brain injury by using an advanced machine learning MRI post processing tool.
   
• NOR-CACTUS
  Clinical project, in collaboration with Diakonhjemmet, evaluating a stepwise treatment strategy for mild to moderate idiopathic carpal tunnel syndrome (CTS), using ultrasound-guided corticosteroid injection, scheduled assessment, and surgery if needed, compared to primary surgical treatment, aiming to achieve non-inferior long-term outcomes while reducing adverse events and overall surgical interventions.
  
  
• Responsible for development and maintenance of "Neuroscience registry for research and quality studies" for Oslo University Hospital 2014 –. (oslo-universitetssykehus.no - in Norwegian)

Collaborative projects