Back to Search
Start Over
Diagnostic delay in amyotrophic lateral sclerosis.
- Source :
- European Journal of Neurology; Sep2023, Vol. 30 Issue 9, p2595-2601, 7p
- Publication Year :
- 2023
-
Abstract
- Background: Amyotrophic lateral sclerosis (ALS) is a progressive, fatal neurodegenerative disease, and the time from symptom onset to diagnosis remains long. With the advent of disease‐modifying treatments, the need to identify and diagnose ALS in a timely fashion has never been greater. Methods: We reviewed the literature to define the severity of ALS diagnostic delay, the various factors that contribute to this delay (including patient and physician factors), and the role that site of symptom onset plays in a patient's diagnostic journey. Results: Diagnostic delay is influenced by general practitioners' lack of recognition of ALS due to disease rarity and heterogenous presentations. As a result, patients are referred to non‐neurologists, have unnecessary diagnostic testing, and may ultimately be misdiagnosed. Patient factors include their illness behavior—which impacts diagnostic delay—and their site of symptom onset. Limb‐onset patients have the greatest diagnostic delay because they are frequently misdiagnosed with degenerative spine disease or peripheral neuropathy. Conclusion: Prompt ALS diagnosis results in more effective clinical management, with earlier access to disease‐modifying therapies, multidisciplinary care, and, if desired, clinical trial involvement. Due to lack of commercially available ALS biomarkers, alternative strategies to identify and triage patients who likely have ALS must be employed. Several diagnostic tools have been developed to encourage general practitioners to consider ALS and make an urgent referral to ALS specialists, bypassing unnecessary referrals to non‐neurologists and unnecessary diagnostic workup. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 13515101
- Volume :
- 30
- Issue :
- 9
- Database :
- Complementary Index
- Journal :
- European Journal of Neurology
- Publication Type :
- Academic Journal
- Accession number :
- 169809589
- Full Text :
- https://doi.org/10.1111/ene.15874