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The neurophysiological lesson from the Italian CIDP database.
- Source :
-
Neurological Sciences . Jan2022, Vol. 43 Issue 1, p573-582. 10p. 4 Charts, 3 Graphs. - Publication Year :
- 2022
-
Abstract
- Introduction: Electrophysiological diagnosis of chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) may be challenging. Thus, with the aim ofproviding some practical advice in electrophysiological approach to a patient with suspected CIDP, we analyzed electrophysiological data from 499 patients enrolled inthe Italian CIDP Database. Methods: We calculated the rate of each demyelinating feature, the rate of demyelinating features per nerve, the diagnostic rate for upper andlower limb nerves, and, using a ROC curve analysis, the diagnostic accuracy of each couple of nerves and each demyelinating feature, for every CIDP subtype.Moreover, we compared the electrophysiological data of definite and probable CIDP patients with those of possible and not-fulfilling CIDP patients, and by a logisticregression analysis, we estimated the odds ratio (OR) to make an electrophysiological diagnosis of definite or probable CIDP. Results: The ulnar nerve had the highestrate of demyelinating features and, when tested bilaterally, had the highest diagnostic accuracy except for DADS in which peroneal nerves were the most informative.In possible and not-fulfilling CIDP patients, a lower number of nerves and proximal temporal dispersion (TD) measurements had been performed compared to definiteand probable CIDP patients. Importantly, OR for each tested motor nerve and each TD measurement was 1.59 and 1.33, respectively. Conclusion: Our findingsdemonstrated that the diagnosis of CIDP may be missed due to inadequate or incomplete electrophysiological examination or interpretation. At the same time, thesedata taken together could be useful to draw a thoughtful electrophysiological approach to patients suspected of CIDP. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 15901874
- Volume :
- 43
- Issue :
- 1
- Database :
- Academic Search Index
- Journal :
- Neurological Sciences
- Publication Type :
- Academic Journal
- Accession number :
- 154457536
- Full Text :
- https://doi.org/10.1007/s10072-021-05321-z