| Title |
Status of diagnostic approaches to AQP4-IgG seronegative NMO and NMO/MS overlap syndromes
|
|---|---|
| Published in |
Journal of Neurology, November 2015
|
| DOI | 10.1007/s00415-015-7952-8 |
| Pubmed ID | |
| Authors |
Maciej Juryńczyk, Brian Weinshenker, Gulsen Akman-Demir, Nasrin Asgari, David Barnes, Mike Boggild, Abhijit Chaudhuri, Marie D’hooghe, Nikos Evangelou, Ruth Geraldes, Zsolt Illes, Anu Jacob, Ho Jin Kim, Ingo Kleiter, Michael Levy, Romain Marignier, Christopher McGuigan, Katy Murray, Ichiro Nakashima, Lekha Pandit, Friedemann Paul, Sean Pittock, Krzysztof Selmaj, Jérôme de Sèze, Aksel Siva, Radu Tanasescu, Sandra Vukusic, Dean Wingerchuk, Damian Wren, Isabel Leite, Jacqueline Palace |
| Abstract |
Distinguishing aquaporin-4 IgG(AQP4-IgG)-negative neuromyelitis optica spectrum disorders (NMOSD) from opticospinal predominant multiple sclerosis (MS) is a clinical challenge with important treatment implications. The objective of the study was to examine whether expert clinicians diagnose and treat NMO/MS overlapping patients in a similar way. 12 AQP4-IgG-negative patients were selected to cover the range of clinical scenarios encountered in an NMO clinic. 27 NMO and MS experts reviewed their clinical vignettes, including relevant imaging and laboratory tests. Diagnoses were categorized into four groups (NMO, MS, indeterminate, other) and management into three groups (MS drugs, immunosuppression, no treatment). The mean proportion of agreement for the diagnosis was low (p o = 0.51) and ranged from 0.25 to 0.73 for individual patients. The majority opinion was divided between NMOSD versus: MS (nine cases), monophasic longitudinally extensive transverse myelitis (LETM) (1), acute disseminated encephalomyelitis (ADEM) (1) and recurrent isolated optic neuritis (RION) (1). Typical NMO features (e.g., LETM) influenced the diagnosis more than features more consistent with MS (e.g., short TM). Agreement on the treatment of patients was higher (p o = 0.64) than that on the diagnosis with immunosuppression being the most common choice not only in patients with the diagnosis of NMO (98 %) but also in those indeterminate between NMO and MS (74 %). The diagnosis in AQP4-IgG-negative NMO/MS overlap syndromes is challenging and diverse. The classification of such patients currently requires new diagnostic categories, which incorporate lesser degrees of diagnostic confidence. Long-term follow-up may identify early features or biomarkers, which can more accurately distinguish the underlying disorder. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 109 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Korea, Republic of | 1 | <1% |
| Germany | 1 | <1% |
| South Africa | 1 | <1% |
| Brazil | 1 | <1% |
| Unknown | 105 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Other | 13 | 12% |
| Student > Ph. D. Student | 13 | 12% |
| Researcher | 11 | 10% |
| Student > Postgraduate | 10 | 9% |
| Student > Bachelor | 9 | 8% |
| Other | 35 | 32% |
| Unknown | 18 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 49 | 45% |
| Neuroscience | 14 | 13% |
| Nursing and Health Professions | 5 | 5% |
| Computer Science | 2 | 2% |
| Engineering | 2 | 2% |
| Other | 11 | 10% |
| Unknown | 26 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 July 2019.
All research outputs
#4,704,098
of 24,892,887 outputs
Outputs from Journal of Neurology
#1,156
of 4,883 outputs
Outputs of similar age
#60,183
of 291,316 outputs
Outputs of similar age from Journal of Neurology
#20
of 54 outputs
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