Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 357

The DOI matches its Crossref record.

Reliability and validity of the CMT neuropathy score as a measure of disability

Shy, M. E., Blake, J., Krajewski, K., Fuerst, D. R., Laura, M., Hahn, A. F., Li, J., Lewis, R. A., Reilly, M.·2005·Neurology

Abstract

OBJECTIVE: To determine the validity and reliability of the Charcot-Marie-Tooth disease (CMT) neuropathy score (CMTNS) in patients with inherited neuropathy. BACKGROUND: Natural history studies and potential treatment trials for patients with various forms of CMT are limited by the lack of quantitative methodologies to monitor disease progression. Most cases of CMT can be considered length-dependent axonal neuropathies because disability for even the demyelinating forms correlates with length-dependent axonal degeneration. The total neuropathy score (TNS) is a validated composite measure of disability in length-dependent axonal neuropathies but is weighted toward predominantly sensory neuropathies. Thus, the authors have devised a CMTNS, modified from the TNS, to provide a single measure to quantify CMT disability. METHODS: The authors measured inter- and intrainvestigator reliability of the CMTNS and performed a validation of the score with the Neuropathy Impairment Score (NIS), patient self-assessment scores, an ambulation index, and other measures of disability. RESULTS: Inter- and intrainvestigator reliability was more than 95% in the 60 patients evaluated. Patients could be divided into mild (CMTNS, < or =10), moderate (CMTNS, 11 to 20), and severe (CMTNS, > or =21) categories and demonstrated excellent correlations among all measures of disability. CONCLUSION: The Charcot-Marie-Tooth disease (CMT) neuropathy score is a validated measure of length-dependent axonal and demyelinating CMT disability and can be investigated as an end point for longitudinal studies and clinical trials of CMT.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1212/01.wnl.0000156517.00615.a3

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

Metadata

Authors
Shy, M. E., Blake, J., Krajewski, K., Fuerst, D. R., Laura, M., Hahn, A. F., Li, J., Lewis, R. A., & Reilly, M.
Venue
Neurology
Published
2005-04-12
Volume
64
Issue
7
Pages
1209-1214
ISSN
  • 0028-3878 (ISSN-L)
  • 1526-632X
OpenAlex
W4302871475
Cited by
357
References
0
FWCI
5.09
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.