The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
The ALSFRSr predicts survival time in an ALS clinic population
Abstract
OBJECTIVE: To determine whether the Amyotrophic Lateral Sclerosis Functional Rating Scale-revised (ALSFRSr), a predictor of survival time in ALS clinical trials, predicts survival time in an ALS clinic population. METHODS: The authors prospectively evaluated 267 consecutive patients with ALS at first visit to an ALS clinic using the ALSFRSr and pulmonary function testing. The association of ALSFRSr score at baseline with death or tracheostomy in ALS was examined using Cox proportional hazards models, adjusting for age at baseline, sex, and symptom duration. RESULTS: Of 267 patients with ALS, 103 (39%) reached the endpoint, defined as either death (79 patients) or tracheostomy (24 patients), during a mean follow-up of 1.0 +/- 0.7 years. Among the 103 patients who reached the endpoint during follow-up, 77 (75%) had a baseline ALSFRSr score of less than 38 (the median baseline score of all patients), compared to 53 of 164 (32%) who remained alive without tracheostomy. Patients with a total ALSFRSr score below the median had a 4.4-fold increased risk of death or tracheostomy compared to those who scored above the median (HR: 4.38, 95% CI: 2.79 to 6.86, p < 0.001). Both the total ALSFRSr score at baseline (HR: 0.94, 95% CI: 0.91 to 0.98, p < 0.001) and forced vital capacity at baseline (HR: 0.99, 95% CI: 0.98 to 1.00, p = 0.02) were associated with death or tracheostomy when included in the same Cox model. CONCLUSIONS: In an ALS clinic population, the total Amyotrophic Lateral Sclerosis Functional Rating Scale-revised score at baseline is a strong predictor of death or tracheostomy independently of forced vital capacity and after adjustment for age at baseline, sex, and symptom duration.
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.
Integrity signals
Registry
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.
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
Cites
Cedarbaum, J. M., Stambler, N., Malta, E., Fuller, C., Hilt, D., Thurmond, B., & Nakanishi, A. (1999) · Journal of the Neurological Sciences · doi:10.1016/s0022-510x(99)00210-5 · Cited by 3,307
Early symptom progression rate is related to ALS outcome: A prospective population-based study
Chiò, A., Mora, G., Leone, M., Mazzini, L., Cocito, D., Giordana, M. T., Bottacchi, E., & Mutani, R. (2002) · Neurology · doi:10.1212/wnl.59.1.99 · Cited by 266
Cited by
Prognostic factors in ALS: A critical review
Chiò, A., Logroscino, G., Hardiman, O., Swingler, R., Mitchell, D., Beghi, E., Traynor, B. G., & On Behalf of the Eurals Consortium (2009) · Amyotrophic Lateral Sclerosis · doi:10.3109/17482960802566824 · Cited by 1,172
Clinical and radiographic spectrum of pathologically confirmed tumefactive multiple sclerosis
Lucchinetti, C. F., Gavrilova, R. H., Metz, I., Parisi, J. E., Scheithauer, B. W., Weigand, S., Thomsen, K., Mandrekar, J., Altintas, A., Erickson, B. J., et al. (2008) · Brain · doi:10.1093/brain/awn098 · Cited by 493
Czaplinski, A. (2005) · Journal of Neurology, Neurosurgery & Psychiatry · doi:10.1136/jnnp.2005.072660 · Cited by 273
ALSFRS-R score and its ratio: A useful predictor for ALS-progression
Kollewe, K., Mauss, U., Krampfl, K., Petri, S., Dengler, R., & Mohammadi, B. (2008) · Journal of the Neurological Sciences · doi:10.1016/j.jns.2008.07.016 · Cited by 253
Study of 962 patients indicates progressive muscular atrophy is a form of ALS
Kim, W. K., Liu, X., Sandner, J., Pasmantier, M., Andrews, J., Rowland, L. P., & Mitsumoto, H. (2009) · Neurology · doi:10.1212/wnl.0b013e3181c1dea3 · Cited by 217
Self-citation
Metadata
- Authors
- Kaufmann, P., Levy, G., Thompson, J. L. P., DelBene, M. L., Battista, V., Gordon, P. H., Rowland, L. P., Levin, B., & Mitsumoto, H.
- Venue
- Neurology
- Published
- 2005-01-11
- Volume
- 64
- Issue
- 1
- Pages
- 38-43
- ISSN
- 0028-3878 (ISSN-L)
- 1526-632X
- OpenAlex
- W1998437790
- Cited by
- 243
- References
- 2
- FWCI
- 11.09
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: The ALSFRSr predicts survival time in an ALS clinic population. https://app.cochat.ai/papers/10.1212/01.wnl.0000148648.38313.64
- The paper
- Kaufmann, P., Levy, G., Thompson, J. L. P., DelBene, M. L., Battista, V., Gordon, P. H., Rowland, L. P., Levin, B., & Mitsumoto, H. (2005). The ALSFRSr predicts survival time in an ALS clinic population. Neurology. https://doi.org/10.1212/01.wnl.0000148648.38313.64
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.