618
Views
65
CrossRef citations to date
0
Altmetric
Original Article

Use of respiratory function tests to predict survival in amyotrophic lateral sclerosis

, , , , , , & show all
Pages 194-202 | Received 04 Apr 2009, Accepted 15 Apr 2009, Published online: 26 Feb 2010
 

Abstract

Respiratory function tests (RFTs) are commonly used as a measure of progression in ALS. This study assessed the ability of various RFTs to predict survival in ALS patients. Subjects with ALS had one or more measurements of seated and supine FVC, maximal inspiratory pressure (MIP) and maximal expiratory pressure (MEP). Kaplan-Meier (KM) analysis was used to determine whether patients with abnormal RFTs had shorter survival than those with normal RFTs. The sensitivity and specificity of RFTs as predictors of two-year survival were calculated from receiver operating characteristic (ROC) curves. With KM analysis, subjects with abnormal values of seated FVC, supine FVC, MIP and MEP had significantly reduced survival compared to subjects with normal values. With ROC curves, a normal supine FVC was highly predictive for two-year survival and had superior sensitivity over seated FVC. Slower rates of decline in seated or supine FVC were strong predictors of two-year survival. Our study demonstrates that respiratory function measurements are useful to predict survival in ALS patients. We show that measurements of FVC in the supine position are worth including in the assessment of respiratory function in ALS.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 478.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.