Is there a relation between neuropsychologic variables and quality of lifeafter stroke?

Citation
Jb. Hochstenbach et al., Is there a relation between neuropsychologic variables and quality of lifeafter stroke?, ARCH PHYS M, 82(10), 2001, pp. 1360-1366
Citations number
58
Categorie Soggetti
Ortopedics, Rehabilitation & Sport Medicine
Journal title
ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION
ISSN journal
00039993 → ACNP
Volume
82
Issue
10
Year of publication
2001
Pages
1360 - 1366
Database
ISI
SICI code
0003-9993(200110)82:10<1360:ITARBN>2.0.ZU;2-P
Abstract
Objectives: To describe the quality of life (QOL) of stroke patients and to distill neuropsychologic predictors for poor QOL. Design: A cohort study in which patients were neuropsychologically assessed at a mean of 72.2 days after stroke, with follow-up at a mean of 9.8 month s after stroke. Setting: Research department of a rehabilitation center. Patients: A consecutive sample of 164 stroke patients (mean age, 55.2yr) re cruited from a university hospital, a regional hospital, and a rehabilitati on center. Interventions: Not applicable. Main Outcome Measures: Orientation, memory, attention and concentration, vi suospatial and visuoconstructive functions, language, and arithmetic skills were assessed with neuropsychologic tests. QOL was assessed with the Sickn ess Impact Profile (SIP). Results: An overall mean SIP score standard deviation of 20 +/- 11 showed t hat stroke has a high impact on everyday functioning. Further analyses indi cated that QOL is related in particular to tests measuring spatiotemporal a nd/or sequential aspects of behavior. Forward/backward stepwise regression analysis (n = 106) showed that poor QOL was more likely if patients had a p oor result on the Trailmaking Test (TMT) B and/or were women. Conclusion: The predictive value of the TMT is most effective and very usef ul because the TMT is a short and economical procedure. However, the gender -related aspects of recovery deserve more attention, as does the possible b ias that can be caused by the composition of a measurement. Further researc h is needed to refine predictive models that are needed to facilitate the d evelopment of more adequate, individual rehabilitation programs.