Hostname: page-component-848d4c4894-x24gv Total loading time: 0 Render date: 2024-05-08T17:13:36.828Z Has data issue: false hasContentIssue false
  • English
  • Français

Predicting Final Disposition after using the Orpington Prognostic Scor

Published online by Cambridge University Press:  02 December 2014

C.J. Wright ,
L.C. Swinton ,
T.L. Green  and
M.D. Hill
C.J. Wright
Affiliation:
Calgary Stroke Program, Department of Clinical Neurosciences, University of Calgary, and Rehabilitation Services (Neurosciences Team-FMC), Calgary Health Region, Calgary, AB, Canada
L.C. Swinton
Affiliation:
Calgary Stroke Program, Department of Clinical Neurosciences, University of Calgary, and Rehabilitation Services (Neurosciences Team-FMC), Calgary Health Region, Calgary, AB, Canada
T.L. Green
Affiliation:
Calgary Stroke Program, Department of Clinical Neurosciences, University of Calgary, and Rehabilitation Services (Neurosciences Team-FMC), Calgary Health Region, Calgary, AB, Canada
M.D. Hill
Affiliation:
Calgary Stroke Program, Department of Clinical Neurosciences, University of Calgary, and Rehabilitation Services (Neurosciences Team-FMC), Calgary Health Region, Calgary, AB, Canada
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
Background:

Prediction of outcome after stroke is important for triage decisions, prognostic estimates for family and for appropriate resource utilization. Prognostication must be timely and simply applied. Several scales have shown good prognostic value. In Calgary, the Orpington Prognostic Score (OPS) has been used to predict outcome as an aid to rehabilitation triage. However, the OPS has not been assessed at one week for predictive capability.

Methods:

Among patients admitted to a sub-acute stroke unit, OPS from the first week were examined to determine if any correlation existed between final disposition after rehabilitation and first week score. The predictive validity of the OPS at one week was compared to National Institute of Health Stroke Scale (NIHSS) score at 24 hours using logistic regression and receiver operator characteristics analysis. The primary outcome was final disposition after discharge from the stroke unit if the patient went directly home, or died, or from the inpatient rehabilitation unit.

Results:

The first week OPS was highly predictive of final disposition. However, no major advantage in using the first week OPS was observed when compared to 24h NIHSS score. Both scales were equally predictive of final disposition of stroke patients, post rehabilitation.

Conclusion:

The first week OPS can be used to predict final outcome. The NIHSS at 24h provides the same prognostic information.

Type
Other
Information
Canadian Journal of Neurological Sciences , Volume 31 , Issue 4 , November 2004 , pp. 494 - 498
Copyright
Copyright © The Canadian Journal of Neurological 2004

References

1. Loewen, SC, Anderson, B. Predictors of stroke outcome using objective measurement scales. Stroke 1990:78-81.Google Scholar
2. Samuelsson, M, Soderfeldt, B, Olsson, GB. Functional outcome in patients with lacunar infarction. Stroke 1996:842-846.Google Scholar
3. Chang, KC, Tseng, MC, Weng, HH, et al. Prediction of length of stay of first-ever ischemic stroke. Stroke 2002:2670-2674.Google Scholar
4. Muir, KW, Weir, CJ, Murray, GD, Povey, C, Lees, KR. Comparison of neurological scales and scoring systems for acute stroke prognosis. Stroke 1996:1817-1820.Google Scholar
5. Prescott, RJ, Garraway, WM, Akhtar, AJ. Predicting functional outcome following acute stroke using a standard clinical examination. Stroke 1982:641-647.Google Scholar
6. Langton Hewer, R. Rehabilitation after stroke. Q J Med 1990:659-674.Google Scholar
7. De Haan, R, Horn, J, Limburg, M, Van Der Meulen, J, Bossuyt, P. A comparison of five stroke scales with measures of disability, handicap, and quality of life. Stroke 1993:1178-1181.Google Scholar
8. De Haan, R, Limburg, M. The relationship between impairment and functional health scales in the outcome of stroke. Cerebrovasc Dis 1994:19-23.Google Scholar
9. Kalra, L, Crome, P. The role of prognostic scores in targeting stroke rehabilitation in elderly patients. J Am Geriatric Soc 1993:396–400.Google Scholar
10. Lai, S, Duncan, PW, Keighley, J. Prediction of functional outcome after stroke. Stroke 1998:1838–1842.Google Scholar
11. Studenski, SA, Wallace, D, Duncan, PW, Rymer, M, Lai, SM. Predicting stroke recovery: three- and six-month rates of patient-centered functional outcomes based on the Orpington Prognostic Scale. J Am Geriatric Soc 2001:308–312.Google Scholar
12. Kalra, L, Dale, P, Crome, P. Evaluation of a clinical score for prognostic stratification of elderly stroke patients. Age Ageing 1994:492-498.Google Scholar
13. Lyden, P, Brott, T, Tilley, B, et al. Improved reliability of the NIH Stroke Scale using video training. NINDS TPA Stroke Study Group. Stroke 1994;25:2220–2226.Google Scholar
14. Fink, JN, Selim, MH, Kumar, S, et al. Is the association of National Institutes of Health Stroke Scale scores and acute magnetic resonance imaging stroke volume equal for patients with right-and left-hemisphere ischemic stroke? Stroke 2002;33:954–958.Google Scholar
15. Woo, D, Broderick, JP, Kothari, RU, et al. Does the National Institutes of Health Stroke Scale favor left hemisphere strokes? NINDS t-PA Stroke Study Group. Stroke 1999;30:2355–2359.Google Scholar
16. Dewey, HM, Donnan, GA, Freeman, EJ, et al. Interrater reliability of the National Institutes of Health Stroke Scale: rating by neurologists and nurses in a community-based stroke incidence study. Cerebrovasc Dis 1999;9:323–327.Google Scholar
17. Goldstein, LB, Samsa, GP. Reliability of the National Institutes of Health Stroke Scale. Extension to non-neurologists in the context of a clinical trial. Stroke 1997;28:307–310.CrossRefGoogle ScholarPubMed
18. Schlegel, D, Kolb, SJ, Luciano, JM, et al. Utility of NIH Stroke Scale as a predictor of hospital disposition. Stroke 2003:134-137.Google Scholar
19. Johnston, KC, Connors, AF Jr, Wagner, DP, et al. A predictive risk model for outcomes of ischemic stroke. Stroke 2000;31:448–455.Google Scholar