(Stroke. 2002;33:2053.)
© 2002 American Heart Association, Inc.
Original Contributions |
From the Department of Neurology, University of Essen, Essen, Germany (C.W., T.K., K.K., H.-C.D.); Division of Preventive Medicine, Brigham and Womens Hospital, Harvard Medical School, Boston Mass (T.K.); Department of Epidemiology, Harvard School of Public Health, Boston, Mass (T.K.); German Stroke Foundation, Gütersloh, Germany (M.W.); Department of Neurology, Klinikum Minden, Minden, Germany (O.B.); and Department of Neurology, Krankenhaus München-Harlaching, Munich, Germany (R.L.H.).
Correspondence to Tobias Kurth, MD, Brigham and Womens Hospital, Division of Preventive Medicine, 900 Commonwealth Ave E, Boston, MA 02215-1204. E-mail tkurth{at}rics.bwh.harvard.edu
| Abstract |
|---|
|
|
|---|
Methods We prospectively identified 4264 patients with acute ischemic stroke from 30 hospitals in Germany during a 1-year period between 1998 and 1999 and registered them in a common data bank. The patients were centrally followed up via telephone interview after 100 days and 1 year to assess various scales such as the Barthel Index (BI), modified Rankin Scale (MRS), extended Barthel Index (EBI), Short Form-36 Physical Functioning (SF-36 PF), and Center for Epidemiologic StudiesDepression short form (CES-D).
Results Outcome status could be assessed in 67.2% of patients 100 days after hospital admission. Of these, 13.9% had died, 53.7% had regained functional independence (BI <95), 46.3% had no or mild residual symptoms (MRS
1), and 44.6% had no higher cognitive deficits on the EBI. Of the patients who personally answered the follow-up questions, 67% had no major physical disability (SF-36 PF <60), and 32.9% reported symptoms classified as depression (CES-D
10). The high percentage of patients reaching the maximum score (ceiling effect) in the BI was less pronounced in the MRS and SF-36 PF. The predictive factors for dichotomized outcomes on each scale were similar for adverse functioning and disability but varied considerably for depression.
Conclusions To avoid ceiling effects in outcome distribution of patients treated in specialized stroke centers, the MRS and SF-36 PF instruments are preferable to the BI. Parametric use of the SF-36 PF could further improve outcome measurement by considering individual treatment effects.
Key Words: cerebral ischemia depression disability evaluation outcome stroke
| Introduction |
|---|
|
|
|---|
An understanding of functioning and disability after stroke is essential for selection of the appropriate instruments for intervention studies, given that the use of inappropriate instruments may obscure treatment effects. To gain a better understanding of what these outcome scales measure and to compare the efficacy of these scales in assessing outcome after ischemic stroke, we investigated the distribution, correlation, and prognostic variables of various end points in a large cohort of consecutive stroke patients.
| Materials and Methods |
|---|
|
|
|---|
According to the criteria established by the National Survey of Stroke,10 ischemic stroke was defined as a focal neurological deficit of presumably vascular origin lasting
24 hours and excluding primary hemorrhage on initial cerebral imaging. To ensure a representative documentation rate, this analysis includes only patients from the 30 hospitals that registered >50 patients with acute stroke during a 1-year registration period. If the registration period in a particular hospital was >1 year, those recruited during the last 12 months were considered. We also excluded patients with serious handicaps (MRS >3) before stroke to ensure that patients were functionally independent to a certain degree before the stroke event.2
Assessment of Outcomes
Using standardized questionnaires, treating physicians in the participating hospitals collected information that included age, sex, time of event and admission to the hospital, risk factors for stroke, prior stroke, prior medication, baseline neurological impairments as rated on the US National Institutes of Health Stroke Scale (NIHSS), functional independence before the event and after hospital admission as rated on the BI and MRS, acute therapy, medical and neurological complications, and length of stay in different wards in the documenting hospital. At discharge from the documenting hospital and at 100 days and 1 year after admission, the BI, MRS, SF-36 PF, extended BI (EBI), and Center for Epidemiologic StudiesDepression short form (CES-D) were administered. Local review boards approved the protocol of the Stroke Data Bank, and all patients gave informed consent. Risk factors for stroke11 and cardiovascular comorbidity were categorized a priori on the basis of clinically used cut points: arterial hypertension (history of elevated blood pressure >160/90 mm Hg at 2 independent readings before the stroke event or on current antihypertensive medication), diabetes mellitus (history of elevated fasting blood glucose >120 mg/dL at 2 independent readings before the stroke event, elevated HbA1c >7.5% at admission, or on current antidiabetic medication), and cardiovascular disease (newly diagnosed or history of myocardial infarction, ischemic heart disease, or peripheral arterial disease).
The NIHSS with 15 items (level of consciousness, answers to questions, responses to simple commands, deviation of gaze, hemianopia, facial palsy, arm and leg weakness of each side, limb ataxia, sensory loss, dysarthria, aphasia, inattention) measures the severity of neurological impairments.12 The single items range from 0 for no deficit to up to 4 (depending on the item) for complete impairment. The scores were quantified by local investigators who were familiar with the NIHSS from other clinical trials or the NIHSS training video.
The CES-D is a 10-item scale used to assess symptoms of depressed mood. Results range from 0 to 30, with a suggested cutoff score at
10 for depressive symptoms.13
The MRS14 is a global outcome rating scale ranging from 0 (no impairment) to 5 (bedridden, incontinent, requiring constant nursing care and attention) and 6 (fatal outcome). The BI15 evaluates 10 basic activities of self-care (feeding, grooming, dressing, toileting, bathing, and continence of bowel and bladder) and mobility (transferring, walking, stair climbing) on a total score from 0 (totally dependent) to 100 (totally independent) functioning.
The SF-36 PF16,17 is composed of 10 questions about mobility (moving a table, pushing a vacuum, lifting or carrying groceries, climbing several flights of stairs, climbing 1 flight of stairs, bending or stooping, walking >1 mile, walking several blocks, walking 1 block) and self-care (bathing or dressing oneself) on a summary score from 0 (maximum disability level) to 100. The SF-36 PF is a sensitive measure of mild functional losses relevant to independent living.7 Scores on the SF-36 PF have been normalized for age and sex in a German population.18
Since none of the above scales target deficits from the other domains of activity and participation as defined by the International Classification of Functioning, Disability and Health, we assessed 6 additional items from the German EBIcomprehension, verbal expression, social interaction, problem solving, orientation, and vision/attentionon a 3- to 5-point scale for each item, with 0 meaning no deficit. The EBI, a valid and reliable instrument, highly correlates to the Functional Independence Measure, has a comparable interrater reliability, and is sensitive to changes over time.19
After a final consistency check with the source data at each site, the questionnaires were sent to the data management center at the German Stroke Foundation, where they were rechecked by 2 physicians for completeness and plausibility and entered into the data bank by trained personnel. Questions about missing or implausible data were relayed to the treating clinicians. Data quality was further improved by monthly reports and clinical site visits. If a patient did not consent to submission of his or her personal data, the participating center forwarded only anonymous data to the data management center and, on bimonthly request, performed the follow-up interview on site. Otherwise, trained interviewers of the German Stroke Foundation performed interviews via telephone 100 days and 1 year after hospital admission to assess the BI, MRS, SF-36 PF, EBI, and CES-D. The NIHSS cannot be performed by telephone interview. If neither the Stroke Foundation interviewers nor the treating physician was able to contact the participant by telephone, he or she was sent a written questionnaire to assess the BI, MRS, SF-36 PF, EBI, and CES-D.
Because of limited funding, follow-up efforts could not be completed for all participants. Of the initial cohort, 2853 patients (67.2%) received a complete follow-up or had died after 100 days, 1.3% refused participation, 9.0% could be reached only outside of the follow-up window, and 22.5% were not contacted. After 1 year, 2539 patients (59.8%) could be followed up or had died.
Statistical Analysis
All statistical analyses were performed with SPSS version 9.0. Continuous variables are presented as mean and median or percentiles. Categorical variables are presented as percentages. Spearmans rank correlation coefficient (r) was used for comparisons between scales. To compare the variability over time of various scales, marked changes were defined as >20% difference on each of the scales. To compare the predictive variables for adverse outcome on various scales, we chose a priori cut points at the median of each scale that coincided with clinically meaningful end points: BI <95 versus BI
95; MRS >1 versus MRS
1; SF-36 PF <60 versus SF-36 PF
60 for functional dependence; and CES-D
10 versus CES-D <10 for depression. The following variables were chosen for inclusion as independent variables in the multiple logistic regression models after a previous literature search: age (continuous), sex, MRS before the event (continuous), diabetes mellitus, prior stroke, other cardiovascular disease, living alone, and NIHSS items (continuous). To test for univariate significance, we used
2 tests for categorical variables and Students t tests for continuous variables. After assessment of the univariate association between the potential predictors and the end-point variable, all significant variables were included in the model and retained if their resulting values were P
0.05. Any variable with P>0.05 was eliminated stepwise. To the remaining set of variables, every previously eliminated variable was again added and kept in the model if it fulfilled the same criteria. Finally, all 2-way interactions of the remaining variables were investigated and kept if P
0.05. For the final models, odds ratios (ORs) with 95% confidence intervals (CIs) for all parameters were calculated.
| Results |
|---|
|
|
|---|
|
|
Overall mortality after 100 days amounted to 13.9% and was higher for women (18.1%) than for men (11.0%). The BI after 100 days showed a marked ceiling effect (Figure 2), whereas the MRS had a more homogenous distribution across various degrees of functional status (Figure 3). The correlation between the 2 scales was r=0.82.
|
|
A broad distribution of the SF-36 PF scores was observed among patients with personal follow-up after 100 days, with 16% reaching the maximum level (Figure 4). On this scale, 63.4% of men and 61.7% of women reached a score equivalent to the 75th percentile of an age- and sex-matched German standard population. The SF-36 PF was highly correlated with the MRS (r=0.84) and moderately correlated with the BI (r=0.65). On the CES-D, 42% of women, 26% of men, and 33% overall scored
10, indicating depression (Figure 5). The respective correlation of the CES-D with SF-36 PF was r=0.58, with the MRS was r=0.54, and with the BI was r=0.38. On the EBI, most patients (55.4%) showed
1 deficits. The most common were related to orientation (37%) and problem solving (31%), whereas comprehension, verbal expression, social interaction, and vision/attention were reduced in
20% of patients.
|
|
In the interval between 100 days and 1 year after admission, 18.6% of patients improved on the BI, 58.5% remained unchanged, and 23% worsened or died. On the MRS, 22.6% of patients improved, 61.3% remained unchanged, and 16.3% worsened or died. The changes in functional independence on the BI and MRS are shown in Figure 6.
|
On the SF-36 PF, 27% of patients with personal follow-up remained unchanged between 100 days and 1 year, whereas 47.3% improved and 25.7% worsened. On the CES-D, only 15.7% remained unchanged, 49.1% improved, and 35.2% worsened. The changes in patients with personal follow-up on the SF-36 PF and CES-D are shown in Figure 7.
|
To assess the influence of predictive factors on various scales, 4 logistic regression models were fitted with the BI, MRS, SF-36 PF, and CES-D as dichotomous end-point variables. The independent variables yielded by each model, together with 95% CIs, are depicted in Table 2. Predictors for BI and MRS were largely identical except for prior stroke, left leg weakness, and living alone before stroke, which were marginally significant predictors for MRS >1 but not for BI <95. The most important predictors in both models were MRS before the stroke event, diabetes mellitus, and severity of either arm weakness. We identified diabetes mellitus, female sex, severity of right leg weakness, increasing MRS before the event, severity of left arm weakness, and increasing age as predictors for adverse outcome according to SF-36 PF <60 in patients with personal follow-up. With respect to depression, we identified living alone before the stroke, female sex, MRS before the stroke, sensory deficit, and cardiovascular disease as predictors for depression according to the CES-D (
10).
|
| Discussion |
|---|
|
|
|---|
During follow-up after 100 days and 1 year, the MRS was more sensitive than the BI to changes in disability. Because of its ceiling effect, the BI is less useful for assessing minor deficits at a high functional level and more useful for differentiating between patients with more severe disabilities. Predictive factors for both scales at the chosen cut points were similar, except for a stronger emphasis on upper limb weakness of the BI and on mobility and social support of the MRS. The MRS is more susceptible to depression, as can be inferred from its higher correlation with the CES-D. Moreover, patients with depression according to the CES-D scored worse on the MRS than patients with the same BI but without depression.
According to the CES-D, 32.9% of patients with personal follow-up after 100 days had symptoms of depression. This percentage is lower than the 40% reported in another follow-up study of stroke patients based on Diagnostic and Statistical Manual of Mental Disorders, 3rd edition, criteria,22 but is markedly higher than the 12% found in an elderly American population based on the CES-D.13 Because the CES-D cannot be assessed through proxy interview, data on this instrument are missing for a considerable number of patients who were unable to answer or could not be reached for follow-up in person. The main determinants of mood disorders are demographic, social, and endogenous factors present before and after the stroke event. This lowers the discrimination of the CES-D for stroke-related effects and caused high fluctuation between follow-up after 100 days and 1 year. Thus, the CES-D does not seem to be as suitable to detect treatment effects in outcome assessment after stroke as the other scales. In contrast, assessing more complex cerebral impairments like cognition, communication, and social competence may provide more objective information regarding the individual treatment-dependent outcome after stroke. In this study, which used 6 items from the EBI, deficits in orientation and problem solving were apparent in >30% of patients, and deficits of other cognitive functions were apparent in
20%. Such impairments present a substantial burden to the patient and his or her family or caregivers and thus should be considered in assessments of outcome after stroke. Clinical trials of neuroprotective agents in ischemic stroke have generally failed to detect significant treatment effects. This could be due to a lack of efficacy of the intervention. It could also be the result of inappropriate outcome measurements. For example, the U-shaped distribution of the BI in many studies makes it difficult to detect outcome effects if the shape of the association is not accounted for in the analysis. The MRS and SF-36 PF are better instruments for differentiating between changes in mild to moderate disability, especially after minor stroke. Although the SF-36 PF was designed as part of a larger, more comprehensive assessment tool and predominantly assesses limitations related to mobility, it has been validated and accepted as an independent instrument with sufficient test-retest reliability and thus may stand alone as a measure of subjective functioning and disability.13,23 This study supports the sensitivity of the SF-36 PF for stroke severity and shows that it is well correlated with other accepted outcome scales. Moreover, the SF-36 PF shows a broad distribution across the whole outcome range, which would enable its parametric use.24 Unlike the BI, the SF-36 PF is designed to assess a patients uniquely personal point of view and therefore shows higher fluctuations during follow-up.23,25 In our investigation, it also showed a moderate correlation with depression as measured by the CES-D. Because of the age- and sex-specific distribution of the SF-36 PF, this scale should be standardized with the general population as a reference. In a previous study, the mode of interview (face-to-face interview, self-completed questionnaire, or telephone interview) did not affect the reproducibility of the SF-36.25 Segal and Schall26 found an intraclass correlation coefficient of r=0.67 between patient and proxy assessment of the SF-36 PF, which is reasonably high for justifying proxy assessments. Thus, the SF-36 PF could be a useful end-point measurement in clinical trials for stroke patients own assessments of their functioning, even among those without moderate or severe disability. Moreover, its parametric use in outcome analysis could improve the efficiency of clinical trials to detect treatment effects.
This study has several strengths and limitations. Patients were included consecutively and, in a number of the participating hospitals, without application of selection criteria. Although the baseline characteristics are most likely representative of patients in specialized stroke care centers, the patients in this study were younger and had a significantly lower fatality rate than in comparable epidemiological studies.27,28 Although the NIHSS would have been the most objective method for assessing body functions after stroke, the large number of patients made it impossible to perform follow-up physical examinations of every patient. Another limitation is that we were not able to ensure complete follow-up of all patients. However, baseline characteristics were very similar among patients with and without follow-up after 100 days. On the contrary, the CES-D and SF-36 PF were exclusively assessed in patients who could be interviewed in person, which was impossible in aphasic or demented patients. Thus, the subgroup with complete assessment of these scales was significantly younger and had less severe neurological deficits at baseline compared with the initial cohort and therefore cannot be regarded as representative of all patients admitted with ischemic stroke.
In conclusion, data from this large prospective cohort study of stroke patients demonstrate the limitations of the BI for assessing outcome among patients with minimal functional limitations. At the same time, they show that the MRS and SF-36 PF are more sensitive for assessing mild to moderate disability and thereby might be better tools to differentiate between treatment effects. Because of its great fluctuations and dependence on various nonstroke-related factors, the CES-D seems unsuitable for use as an end-point variable in the design of future randomized trials. More appropriate selection of outcome measures in the design of intervention trials for ischemic stroke might help to reveal true benefits or harms that are currently obscured.
| Acknowledgments |
|---|
| Footnotes |
|---|
| Appendix 1 |
|---|
|
|
|---|
Received December 14, 2001; revision received February 19, 2002; accepted April 19, 2002.
| References |
|---|
|
|
|---|
2. Committee for Proprietary Medicinal Products. Points to Consider on Clinical Investigation of Medicinal Products for the Treatment of Acute Stroke. London, UK: The European Agency for the Evaluation of Medicinal Products; 2000. CPMP/EWP/560/98. http://www.emea.eu.int/pdfs/human/ewp/056098en.pdf.
3. Sulter G, Steen C, De Keyser J. Use of the Barthel Index and modified Rankin Scale in acute stroke trials. Stroke. 1999; 30: 15381541.
4. Roberts L, Counsell C. Assessment of clinical outcomes in acute stroke trials. Stroke. 1998; 29: 986991.
5. DOlhaberriague L, Litvan I, Mitsias P, Mansbach HH. A reappraisal of reliability and validity studies in stroke. Stroke. 1996; 27: 23312336.
6. Korner-Bitensky N, Wood-Dauphinee S, Siemiatycki J, Shapiro S, Becker R. Health-related information postdischarge: telephone versus face-to-face interviewing. Arch Phys Med Rehabil. 1994; 75: 12871296.[Medline] [Order article via Infotrieve]
7. Anderson C, Laubscher S, Burns R. Validation of the Short Form 36 (SF-36) health survey questionnaire among stroke patients. Stroke. 1996; 27: 18121816.
8. Duncan PW, Lai SM, Keighley J. Defining post-stroke recovery: implications for design and interpretation of drug trials. Neuropharmacology. 2000; 39: 835841.[CrossRef][Medline] [Order article via Infotrieve]
9. Herrmann N, Black SE, Lawrence J, Szekely C, Szalai JP. The Sunnybrook Stroke Study: a prospective study of depressive symptoms and functional outcome. Stroke. 1998; 29: 618624.
10. Walker AE, Robins M, Weinfeld FD. The National Survey of Stroke: clinical findings. Stroke. 1981; 12 (suppl): I13I44.[Medline] [Order article via Infotrieve]
11. DAgostino RB, Wolf PA, Belanger AJ, Kannel WB. Stroke risk profile: adjustment for antihypertensive medication: the Framingham study. Stroke. 1994; 25: 4043.[Abstract]
12. Lyden P, Brott T, Tilley B, Welch KM, Mascha EJ, Levine S, Haley EC, Grotta J, Marler J. Improved reliability of the NIH Stroke Scale using video training: NINDS TPA Stroke Study Group. Stroke. 1994; 25: 22202226.[Abstract]
13. Andresen EM, Malmgren JA, Carter WB, Patrick DL. Screening for depression in well older adults: evaluation of a short form of the CES-D (Center for Epidemiologic Studies Depression Scale). Am J Prev Med. 1994; 10: 7784.[Medline] [Order article via Infotrieve]
14. van Swieten JC, Koudstaal PJ, Visser MC, Schouten HJ, van Gijn J. Interobserver agreement for the assessment of handicap in stroke patients. Stroke. 1988; 19: 604607.
15. Mahony FI, Barthel DW. Functional evaluation: the Barthel Index. Md Med J. 1965; 14: 6165.
16. Ware JE Jr, Sherbourne CD. The MOS 36-item Short-Form Health Survey (SF-36), I: conceptual framework and item selection. Med Care. 1992; 30: 473483.[Medline] [Order article via Infotrieve]
17. Bullinger M. Assessment of health related quality of life with the SF-36 Health Survey. Rehabilitation (Stuttg). 1996; 35: 1727. quiz 2729.
18. Ellert U, Bellach BM. The SF-36 in the Federal Health Survey: description of a current normal sample. Gesundheitswesen. 1999; 61: S184S190.[Medline] [Order article via Infotrieve]
19. Prosiegel M, Böttger S, Schenk T, König N, Marolf M, Vaney C, Garner C, Yassouridis A. Der Erweiterte Barthel-Index (EBI): eine neue Skala zur Erfassung von Fähigkeitsstörungen bei neurologischen Patienten. Neurol Rehabil. 1996; 1: 713.
20. Tilley BC, Marler J, Geller NL, Lu M, Legler J, Brott T, Lyden P, Grotta J. Use of a global test for multiple outcomes in stroke trials with application to the National Institute of Neurological Disorders and Stroke t-PA Stroke Trial. Stroke. 1996; 27: 21362142.
21. Wolfe CD, Taub NA, Woodrow EJ, Burney PG. Assessment of scales of disability and handicap for stroke patients. Stroke. 1991; 22: 12421244.
22. Pohjasvaara T, Leppavuori A, Siira I, Vataja R, Kaste M, Erkinjuntti T. Frequency and clinical determinants of poststroke depression. Stroke. 1998; 29: 23112317.
23. Dorman P, Slattery J, Farrell B, Dennis M, Sandercock P. Qualitative comparison of the reliability of health status assessments with the EuroQol and SF-36 questionnaires after stroke: United Kingdom Collaborators in the International Stroke Trial. Stroke. 1998; 29: 6368.
24. Ware JE, Jr, Gandek B. Overview of the SF-36 Health Survey and the International Quality of Life Assessment (IQOLA) Project. J Clin Epidemiol. 1998; 51: 903912.[CrossRef][Medline] [Order article via Infotrieve]
25. Weinberger M, Oddone EZ, Samsa GP, Landsman PB. Are health-related quality-of-life measures affected by the mode of administration? J Clin Epidemiol. 1996; 49: 135140.[CrossRef][Medline] [Order article via Infotrieve]
26. Segal ME, Schall RR. Determining functional/health status and its relation to disability in stroke survivors. Stroke. 1994; 25: 23912397.[Abstract]
27. Kolominsky-Rabas PL, Sarti C, Heuschmann PU, Graf C, Siemonsen S, Neundoerfer B, Katalinic A, Lang E, Gassmann KG, von Stockert TR. A prospective community-based study of stroke in Germany: the Erlangen Stroke Project (ESPro): incidence and case fatality at 1, 3, and 12 months. Stroke. 1998; 29: 25012506.
28. Petty GW, Brown RD, Jr, Whisnant JP, Sicks JD, OFallon WM, Wiebers DO. Ischemic stroke: outcomes, patient mix, and practice variation for neurologists and generalists in a community. Neurology. 1998; 50: 16691678.
This article has been cited by other articles:
![]() |
K.-S. Hong and J. L. Saver Quantifying the Value of Stroke Disability Outcomes: WHO Global Burden of Disease Project Disability Weights for Each Level of the Modified Rankin Scale * Supplemental Mathematical Appendix Stroke, December 1, 2009; 40(12): 3828 - 3833. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. Torn, S. C. Cannegieter, W. L. E. M. Bollen, F. J. M. van der Meer, E. E. van der Wall, and F. R. Rosendaal Optimal Level of Oral Anticoagulant Therapy for the Prevention of Arterial Thrombosis in Patients With Mechanical Heart Valve Prostheses, Atrial Fibrillation, or Myocardial Infarction: A Prospective Study of 4202 Patients Arch Intern Med, July 13, 2009; 169(13): 1203 - 1209. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. N. Fink, C. M. Frampton, P. Lyden, K. R. Lees, and on behalf of the VISTA Investigators Does Hemispheric Lateralization Influence Functional and Cardiovascular Outcomes After Stroke?: An Analysis of Placebo-Treated Patients From Prospective Acute Stroke Trials Stroke, December 1, 2008; 39(12): 3335 - 3340. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. Dawson, J. S. Lees, T.-P. Chang, M. R. Walters, M. Ali, S. M. Davis, H.-C. Diener, K. R. Lees, and for the GAIN and VISTA Investigators Association Between Disability Measures and Healthcare Costs After Initial Treatment for Acute Stroke Stroke, June 1, 2007; 38(6): 1893 - 1898. [Abstract] [Full Text] [PDF] |
||||
![]() |
G. J. Hankey, J. Spiesser, Z. Hakimi, G. Bego, P. Carita, and S. Gabriel Rate, degree, and predictors of recovery from disability following ischemic stroke Neurology, May 8, 2007; 68(19): 1583 - 1587. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. L. Banks and C. A. Marotta Outcomes Validity and Reliability of the Modified Rankin Scale: Implications for Stroke Clinical Trials: A Literature Review and Synthesis Stroke, March 1, 2007; 38(3): 1091 - 1096. [Abstract] [Full Text] [PDF] |
||||
![]() |
K. R. Lees, A. Davalos, S. M. Davis, H.-C. Diener, J. Grotta, P. Lyden, A. Shuaib, T. Ashwood, H.-G. Hardemark, W. Wasiewski, et al. Additional Outcomes and Subgroup Analyses of NXY-059 for Acute Ischemic Stroke in the SAINT I Trial Stroke, December 1, 2006; 37(12): 2970 - 2978. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. Dawson and M. Walters New and emerging treatments for stroke Br. Med. Bull., November 7, 2006; (2006) ldl011v1. [Abstract] [Full Text] [PDF] |
||||
![]() |
D. A. Regier, R. Sunderji, L. D. Lynd, K. Gin, and C. A. Marra Cost-effectiveness of self-managed versus physician-managed oral anticoagulation therapy. Can. Med. Assoc. J., June 20, 2006; 174(13): 1847 - 1852. [Abstract] [Full Text] [PDF] |
||||
![]() |
E. R Skidmore, J. C Rogers, L. S Chandler, and M. B Holm Dynamic interactions between impairment and activity after stroke: examining the utility of decision analysis methods Clinical Rehabilitation, June 1, 2006; 20(6): 523 - 535. [Abstract] [PDF] |
||||
![]() |
K. R. Lees, J. A. Zivin, T. Ashwood, A. Davalos, S. M. Davis, H.-C. Diener, J. Grotta, P. Lyden, A. Shuaib, H.-G. Hardemark, et al. NXY-059 for Acute Ischemic Stroke N. Engl. J. Med., February 9, 2006; 354(6): 588 - 600. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. L. Hackett and C. S. Anderson Predictors of Depression after Stroke: A Systematic Review of Observational Studies Stroke, October 1, 2005; 36(10): 2296 - 2301. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. Uyttenboogaart, R. E. Stewart, P. C.A.J. Vroomen, J. De Keyser, and G.-J. Luijckx Optimizing Cutoff Scores for the Barthel Index and the Modified Rankin Scale for Defining Outcome in Acute Stroke Trials Stroke, September 1, 2005; 36(9): 1984 - 1987. [Abstract] [Full Text] [PDF] |
||||
![]() |
M. L. Hackett, C. Yapa, V. Parag, and C. S. Anderson Frequency of Depression After Stroke: A Systematic Review of Observational Studies Stroke, June 1, 2005; 36(6): 1330 - 1340. [Abstract] [Full Text] [PDF] |
||||
![]() |
S. Kwon, A. G. Hartzema, P. W. Duncan, and S. Min-Lai Disability Measures in Stroke: Relationship Among the Barthel Index, the Functional Independence Measure, and the Modified Rankin Scale Stroke, April 1, 2004; 35(4): 918 - 923. [Abstract] [Full Text] [PDF] |
||||
![]() |
J. Schrader, S. Luders, A. Kulschewski, J. Berger, W. Zidek, J. Treib, K. Einhaupl, H. C. Diener, and P. Dominiak The ACCESS Study: Evaluation of Acute Candesartan Cilexetil Therapy in Stroke Survivors Stroke, July 1, 2003; 34(7): 1699 - 1703. [Abstract] [Full Text] [PDF] |
||||
![]() |
E. M.J. Steultjens, J. Dekker, L. M. Bouter, J. C.M. van de Nes, E. H.C. Cup, C. H.M. van den Ende, F. Landi, and R. Bernabei Occupational Therapy for Stroke Patients: A Systematic Review * Occupational Therapy for Stroke Patients: When, Where, and How? Stroke, March 1, 2003; 34(3): 676 - 687. [Abstract] [Full Text] [PDF] |
||||
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Stroke Home | Subscriptions | Archives | Feedback | Authors | Help | AHA Journals Home | Search Copyright © 2002 American Heart Association, Inc. All rights reserved. Unauthorized use prohibited. |