The berg balance scale as a predictor of length of stay and discharge destination in an acute stroke rehabilitation setting

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The Berg Balance Scale as a Predictor of Length of Stay and Discharge Destination in an Acute Stroke Rehabilitation Setting Joy XM. Wee, MD, Stephen D. Bagg, MD, Anita Palepu, MD ABSTRACT. Wee JYM, Bagg SD, Palepu A. The Berg Balance Scale as a predictor of length of stay and discharge destination in an acute stroke rehabilitation setting. Arch Phys Med Rehabil 1999;80:448-52. Objective: To examine the utility of the Berg Balance Scale (BBS) in predicting length of stay and discharge destination for patients admitted to a stroke rehabilitation unit. Design: Retrospective study. Setting: Regional tertiary inpatient stroke rehabilitation unit. Patients: One hundred twenty-eight of 141 patients admitted consecutively between January 1, 1995, and March 31, 1996. Main Outcome Measures: Length of stay and discharge destination. Results: Admission BBS scores and Functional Independence Measure scores correlated with length of stay (r = -0.6 and -0.5, respectively, controlling for age). Logistic regression revealed that the following were independent predictors of being discharged home rather than to an institution (adjusted odds ratio, 95% confidence interval): .admission BBS (1.09, 1.04-1.13), age (.89, .83-.95), and presence of family support (11.7,3.1-44.3). Conclusions: Measuring the BBS scores of patients upon admission to an acute stroke rehabilitation unit may assist in approximating length of stay and predicting eventual discharge destination. 0 1999 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation

I

NVESTIGATORS HAVE TRIED to predict functional recovery after stroke and have examined variables such as admission disability, urinary continence, degree of motor impairment, age, orientation and level of consciousness, balance, and perceived social support1 Balance has been found to be a predictor of length of stay (LOS)2 whereas gait status and social supports are predictors of discharge disposition.2 These relationships, however, have not been clearly quantified. Therefore, the search for accurate and practical prediction models continues. Studies have shown that balance is important for locomotor

From Queen’s University, Department of Rehabilitation Medicine, St. Mary’s of the Lake Hospital, Kingston, Ontario, Canada. Dr. Wee is currently affiliated with Holy Family Hospital, Vancouver, and the Division of Physical Medicine and Rehabilitation, Department of Medicine, University of British Columbia. Dr. Palepu is currently affiliated with the Division of General Internal Medicine, Department of Medicine, University of British Columbia. Submitted for publication May 8, 1998. Accepted in revised form September 28, 1998. Presented in part at the Annual Meeting of the Royal College of Physicians and Surgeons of Canada, September 27,1997, Vancouver, British Columbia, Canada. No commercial party having a direct financial interest in the results of the research supporting this article has or will confer a benefit upon the authors or upon any organization with which the authors are associated. Reprint requests to Dr. Joy Y.M. Wee, Holy Family Hospital, 7801 Argyle Street, Vancouver, B.C., Canada, V5P 3L6. 0 1999 by the American Congress of Rehabilitation Medicine and the American Academy of Physical Medicine and Rehabilitation 0003-9993/99/8004-5019$3.00/O

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control and, therefore, functional abilities, because good trunk control is important for many activities of daily living (ADL).3-5 A high correlation has been found between static balance and locomotor function and functional abilities after a stroke.6,7 There has not been an agreement among rehabilitation health care personnel as to which balance scale should be used in predicting outcomes after stroke. The scale developed by Katherine Bergs measures not only sitting balance but also higher-level balance activities such as standing on one leg and stepping. The Berg Balance Scale (BBS) is a 56-point scale measuring balance. It has been shown to have strong internal consistency and high interrater and intrarater reliability in patients with acute stroke.g The BBS is appropriate for use in acute stroke rehabilitation, as most patients do not obtain maximum scoreson admission to stroke rehabilitation units (SRUs), unlike some other patient populations. For example, patients undergoing musculoskeletal rehabilitation usually do not have significant impairments in truncal control despite absent or poorly functioning limbs because balance is usually not affected; these patients would generally achieve high scores if scored with the BBS. If a patient population generally scores high initially on the BBS, the scale’s predictive ability would not be strong, as compared with a patient population that has a wide range of values for admission BBS scores (Adm BBS). The ability of balance and gait status to predict overall outcomes such as LOS and discharge destination (DD) is recognized.2,10Therefore, use of a balance scale, such as the BBS, applied to patients admitted to an SRU could be proposed to guide clinicians in predicting LOS and DD. This scale has been used to assesspatients at our institution on admission for at least 2 years, allowing for a retrospective review of its prognostic utility. No other studies have examined the ability of the BBS to predict overall outcomes such as rehabilitation unit LOS and DD. METHODS Subjects Charts of 141 patients admitted consecutively to our hospital between January 1, 1995, and March 3 1, 1996, were reviewed. This regional hospital has a tertiary SRU with a catchment area in Ontario, east of Toronto and south of Ottawa. Ethical approval was obtained by the hospital’s Ethics Committee. All patients with acute strokes, hemorrhagic or nonhemorrhagic, were included. Thirteen patients were excluded for the following reasons: severe cognitive impairment precluding participation in rehabilitation therapy; brain tumors or carcinoma as the main diagnosis; long-standing (>6 months) strokes; death; and incomplete information. Therefore, information from 128 patients is presented. Procedures

Zndependent variables. Independent variables abstracted from the medical record included age, gender, time from stroke to SRU admission, and presence or absence of family supports (dichotomous value). Family support was deemed available if

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there was any relative or caregiver able and willing to live with the subject to assist with ADL after discharge from the SRU. Scores collected included the Adm BBS, admission Functional Independence Measure (FIM) scores (AdmFIM), and Motor FIM-5 subscoresof transfers and locomotion. These two scales (Adm BBS and Adm FIM) have been recorded for patients at this institution for the previous 2 years. The BBS was completed by the treating physiotherapist, and the FIM was scored by the treating physiotherapist, occupational therapist, speech pathologist, and nurse. These assessments were carried out within 3 days of admission to the SRU. Berg Balance Scale. The 56-point BBS grades 14 tasks, from 0 to 4 (0 indicating inability to complete task entirely). Tasks include balance activities such as sitting with arms folded, rising, standing, transferring between one surface and another, reaching forward in standing, picking up objects from the floor, turning around in a full circle, and standing on one leg. Scoring is based on ability to meet specific time and distance requirements. The test is easily administered, using a ruler and stopwatch, and takes approximately 10 minutes to complete. It is a scale targeted for elderly and rehabilitation patients that has been validated in the early poststroke period.9 Reliability in these populations has also been shown, with intrarater reliability being .97 and interrater reliability .9K9 Functiorzal Independence Measure. The FIM has been used to predict outcomes.” The FIM is a scale that is intended to measure level of disability; it is divided into six areas of ability, and further subdivided into 18 subcategories, each scored out of 7 (1 indicating total dependence). The areas measured are basic self-care or ADL, sphincter control, transfers, locomotion, communication, and social cognition. The minimum and maximum FIM scores possible are 18 and 126, respectively. There are specific scoring guidelines, including measurement within 72 hours of admission or discharge. It is a scale widely used in the rehabilitation population, and has been found to have good reliability. I2 The FIM has been used as a prognostic tool when applied at admission,13 but is more comprehensive than the BBS, measuring much more than balance. As admission FIM (Adm FIM) is a recognized prognostic factor,‘4,15 our study also compared the predictive value of the BBS with that of the FIM and Motor FIM-5 subscores (locomotion and transfers), with respect to LOS and DD (in particular, discharge to home as opposed to facilities). Motor FZM-5 scores. FIM subscores have been used for various reasons.16They include only scores obtained within selected domains of the FIM. In this study, the categories of locomotion and transfers of the FIM most closely reflect what is measured in the BBS. Therefore, scores in these categories were combined to form the Motor FIM-5 subscores. Locomotion includes the ability to negotiate stairs and either ambulate or use a wheelchair. Transfers include moving between bed and chair, chair and toilet, and chair and tub or shower. For each of these activities, complete independence would yield a score of 7 of a possible 7, modified independence 6, and set-up or supervision 5. Minimal (25%), moderate (50%), and maximal (75%) assistance required would yield scores of 4, 3, and 2, respectively, and total dependence a score of 1. Therefore, the Motor FIM-5 score could range from 5 to 35. Dependent variables. Dependent variables obtained were LOS and DD. LOS was measured as the number of days between admission to and discharge from the SRU. Four possible DDs were identified: private dwellings; residential facilities, where individuals were expected to be independent in basic ADL; nursing homes, in which assistance in basic self-care was provided; and hospital wards. The fourth category

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included chronic-care hospital wards, where almost total care was provided, and acute hospital wards, for unexpected acute medical emergencies. Discharge FIM scores were also collected as indicators of patient level of function at discharge from the SRU. Statistical Analysis Raw FIM scoreswere used. To compare proportions, x2 tests, and the Fisher Exact test, where cell sizes were small, were used; analyses of variance were used to compare means among groups. T testing was used to look for any differences between men and women with respect to age, Adm BBS, Adm FIM, LOS, and DD. The LOS was log-transformed (In LOS) due to the skewness of the LOS distribution. General linear models were used to examine the relationship between the LOS and Adm BBS as well as between LOS and Adm FIM, adjusting for age. Similarly, the relation between time from stroke onset to SRU admission and LOS was examined. Unconditional logistic regression was used to assessthe independent effect of the Adm BBS and family support on DD, adjusting for age. Possible influences that DD could have had upon LOS were examined. Similarly, the availability of family support and its influence on DD were explored. Analyses were performed using SAS statistical software (version 6.11). RESULTS Sample Characteristics Of the 141 subjects admitted to the SRU, 13 were excluded (three had severe cognitive impairment; four had a brain tumor or carcinoma; two had nonacute stroke; two had died; and two had incomplete information). Patient age ranged from 39 to 96 years, with a mean of 69.9 years (SD = 11.6). Seventy-nine were men and 49 were women. Sixty-two subjects had right hemispheric strokes, 58 had left hemispheric strokes, and eight had bilateral strokes. There were no significant differences between the men and women with respect to age, admission BBS/FIM scores, LOS, or DD. The average number of days from stroke onset to SRU admission was 28.7 days (SD = 26.5). The time from stroke onset to SRU admission was not found to be related to LOS or DD. Both Adm BBS and Adm FIM scores were normally distributed. Adm BBS ranged from 0156 to 56156 and Adm FIM scores ranged from 231126 to 1241126. A significant positive correlation between Adm BBS and Adm FIM scores was observed (Y = .76, p < ,001). Length of Stay The in-hospital LOS ranged from 3 to 328 days (interquartile range 29 to 66 days). Clear negative correlations between Adm BBS and Adm FIM scores with In LOS are shown in the regression equations obtained (table l), controlling for age. Admission Motor FIM-5 subscoresfor those subjects in which information was available (n = 124) also correlated with In LOS (not controlled for age). Motor FIM-5 correlated with LOS better than did the total Adm FIM scores, whereas the Adm BBS scoreshad the strongest correlation with LOS. LOS was also significantly longer for those discharged to Table

1: Logistic

Regression

Equation rz

In LOS

= -.023(Adm

BBS)

~ .006(age)

+ 4.75

In LOS In LOS

= -.Oll(Adm = -.044(Motor

FIM) - .002(age) FIM-5) + 4.55

+ 4.84

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.36 .21 .33

P <.OOl <.OOl <.OOl

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BERG

Table Discharge N(%)

* Indicates group used for gender, nonsignificance.

2: Characteristics

Destination

Age: mean t SE Gender: n (%) Men Women Hemisphere: n (%) Right Left Bilateral Adm BBS: mean t SE Adm FIM: mean i- SE Family support: n (%) D/C FIM: mean ir SE

BALANCE

SCALE

AS PREDICTOR

of Subjects

Nursing

98 (77) 67.3 + l.l*

9 (7) 79.8 t 3.6

13 (IO) 78.8 2 3.0”

63 (64.3) 35 (35.7) 46 (46.9) 46 (46.9) 6 (6.1) 28.5 + 1.7* 88.5 + 2.4* 82 (83.7)* 109.1 t 2.1*

was significantly greater hemisphere, and family

1 (11.1)" 8 (88.9)*

5 (55.6) 3 (33.3) l(11.1) 21.8 t 5.7 80.3 ? 8.0 2 (22.2) 97.7 t 6.9

Rehabil

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Hospital

p Value

8 (‘3 75 + 3.8

,001

9 (69.2)

6 (75)

,001

4 (30.8)

2 (25)

6 (46.2) 7 (53.9) 0 (0) 7.9 t 4.8s 56.1 I: 6.7* 7 (53.9)X 73.1 ir 5.8”

than or less than the other groups support comparisons; general

Family Support and Discharge Destination There is an interesting observation in the small group of individuals discharged to residential facilities with regard to gender, in that there were many more women than men discharged to a residential facility (p = .OOl, 89.9% women). The disability level is similar for those discharged home and those discharged to residential settings, as demonstrated by the average discharge FIM scores (DC FIM), shown in table 2. A key significant difference between the patients returning home compared to a residential setting appears to be the presence of family supports (85% vs 22%). Figure 1 shows that patients returning home have a higher level of functioning in general than those discharged elsewhere, particularly those going home Med

Destination

Residential

Discharge Destination Regarding DD, 98 patients were discharged home; 30 were discharged to institutions, including residential homes (n = 9), nursing homes (n = 13) chronic-care hospital wards, and acute hospital wards (n = 8). Overall, gender and hemispheric localization of stroke were not significantly associated with DD. We found significant differences in Adm BBS and FIM scoresfor patients discharged to residential and nursing facilities, and hospital wards (acute wards if medically unstable, and chronic wards if care requirements exceed that available at nursing facilities) compared to those discharged home (10.4 -t 13 SD vs 28.3 2 19 for Adm BBS, and 57.1 2 27 vs 88.4 t 25 for Adm FIM; p < .OOl). There were also significant differences in mean age between those discharged home and those discharged to institutions (67.6 + 11 years vs 77.5 2 8 years;p < .OOl). In general, those discharged home were younger and had higher Adm BBS and FIM scores. Most (>75%) of those discharged to facilities had Adm BBS scores of <20. Only 59% of patients with Adm BBS scores of 520 were discharged home, while 93% of patients with Adm BBS scores of >20 went home.

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nursing facilities as compared with those discharged home (91.4 days, SE = 9.7 and 49.5 days, SE = 3.4, respectively, p < .OOl). Most of the prolonged duration was due to long waiting periods for nursing homes in the Kingston area (nine patients, average wait 75.2 days from completion of rehabilitation program: two transferred immediately, seven with average wait of 96.7 days, range 7 days to 9 months). The other four patients discharged to nursing homes went to areas outside Kingston, with shorter waiting periods.

Arch

Based

OF OUTCOMES,

5 (62.5)

NS

2 (25) 1 (12.5) 1.4 + 6.1 35.3 t 8.5 6 (75) 63.9 i 7.4

.OOOl .OOOl .Ol .OOOl

indicated on pairwise comparisons (p < .05). Fisher Exact test linear models for age and measurement data. NS indicates

without family support. It also shows that some significantly disabled patients are able to return home if family support is available. Table 3 shows the independent predictors of being discharged home. The contribution of family support far outweighs the contribution of age and Adm BBS, as can be gleaned from the odds ratio. The presence of family support gives one an adjusted odds ratio of 4.91 of going home rather than to an institution, when compared with subjects without family support, controlling for age and Adm BBS. DISCUSSION This study demonstrates that the admission BBS score is moderately correlated with LOS and DD, with significant differences found in admission BBS scores between patients who were discharged home and those discharged elsewhere. The admission BBS scores in our study were highly correlated with admission FIM scores, which have also been used as predictors of outcome.13,15These results concur with studies that found relationships between standing balance and FIM scores17 and those that show correlations between motor impairment and discharge FIM scores.18 If only the FIM categories of transfers and locomotion are included (Motor FIM-5), correlation with LOS is stronger than that of total FIM, as shown by the linear regression equations obtained. Among these predictors (Motor FIM-5, Adm FIM, Adm BBS), strength of relationship was highest for Adm BBS and LOS, as shown by the equations obtained. Clinical utility of

Fig 1. Discharge FIM scores by discharge destination support. Horizontal bar (-) indicates average discharge Vertical line indicates range of discharge FIM scores.

and family FIM score.

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Table 3: Multivariate Logistic Regression Model Predicting Discharge Destination From Stroke Rehabilitation Unit Variable

Coefficient

Standard Error

Adjusted Odds Ratio

Age (per year) Supports (Y/N) Adm BBS (per point)

-.I2

.036

2.46 .08

.68 .02

.89 11.7 1.09

95% Cl

.83-.95 3.09-44.3 1.04-1.13

these equations in predicting LOS could be examined by applying them in future prospective studies. It is recognized that balance ability is closely related to functional status.19 There is an association between postural stability and function, as measured by the Barthel ADL Index.6 The evaluation of balance has historically been subjective in nature.i9 Scales such as the Fugl-Meyer motor performance scale20have incorporated a section on balance within them, but it has not seemed sensitive enough to be used to measure progress or deteriorationi Berg provides a good review of various measures of balance that have been used. The scale she developed has been shown to be reliable and relevant in an acute poststroke population9 and this author’s experience has been that it is a measure that does quantitate progress in a stroke rehabilitation population. Sitting balance has been identified as a valid predictor of disability in stroke.’ In fact, within the first few weeks, sitting equilibrium is correlated with gait ability after 6 months.21 In this study, however, the initial scale was not sensitive enough to monitor improvement in balance in a clinically useful manner. A new test called the Trunk Control Test, which examines four movements, has correlated with performance on the motor items of the FIM (FIM-13), 22 but it is not a well-known or validated test. We aimed to see if the BBS, which we feel is a good and useful measure of balance after stroke, could predict the LOS and DD from a rehabilitation unit. The only similar papers found in our literature search were those of Brosseau and coworkers,2,10 which examined predictors of LOS and discharge disposition poststroke. In their work, significant predictors found for LOS were age, functional status, perceptual status, and balance. However, they used the total Fugl-Meyer score in statistical analyses, which reflects function on other motor tasks, and not purely balance. Additionally, their LOS data would be influenced by factors other than rehabilitation, as their patient population was not on a rehabilitation unit. No other paper was found to examine the ability of the BBS to predict LOS or DD. In our study, there was a definite correlation between Adm BBS and LOS. It should be noted that some of the contribution to prolonged LOS in the group discharged to institutions was likely due to long waiting periods for nursing home beds in the Kingston area (the delay averaged 75 days). This is typical for a Canadian rehabilitation center if no formal “return to sender” agreements exist for patients no longer benefiting from further rehabilitation. A “return to sender” agreement generally implies that once active rehabilitation and discharge planning has been completed for a patient, he or she would return to the ward of origin if the waiting period for the definitive DD is lengthy. This allows rehabilitation beds to be used for active rehabilitation rather than simply accommodating to the waiting periods of various nursing and residential facilities. Various factors would be expected to influence DD, including age, the presence of supportive caregivers, financial resources of individual patients, and type of institutions available. Brosseau,i” when looking at discharge disposition, found

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significant predictors to be functional status at admission, social supports, gait status, and medical complications. The DDs they looked at included private homes, rehabilitation centers, and long-term care facilities. Their patient population was derived from a general hospital physiotherapy department rather than a tertiary SRU. Therefore, their population could have been younger, although they did not comment on age, and it is unclear whether or not their population is comparable with ours. We found age, higher Adm BBS, and presence of social supports to be associated with a higher number of discharges to the community (ie, private dwellings). Odds ratios obtained for these three independent predictors would indicate that family support was by far the most influential predictor of discharge to a private home upon completion of rehabilitation on an acute SRU. A significant lo-year difference in age was found between those discharged home and those who went to institutions. The key importance of family support in determining discharge home rather than to a residential setting was also shown in our study. Of those discharged to a residential setting, only 22% had family support, compared to 85% for those discharged home, even though disability level, as reflected in discharge FIM scores, was similar. For more severely disabled patients, it is likely that their disability, rather than presence of family support or balance, contributed more to determining DD. However, some severely disabled patients were able to go home due to the presence of able-bodied, supportive caregivers. Patients discharged home have a much broader range of disability for those with family supports than those without, as shown in figure 1. Clearly a significant number of individuals in the first column would be in a facility without family support. With average life expectancy for women being higher than that for men, one might expect that more women would be institutionalized due to lack of support. However, we did not observe any differences in DD with respect to gender. We also did not find patients with right hemispheric strokes, who are more likely to have difficulties in cognition and perception, to be discharged to institutions more often than to home. Although Brosseau*lo also found balance to be a direct predictor of LOS and gait status to predict DD poststroke, our study goes a step further in trying to quantify the predictive contribution that balance, as measured by the BBS, has with regard to LOS and DD in an SRU population. Patients and their families often ask questions pertaining to LOS and DD, and it is helpful to have a simple prognostic tool available for discussions on these issues. As with any prognostic indicator, individual variation is expected, and such predictions would provide only rough guidelines. However, admission BBS appears to be a measure that could be used, when combined with assessmentof family support and availability of caregivers willing to care for the patient at home, to assistin the estimation of LOS and prediction of DD. A prospective study to crossvalidate these findings in a second, independent group of patients is currently under way. Another potential application of the BBS could be in its early use, during the acute-care hospital assessment, to guide decisions regarding admission to a rehabilitation unit, or for prognosis. Assessment of such an application would also necessitate further studies. With the changes in the health care system resulting in fewer acute care and rehabilitation beds, accurate predictive tools are essential in optimizing efficiency of inpatient stroke rehabilitation services. Acknowledgment: sity, Kingston,

for support

Thanks to Dr. Karen and advice.

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References 1. Kwakkel G, Wagenaar RC, Kollen BJ, Lankhorst GJ. Predicting disability in stroke-a critical review of the literature. Age Ageing 1996;25:479-89. 2. Brosseau L, Philippe P, Potvin L, Boulanger Y-L. Post-stroke inpatient rehabilitation I. Predicting length of stay. Am J Phys Med Rehabil 1996;75:422-30. 3. Wade DT, Stilbeck CE, Langton HR. Predicting Barthel ADL score at 6 months after an acute stroke. Arch Phys Med Rehabil 1983;64:24-8. 4. Sandin KJ, Smith BS. The measure of balance in sitting in stroke rehabilitation prognosis. Stroke 1990;21:82-6. 5. Loewen SC, Anderson BA. Predictors of stroke outcome using objective measurement scales. Stroke 1990;21:78-81. 6. Dettmann MA, Linder MT, Sepic SB. Relationships among walking performance, postural stability, and functional assessments of the hemiplegic patient. Am J Phys Med Rehabil 1987;66:77-90. - - 7. Hamrin E, Eklund G, Hillgren A-K, Borges 0, Hall J, Hellstrom 0. Muscle strength and balance in post-stroke patients. Ups J Med Sci 1982;87:11-26. 8. Berg K, Wood-Dauphinee S, Williams JI, Gayton D. Measuring balance in the elderly: preliminary development of an instrument. Physiother Can 1989;41:304. 9. Berg K, Wood-Dauphinee S, Williams JI. The Balance Scale: reliability assessment with elderly residents and patients with an acute stroke. Stand J Rehabil Med 1995;27:27-36. 10. Brosseau L, Potvin L, Philippe P, Boulanger Y-L. Post-stroke inpatient rehabilitation II. Predicting discharge disposition. Am J Phys Med Rehabil 1996;75:431-6. 11. Guide for the Uniform Data Set for Medical Rehabilitation (Adult FIM), version 4.0. Buffalo (NY): State University of New York at Buffalo: 1993.

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12. Ottenbacher KJ, Hsu Y, Granger CV, Fieldler RC. The reliability of the Functional Independence Measure: a quantitative review. Arch Phys Med Rehabil 1996;77:1226-32. 13. Ween JE, Alexander MP, D’Esposito M, Roberts M. Factors predictive of stroke outcome in a rehabilitation setting. Neurology 1996;47:388-92. 14. Heinemann AW, Linacre JM, Wright BD, Hamilton BB, Granger C. Prediction of rehabilitation outcomes with disability measures. Arch Phys Med Rehabil 1994;75:133-43. 15. Oczkowski WJ, Barreca S. The functional independence measure: its use to identify rehabilitation needs in stroke survivors. Arch Phys Med Rehabil 1993;74:1291-4. 16. Granger CL, Cotter AC, Hamilton BB, Fiedler RC. Functional Assessment Scales: a study of persons after stroke. Arch Phys Med Rehabil 1993;74:133-8. 17. Bohannon RW, Leary KM. Standing balance and function over the course of acute rehabilitation. Arch Phys Med Rehabil 1995;76: 994-6. 18. Chae J, Johnston M, Kim H, Zorowitz R. Admission motor impairment as a predictor of physical disability after stroke rehabilitation. Am J Phys Med Rehabil 1995;74:218-23. 19. Berg K. Balance and its measure in the elderly: a review. Physiother Can 1989;41:240-6. 20. Fugl-Meyer AR, Jaaski L, Legman I, Olsson S, Steglind S. The post-stroke hemiplegic patient. 1. A method for evaluation of physical performance. Stand J Rehabil Med 1975;7:13-31. 21. Feigin L, Sharon B, Czaczkes B, Rosin AJ. Sitting equilibrium 2 weeks after a stroke can predict the walking ability after 6 months. Gerontology 1996;42:348-53. 22. Franchignoni FP, Tesio L, Ricupero C, Martin0 MT. Trunk Control Test as an early predictor of stroke rehabilitation outcome. Stroke 1997;28:1382-5.