(Stroke. 1997;28:716-721.)
© 1997 American Heart Association, Inc.
Articles |
Fall Prediction Index for Patients in Stroke Rehabilitation
From the Department of Geriatric Medicine, Umeå University (Sweden).
Correspondence to Lars Nyberg, RPT, PhD, Department of Geriatric Medicine, Umeå University, S-901 87 Umeå, Sweden. E-mail yngve.gustafsson{at}germed.umu.se
 |
Abstract |
|---|
 Top Abstract IntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
Background and Purpose The identification of stroke patients who are prone to falls is essential to the development of prevention strategies. This study aimed at developing an easily administered fall risk index for patients in stroke rehabilitation.
Methods A consecutive series of 135 patients in geriatric stroke rehabilitation was studied. Patient characteristics viewed as potential fall predictor variables were assessed at admission. Univariate and multiple Cox regression analyses of these variables were used in the development of a fall prediction index.
Results The final index included the following items: male sex, poor performance of activities of daily living, urinary incontinence, impaired postural stability, bilateral motor impairment, presence of bilateral cortical or white matter lesions, visuospatial hemineglect, and use of diuretics, antidepressants, or sedatives. The index score correlated significantly with the fall risk (odds ratio, 1.46; 95% confidence interval, 1.26 to 1.69). The score was also used to classify individuals into low-, intermediate-, and high-risk groups, among which the fall rates differed significantly (log rank statistics, 29.86; P<.001).
Conclusions An easily administered fall risk index is suggested, which might serve as a basis for prevention strategies among patients in stroke rehabilitation.
Key Words: accidental falls • risk assessment • complications • rehabilitation
|
Introduction |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
Stroke patients are prone to falls. Stroke has been connected with a greater fall risk in various kinds of rehabilitation1 2 and acute care settings.3 Furthermore, stroke has proved to be a risk factor for hip fracture among women in a case-control study,4 and subjects with previous strokes have been overrepresented in a sample of femoral neck-fracture patients.5
Falls are one of the most frequent complications in stroke rehabilitation,6 and the incidence rate of falls in a geriatric stroke rehabilitation setting was 5800 per 1000 person-years.7 The reported percentages of stroke patients suffering falls during their hospitalization include 14% in acute care,8 24% in a rehabilitation setting,2 and 39% in geriatric rehabilitation.7 Although only a small percentage of the falls result in serious injury,7 9 10 a considerable number of fall-related injuries still occur in stroke rehabilitation because falls are so common. Hence, it could well be assumed that injuries and other consequences of falls (eg, restricted activity as a result of the fear of new falls11 ) are likely to have a negative effect on the rehabilitation process and its outcome. Also, the number of hospital falls among stroke patients has been found to be a significant predictor of falls after discharge from the hospital, which in turn was associated with lower activity levels, depressed mood, and pressure on caregivers.12
Therefore, the identification of fall-prone stroke patients is of great importance. The issue has already been studied to some extent, and a number of risk factors have been suggested. Postural sway,13 increased motor response time to visual stimuli,14 and rightward orienting bias among right-hemisphere stroke patients15 have been associated with an increased fall risk. Moreover, a study of male right-hemisphere stroke patients concluded that behavioral impulsivity was a mediating factor among other risk factors for falls.16 A multifactorial case-control study concluded that a history of falls, impaired decision-making ability, restlessness, generalized weakness, and abnormal hematocrit level were independent fall risk factors among stroke patients in acute care.9
However, one attractive assumption is that the combination of multiple risk factors, concurrently present and compounding the contribution of each factor to the risk of falls, may be of greater importance than the independent effect of each factor alone.17 As a consequence of this, a number of scoring systems have been presented in which the numbers of present risk factors are added together by means of different algorithms to a score, reflecting the fall risk.16 18 19 Although these scoring systems offer quite good content validity for use in general populations of the elderly, none of them was originally intended for use in stroke-patient populations specifically. The Tinetti Index18 seems too complex to be suitable for clinical use, although its predictive accuracy has been documented. The others appear to be very easily administered in clinical practice, and two of them have been tried for stroke patients. When tested in a geriatric stroke rehabilitation setting,20 the prediction accuracy of the Downton Index19 proved to be moderate, and it was concluded that adjustments to the index would be preferable if it was to be used in a population of stroke patients. The Fall Assessment Questionnaire (FAQ) showed rather high correlation with falls among male right-hemisphere stroke patients in rehabilitation,16 but that was in combination with a measure of behavioral impulsivity, which requires a rather complex instrumental setting, thus reducing its clinical usefulness.
The purpose of this prospective investigation was therefore to develop an easily administered instrument for the identification of fall-prone individuals in stroke rehabilitation.
|
Subjects and Methods |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
Setting and Patients
The study was performed at the stroke rehabilitation unit of the geriatric clinic at Umeå University Hospital, Sweden. Patients admitted to this 24-bed ward are the most severely affected third of the survivors of those admitted to the hospital for acute-phase stroke in the catchment area of Umeå University Hospital.21 These patients all need further rehabilitation and hospital stay after the acute phase and are transferred from acute-care clinics, usually 2 to 4 weeks after the stroke.
All patients (n=142) admitted to rehabilitation after cerebrovascular
accidents or other clinically similar conditions from November 1, 1991,
through October 31, 1992, were included. Seven patients, who were
completely immobile and bedridden throughout their entire stay and who
made no locomotion efforts, were subsequently excluded from
analysis because they were judged not to be at risk of falls
and rehabilitation was not possible. Thus, 135 patients remained, and
their basic characteristics are summarized in Table 1
.
|
The study was approved by the ethics committee of the Faculty of Medicine of Umeå University, and all subjects or their relatives gave their informed consent.
Assessments
Data on patient characteristics were collected during the first
week of hospitalization at the geriatric rehabilitation unit. The
stroke diagnoses were based on clinical examination and CT in
accordance with the procedures of the Stroke Unit of Umeå University
Hospital, the criteria of which have been published
previously.24 The history of previous strokes and falls
was taken from medical records, from the subjects themselves during
admission interviews, or from their family members or caregivers.
During the admission assessment, a physician recorded visual and
hearing impairments if the subject was unable to read a short text in
10-mm block letters at reading distance or comprehend a conversation in
a normal voice from a distance of 1 m. Clinical findings from the
admission assessments and from the following 1-week inclusion period
were used when concurrent medical disorders and comorbidity were rated
by means of standard clinical procedures.
A score of 7 or lower of a maximum of 9 on the Line Bisection Test was taken to indicate visuospatial hemineglect.25 However, only 74% of the patients could complete this test. Dyspractic behavior and dysphasia, as well as visuospatial hemineglect for those who were not able to complete the Line Bisection Test, were estimated in multidisciplinary rehabilitation team consensus after comprehensive admission assessments and observations of the patients' behavior in activities performed during the inclusion period.
The location of brain lesions was determined by means of CT scan examinations and categorized: no lesions observed; right, left, or bilateral hemisphere cortical lesions; cerebellar lesions; mid-brain/brain-stem lesions; findings of bilateral white matter lesions (leukoaraiosis and multiple lacunar infarcts); and other (such as hydrocephalus).
Blood component analyses included erythrocyte sedimentation rate; white cell count; blood glucose and hemoglobin levels; and serum sodium, potassium, calcium, albumin, and creatinine levels. Venous blood samples were taken from the subjects in a fasting state and were part of the clinical routines used in this particular setting. Component values were rated as high, normal, or low, depending on how they related to the reference values used by the clinical chemistry laboratory contracted.
The performance of activities of daily living (ADL) was assessed according to the Katz Index,22 which includes six items: bathing, dressing, toileting, transferring, urinary continence, and feeding. The score ranges from A (independent in all items) to G (completely dependent). Ratings indicating dependence in the urinary continence item were taken to correspond to urinary incontinence.
Cognitive state was examined with the Mini-Mental State Examination (MMSE),23 including assessments of orientation, registration, attention, calculation, recall, language, and copying. The score ranges from 0 to 30, and a score of 23 points or less is usually considered to indicate cognitive impairment.
Motor function and postural stability were assessed by means of the Brunnström–Fugl-Meyer assessment scale.26 The motor function score ranges from 0 to 100, where 0 to 49 is graded as severe motor impairment, 50 to 84 as marked, 85 to 95 as moderate, and 96 to 100 as no or slight impairment.27 Motor function was assessed on both sides, but only the score of the most impaired side was used in the analyses of its relation to the fall risk. Furthermore, if the motor function scores of both sides were 95 or less, subjects were rated as bilaterally impaired. From a practical point of view, this cutoff score corresponds to findings of marked tendon reflex abnormalities or signs of marked dyscoordination in finger-nose and heel-knee coordination tests. The postural stability score, ranging from 0 to 14, includes assessments of postural stability and balance reactions in a sitting position, as well as bipedal and unipedal stance stability. A cutoff score of 9 or less corresponds to severe postural instability (ie, inability to stand steadily on both feet for 1 minute) or difficulties with one-legged stance in combination with reduced balance reactions in a sitting position.
Postural hypotension was defined as a drop of more than 10 mm Hg in systolic blood pressure when a subject rises to a sitting position after a 5-minute rest in a supine position. Medication data were abstracted from medical records and included only drugs prescribed for regular use. The groupings used were those suggested by Downton.19
Falls
The patients were studied for 8 weeks (56 days) from their
admission to the geriatric rehabilitation unit up to their discharge or
death. They were thus studied for a median of 49 days, ranging from 3
to 56 days, with an interquartile range of 22 to 56 days. Falls were
defined as incidents when the subject, due to an unexpected loss of
balance, came to rest on the floor or an object below knee height. All
such incidents that took place during the study period and that came to
the knowledge of the nursing staff were reported on special fall-report
forms. The incidence, characteristics, and injury consequences of these
falls have been presented previously.7
Statistical Analyses
Because of the wide range of the observation periods, survival
analysis methods were used, describing the fall risk (dependent
variable) as a function of time. For each subject, the time from
admission to the first fall (ie, the event-free period) was calculated.
If no falls occurred during the study period, observations were
censored either at the end point of study (8 weeks) or on discharge or
death. Univariate and multiple Cox regression
analyses were used to assess the associations of
patient-characteristic variables to the dependent
variable.28 Variables associated with the fall
risk by a value of P<.10 in the univariate
analyses were selected for further analysis and tried
in the multiple Cox regression modeling. The selection of the final
model variables was based on three prerequisites: the inclusion of
them should contribute significantly to the model (a significant change
to the log-likelihood 
2), they should be easy to
rate in a clinical situation, and they should offer good content
validity. The final Cox regression model was transformed into an index,
by means of which the scores of the variables included were added
together. Finally, the fit of the resulting index to the outcome
variable was assessed with Cox regression and Kaplan-Meier
analysis with log-rank test for statistical
significance.29 30 SYSTAT and SPSS statistical
software programs were used for the computation.31 32
|
Results |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
During the first 8 weeks of rehabilitation, 49 (36%) patients fell at least once, and 30 (22%) fell twice or more. Table 2
shows the univariate association of
selected patient-characteristic variables with the fall risk.
Variables selected for further multiple analyses (values of
P<.10) included sex, signs of visuospatial neglect and
dyspraxia, CT findings of bilateral hemispheric cortical or white
matter lesions, Katz ADL score of E or lower, urinary incontinence,
cognitive impairment (MMSE score <24), bilateral motor impairment,
severe postural stability impairment (score <10), high blood glucose
level, high white blood cell count, and the combined variable of
use of any of the medication groups of diuretics,
antidepressants, or sedatives. The dichotomous transformations of the
functional scores were selected; because of clear threshold effects,
they appeared to produce a stronger association with the dependent
variable than their scale origins did.
|
Regarding medical disorders, comorbidity conditions, blood component
findings, or type or location of brain lesions, no other than those
indicated in Table 2
appeared to be associated with the fall risk. As
can also be seen, the variables age, previous stroke, previous
falls, and orthostatic hypotension did not seem to
contribute to the fall risk.
The stepwise Cox regression modeling resulted in the fall risk score
presented in Table 3. The weights of the scores
were derived from the odds ratios of the final model. As shown, the
final model risk factors included male sex, urinary incontinence, Katz
ADL score of E or lower, severe postural impairment, bilateral signs of
hemiplegia, signs of visuospatial hemineglect, CT-verified bilateral
cortical and white matter lesions, and use of diuretics,
antidepressants, or sedatives. The variables high white blood cell
count and high blood glucose level did not contribute significantly to
the overall accuracy of the model, nor did the variables dyspraxia
or cognitive impairment.
|
In the total sample, the median fall risk index score was 7, with an
interquartile range of 4 to 9 and a total range of 0 to 11. The index
score proved to relate significantly to the fall risk in a Cox
regression (odds ratio, 1.46; 95% confidence interval, 1.26 to 1.69;
Wald 2, 25.13; P<.001). The odds
ratio indicates that a change of 1 point in the index score related to
a 46% increase in the fall risk.
On the basis of distribution of index scores among fallers and
nonfallers (Table 4), we suggest the following risk
level classifications of the scores: a score from 0 to 4 would indicate
a low fall risk, a score of 5 to 7 an intermediate fall risk, and a
score of 8 to 11 a high fall risk. As can be seen from the
Figure, the fall risk differed significantly (log-rank
statistics, 29.86; P<.001) among the patients assigned to
the low-, intermediate-, and high-risk groups. No falls occurred among
the patients assigned to the low-risk group.
|
|
|
Discussion |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
An accurate and easily administered instrument for the identification of fall-prone individuals may serve as an important basis for tailored fall-prevention models, in which prevention measures are directed toward high-risk individuals addressing identified risk factors, either by modification or compensation. Such a prevention approach was recently successfully tested in a community population of elderly persons.33
The fall risk index proposed in this study correlated well with the fall risk in a sample of patients in geriatric stroke rehabilitation. Furthermore, we believe that the index suggested offers quite good content validity. The item selection seems suitable for use in a stroke-patient population and reflects well-established fall risk factors.34
The functional items (low ADL score, severe postural stability impairment, and bilateral motor impairment) reflect dependence and reduced locomotion ability and safety. Multifocal or widespread brain lesions can generally be expected to affect neuropsychological function, behavior, and motor abilities.35 Perceptual impairment is a very likely and often suggested fall risk factor, since it is connected both with attention deficits and impulsivity.15 16 Urinary incontinence has previously proved to correlate with rehabilitation outcome, and this factor is assumed to be a marker of the severity of cerebral injury or to reflect a generally low cerebral function level.36 The reason why male sex turned out to be a risk indicator is not clear. There are a few studies indicating that among the institutionalized elderly, men are more likely to fall than women,37 38 which is quite contrary to what has uniformly been found in community populations of the elderly.39 Whether this should be attributed to a supposedly higher degree of proneness to risky behavior or a relatively more pronounced disability among men than women in hospitalized and disabled populations, or some other factors, remains to be determined.
It is noteworthy, however, that the medication factor accounted for an unexpectedly small contribution to the index. Also, cognitive impairment and dyspraxia did not seem to add to the contribution of the other items of the multifactorial model, although these factors were associated with the fall risk in the univariate analyses. Previous (prestroke) falls are likely to be of less importance as a risk indicator in a stroke-patient population, since the stroke itself changes the individual's state so dramatically.
Some methodological difficulties were considered in the study design and analyses. Because stroke patients are subject to a considerable amount of change during their acute and subacute phases, the validity of many patient-characteristic ratings must be seen as time dependent. Therefore, we limited the study period to a maximum of 8 weeks. The fact that the study concerned only the inpatient rehabilitation period resulted in a wide variation in observation time, which was accounted for by the use of survival analysis methods.
The study also had a number of limitations that should be considered. Although completely immobile patients were excluded from the analysis, no specific measure of patient activity was used. Such a measure of the actual risk exposure would undoubtedly have enhanced our analyses. Nor were any measures of increased response time, impulsive behavior, or rightward orienting bias included (ie, factors previously associated with the risk of falls among stroke patients).14 15 16 If these factors had been included, it is possible that our study would have resulted in a better prediction model. The Line-Bisection Test could not be completed by all patients, so some of the ratings regarding visuospatial hemineglect were based on behavioral observations, which were made by an experienced multidisciplinary team constellation. The study included a selected sample of stroke patients. However, we believe that this sample is fairly representative of moderately to severely disabled stroke patients who need further hospital stay and rehabilitation after the acute phase. Furthermore, the accuracy of the fall risk index was expressed only by means of its fit to the data from which it originated. To ensure its accuracy, the index should be tested prospectively on an independent patient sample.
We expect that our proposed index will be easy to administer in the clinical situation. The Katz ADL Index is well known and easily rated by means of information that should be available in the rehabilitation setting. The postural stability score of the Brunnström–Fugl-Meyer assessment includes five well-defined items (two of which are rated bilaterally) and is accomplished in 5 to 10 minutes. Although we used the Brunnström–Fugl-Meyer motor score, which is quite elaborate, to assess bilateral motor impairment, this could easily be defined as bilateral findings of marked motor impairment (ie, findings indicating more severe impairment than a slight dyscoordination in finger-nose and heel-knee tests or slightly abnormal tendon reflexes). The ratings of visuospatial hemineglect should preferably be accompanied by relevant available testing procedures (eg, the Line Bisection Test). For the time being, we assume that CT scans or other brain imaging techniques are a standard clinical routine in the management of patients with stroke. We therefore expect that the assessment of an index score would not lengthen a standard clinical evaluation by more than approximately 15 to 20 minutes.
This study resulted in a fall prediction model in the form of an index score that correlated very well with the fall risk in a geriatric stroke rehabilitation patient sample. The index is easily administered and intended to be used for patients in stroke rehabilitation. However, its predictive accuracy has to be further evaluated.
|
Acknowledgments |
|---|
The study was supported by grants from the Borgerskapet i Umeå Research Foundation, the Federation of County Councils in Sweden, the 1987 Foundation for Stroke Research, the Joint Committee of the Northern Health Region of Sweden, the Swedish Society of Medicine (reference No. 340.0), Umeå University's Fund for Medical Research, and the Västerbotten County Council. Thanks to Mai Mattsson, MD, and Ulrica Radsjö, RPT, for their assistance and to Hans Stenlund, Department of Epidemiology and Public Health, Umeå University, for statistical advice.
Received November 8, 1996; revision received January 7, 1997; accepted January 20, 1997.
|
References |
|---|
|
TopAbstractIntroductionSubjects and MethodsResultsDiscussionReferences |
|---|
1. Mayo NE, Korner-Bitensky N, Becker R, Georges P. Predicting falls among patients in a rehabilitation hospital. Am J Phys Med Rehabil. 1989;68:139-146. [Medline] [Order article via Infotrieve]
2. Vlahov D, Myers AH, Al-Ibrahim MS. Epidemiology of falls among patients in a rehabilitation hospital. Arch Phys Med Rehabil. 1990;71:8-12. [Medline] [Order article via Infotrieve]
3. Salgado R, Lord SR, Packer J, Ehrlich F. Factors associated with falling in elderly hospital patients. Gerontology. 1994;40:325-331. [Medline] [Order article via Infotrieve]
4. Grisso JA, Kelsey JL, Strom BL, Chiu GY, Maislin G, O'Brien LA, Hoffman S, Kaplan F, for the Northeast Hip Fracture Study Group. Risk factors for falls as a cause of hip fracture in women. N Engl J Med. 1991;324:1326-1331. [Abstract]
5. Gustafson Y, Brännström B, Berggren D, Ragnarsson JI, Sigaard J, Bucht G, Reiz S, Norberg A, Winblad B. A geriatric-anesthesiologic program to reduce acute confusional states in elderly patients treated for femoral neck fractures. J Am Geriatr Soc. 1991;39:655-662. [Medline] [Order article via Infotrieve]
6. Dromerick A, Reding M. Medical and neurological complications during inpatient stroke rehabilitation. Stroke. 1994;25:358-361. [Abstract]
7.
Nyberg L, Gustafson Y. Patient falls in stroke
rehabilitation: a challenge to rehabilitation strategies.
Stroke. 1995;26:838-842.
8. Tutuarima JA, de Haan RJ, Limburg M. Number of nursing staff and falls: a case-control study on falls by stroke patients in acute-care settings. J Adv Nurs. 1993;18:1101-1105. [Medline] [Order article via Infotrieve]
9. Byers V, Arrington ME, Finstuen K. Predictive risk factors associated with stroke patient falls in acute care settings. J Neurosci Nurs. 1990;22:147-154. [Medline] [Order article via Infotrieve]
10. Stein J, Viramontes BE, Kerrigan DC. Fall-related injuries in anticoagulated stroke patients during inpatient rehabilitation. Arch Phys Med Rehabil. 1995;76:840-843. [Medline] [Order article via Infotrieve]
11.
Vellas B, Cayla F, Bocquet H, de Pemille F, Albarede
JL. Prospective study of restriction of activity in old people
after falls. Age Ageing. 1987;16:189-193.
12.
Forster A, Young J. Incidence and consequences
of falls due to stroke: a systematic inquiry. Br Med
J. 1995;311:83-86.
13. Sackley CM. Falls, sway, and symmetry of weight-bearing after stroke. Int Disabil Stud. 1991;13:1-4. [Medline] [Order article via Infotrieve]
14. Mayo NE, Korner-Bitensky N, Kaizer F. Relationship between response time and falls among stroke patients undergoing physical rehabilitation. Int J Rehabil Res. 1990;13:47-55. [Medline] [Order article via Infotrieve]
15. Webster JS, Roades LA, Morrill B, Rapport LJ, Abadee PS, Sowa MV, Dutra R, Godlewski MC. Rightward orienting bias, wheelchair maneuvering, and fall risk. Arch Phys Med Rehabil. 1995;76:924-928. [Medline] [Order article via Infotrieve]
16. Rapport LJ, Webster JS, Flemming KL, Lindberg JW, Godlewski MC, Brees JE, Abadee PS. Predictors of falls among right-hemisphere stroke patients in the rehabilitation setting. Arch Phys Med Rehabil. 1993;74:621-626. [Medline] [Order article via Infotrieve]
17. Tinetti ME, Speechley M. Prevention of falls among the elderly. N Engl J Med. 1989;320:1055-1059. [Medline] [Order article via Infotrieve]
18. Tinetti ME, Williams TF, Mayewski R. Fall risk index for elderly patients based on number of chronic disabilities. Am J Med. 1986;80:429-434. [Medline] [Order article via Infotrieve]
19. Downton JH. Falls in the Elderly. London, UK: Edward Arnold; 1993:128-130.
20.
Nyberg L, Gustafson Y. Using the Downton Index
to predict those prone to falls in stroke rehabilitation.
Stroke. 1996;27:1821-1824.
21. Gustafson Y, Olsson T, Eriksson S, Asplund K, Bucht G. Acute confusional states (delirium) in stroke patients. Cerebrovasc Dis. 1991;1:257-264.
22. Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW. Studies of illness in the aged. The index of ADL: a standardized measure of biological and psychosocial function. J Am Med Assoc. 1963;185:914-919.
23. Folstein MF, Folstein SE, McHugh PR. `Mini-Mental State': a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12:189-198. [Medline] [Order article via Infotrieve]
24.
Strand T, Asplund K, Eriksson S, Hägg E, Lithner
F, Wester PO. A non-intensive stroke unit reduces functional
disability and the need for long-term hospitalization.
Stroke. 1985;16:29-34.
25. Friedman PJ. Spatial neglect in acute stroke: the Line Bisection Test. Scand J Rehabil Med. 1990;22:101-106. [Medline] [Order article via Infotrieve]
26. Fugl-Meyer AR, Jääskö L, Leyman I, Olsson S, Steglind S. The post-stroke hemiplegic patient, I: a method for evaluation of physical performance. Scand J Rehabil Med. 1975;7:13-31. [Medline] [Order article via Infotrieve]
27. Fugl-Meyer AR. Post-stroke hemiplegia: assessment of physical properties. Scand J Rehabil Med. 1980;suppl 7:85-93.
28. Cox DR. Regression models and life tables. J R Stat Soc. 1972;B34;187-220.
29. Kaplan EL, Meier P. Nonparametric estimation from incomplete observations. J Am Stat Assoc. 1958;53:457-481.
30. Dawson-Saunders B, Trapp RG. Basic & Clinical Biostatistics. 2nd ed. East Norwalk, CT: Appleton & Lange; 1994:200-201.
31. SYSTAT: Statistics, Version 5.2 Edition. Evanston, Ill: SYSTAT Inc; 1992.
32. Norusis MJ. SPSS Advanced Statistics 6.1. Chicago, Ill: SPSS Inc; 1994.
33.
Tinetti ME, Baker DI, McAvay G, Claus EB, Garrett P,
Gottschalk M, Koch ML, Trainor K, Horwitz RI. A multifactorial
intervention to reduce the risk of falling among elderly people living
in the community. N Engl J Med. 1994;331:821-827.
34. Myers AH, Young Y, Langlois JA. Prevention of falls in the elderly. Bone. 1996;18:87S-101S. [Medline] [Order article via Infotrieve]
35.
Longstreth WT, Manolio TA, Arnold A, Burke GL, Bryan N,
Jungreis CA, Enright PL, O'Leary D, Fried L, for the
Cardiovascular Health Study Collaborative Research
Group. Clinical correlates of white matter findings on cranial magnetic
resonance imaging of 3301 elderly people: the
Cardiovascular Health Study. Stroke. 1996;27:1274-1282.
36. Wade DT, Langton-Hewer R, Skilbeck CE, David RM. Stroke. A Critical Approach to Diagnosis, Treatment, and Management. London, UK: Chapmann and Hall; 1985:249.
37. Sehested P, Severin-Nielsen T. Falls by hospitalized elderly patients: causes, prevention. Geriatrics. 1977;32:101-108.
38. Nyberg L, Gustafson Y, Janson A, Sandman PO, Eriksson S. Incidence of falls in three different types of geriatric care: a Swedish prospective study. Scand J Soc Med. In press.
39. Campbell AJ, Spears GF, Borrie MJ. Examination by logistic regression modelling of the variables which increase the relative risk of elderly women falling compared to elderly men. J Clin Epidemiol. 1990;43:1415-1420.[Medline] [Order article via Infotrieve]
This article has been cited by other articles:
 |
|
 |
|
  U. Sennerby, H. Melhus, R. Gedeborg, L. Byberg, H. Garmo, A. Ahlbom, N. L. Pedersen, and K. Michaelsson Cardiovascular Diseases and Risk of Hip Fracture JAMA, October 21, 2009; 302(15): 1666 - 1673. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. A. Divani, G. Vazquez, A. M. Barrett, M. Asadollahi, and A. R. Luft Risk Factors Associated With Injury Attributable to Falling Among Elderly Population With History of Stroke Stroke, October 1, 2009; 40(10): 3286 - 3292. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. Czernuszenko and A. Czlonkowska Risk factors for falls in stroke patients during inpatient rehabilitation Clinical Rehabilitation, February 1, 2009; 23(2): 176 - 188. [Abstract] [PDF]
|
|
|
|
|
|
R. Luengo-Fernandez, A. M. Gray, and P. M. Rothwell Costs of Stroke Using Patient-Level Data: A Critical Review of the Literature Stroke, February 1, 2009; 40(2): e18 - e23. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. P. Yelnik, F. Le Breton, F. M. Colle, I. V. Bonan, C. Hugeron, V. Egal, E. Lebomin, J.-P. Regnaux, D. Perennou, and E. Vicaut Rehabilitation of Balance After Stroke With Multisensorial Training: A Single-Blind Randomized Controlled Study Neurorehabil Neural Repair, September 1, 2008; 22(5): 468 - 476. [Abstract] [PDF]
|
|
|
|
 |
|
 T. Haines, S. S. Kuys, G. Morrison, J. Clarke, and P. Bew Balance Impairment Not Predictive of Falls in Geriatric Rehabilitation Wards J. Gerontol. A Biol. Sci. Med. Sci., May 1, 2008; 63(5): 523 - 528. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 A. Ashburn, D. Hyndman, R. Pickering, L. Yardley, and S. Harris Predicting people with stroke at risk of falls Age Ageing, May 1, 2008; 37(3): 270 - 276. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 P.K. Myint, K.E.S. Poole, and E.A. Warburton Hip fractures after stroke and their prevention QJM, September 1, 2007; 100(9): 539 - 545. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
T. P. Haines, K. D. Hill, K. L. Bennell, and R. H. Osborne Additional exercise for older subacute hospital inpatients to prevent falls: benefits and barriers to implementation and evaluation Clinical Rehabilitation, August 1, 2007; 21(8): 742 - 753. [Abstract] [PDF]
|
|
|
|
|
|
T. P. Haines, K. Hill, W. Walsh, and R. Osborne Design-Related Bias in Hospital Fall Risk Screening Tool Predictive Accuracy Evaluations: Systematic Review and Meta-Analysis J. Gerontol. A Biol. Sci. Med. Sci., June 1, 2007; 62(6): 664 - 672. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
T. P Haines, K. D Hill, K. L Bennell, and R. H Osborne Patient education to prevent falls in subacute care Clinical Rehabilitation, November 1, 2006; 20(11): 970 - 979. [Abstract] [PDF]
|
|
|
|
 |
|
 C. Seneviratne The STRATIFY falls risk assessment tool was not useful in predicting falls in patients with acute stroke Evid. Based Nurs., July 1, 2006; 9(3): 91 - 91. [Full Text] [PDF]
|
|
|
|
|
|
J. Smith, A. Forster, and J. Young Use of the 'STRATIFY' falls risk assessment in patients recovering from acute stroke Age Ageing, March 1, 2006; 35(2): 138 - 143. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
Y.-R. Yang, J.-G. Yen, R.-Y. Wang, L.-L. Yen, and F.-K. Lieu Gait outcomes after additional backward walking training in patients with stroke: a randomized controlled trial Clinical Rehabilitation, March 1, 2005; 19(3): 264 - 273. [Abstract] [PDF]
|
|
|
|
|
|
S.E. Lamb, L. Ferrucci, S. Volapto, L.P. Fried, J.M. Guralnik, and Y. Gustafson Risk Factors for Falling in Home-Dwelling Older Women With Stroke: The Women's Health and Aging Study * Editorial Comment Stroke, February 1, 2003; 34(2): 494 - 501. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
K. L. Perell, A. Nelson, R. L. Goldman, S. L. Luther, N. Prieto-Lewis, and L. Z. Rubenstein Fall Risk Assessment Measures: An Analytic Review J. Gerontol. A Biol. Sci. Med. Sci., December 1, 2001; 56(12): M761 - 766. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. L. Harris-Love, L. W. Forrester, R. F. Macko, K. H. C. Silver, and G. V. Smith Hemiparetic Gait Parameters in Overground Versus Treadmill Walking Neurorehabil Neural Repair, March 1, 2001; 15(2): 105 - 112. [Abstract] [PDF]
|
|
|
|
 |
|
 C. Ugur, D. Gucuyener, N. Uzuner, S. Ozkan, and G. Ozdemir Characteristics of falling in patients with stroke J. Neurol. Neurosurg. Psychiatry, November 1, 2000; 69(5): 649 - 651. [Abstract] [Full Text] [PDF]
|
|
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||