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Association Between Performance on an Interdisciplinary Stroke Assessment Battery and Falls in Patients With Acute Stroke in an Inpatient Rehabilitation Facility: A Retrospective Cohort Study

      Abstract

      Objective

      To explore the association between demographic factors and functional performance measures of patients with acute stroke in an inpatient rehabilitation facility (IRF) and falls during the IRF stay and to quantify the diagnostic accuracy of functional outcome measures in identifying fallers.

      Design

      Retrospective cohort study.

      Setting

      Inpatient rehabilitation facility.

      Participants

      Individuals with acute stroke admitted to hospital-based IRF (N=139).

      Interventions

      Not applicable.

      Main Outcome Measures

      Odds ratios were used to examine the relationship between fall frequency and functional outcome measures (National Institute of Stroke Scale, neglect [Item #11], Berg Balance Scale, Stroke Rehabilitation Assessment of Movement mobility and Stroke Rehabilitation Assessment of Movement lower extremity subscales [STREAM-LE], Montreal Cognitive Assessment, Dynamic Gait Index, and Stroke Impact Scale). Receiver operator characteristic analysis with area under the curve, sensitivity, specificity, and diagnostic odds ratio were used to assess the diagnostic accuracy of each functional outcome measure to distinguish patients who fell vs those who did not fall in the IRF.

      Results

      A total of 23 patients (16.2%) fell during the IRF hospitalization. Patients who did and did not fall did not differ in terms of age, sex, stroke type, or stroke location. Only the STREAM-LE was associated with falls (odds ratio, 0.93; 95% CI, 0.86-0.99). Area under the curve was 0.67 (95% CI, 0.51-0.82). With a positivity cutoff point of 12, sensitivity and specificity were 73.3% (95% CI, 54.6%-92.2%) and 50.0% (95% CI, 39.9%-59.2%), respectively. The diagnostic odds ratio was 3.4.

      Conclusions

      The STREAM-LE score at admission to IRF may identify patients with acute stroke who are more likely to fall during their stay. However, the search for measures with greater diagnostic accuracy should continue.

      Keywords

      List of abbreviations:

      AUC (area under the curve), BBS (Berg Balance Scale), DOR (diagnostic odds ratio), DGI (Dynamic Gait Index), EMR (electronic medical record), ICC (intraclass correlation coefficient), IRF (inpatient rehabilitation facility), MoCA (Montreal Cognitive Assessment), NIHSS (National Institute of Health Stroke Scale), NIHSS-11 (National Institute of Health Stroke Scale, item 11), NPV (negative predictive values), OT (occupational therapist), PPV (positive predictive value), PT (physical therapist), PTA (physical therapist assistant), REDCap (Research Electronic Data Capture), ROC (receiver operating characteristic), STREAM (Stroke Rehabilitation Assessment of Movement), STREAM-LE (Stroke Rehabilitation Assessment of Movement, lower extremity subscale), STREAM-M (Stroke Rehabilitation Assessment of Movement, mobility subscale)
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      References

        • Walsh M.E.
        • Horgan N.F.
        • Walsh C.D.
        • Galvin R.
        Systematic review of risk prediction models for falls after stroke.
        J Epidemiol Community Health. 2016; 70: 513-519
        • Czernuszenko A.
        • Czlonkowska A.
        Risk factors for falls in stroke patients during inpatient rehabilitation.
        Clin Rehabil. 2009; 23: 463
        • Teasell R.
        • McRae M.
        • Foley N.
        • Bhardwaj A.
        The incidence and consequences of falls in stroke patients during inpatient rehabilitation: factors associated with high risk.
        Arch Phys Med Rehabil. 2002; 83: 329-333
        • Holloway R.G.
        • Tuttle D.
        • Baird T.
        • Skelton W.K.
        The safety of hospital stroke care.
        Neurology. 2007; 68: 550-555
        • Wong J.S.
        • Brooks D.
        • Mansfield A.
        Do falls experienced during inpatient stroke rehabilitation affect length of stay, functional status, and discharge destination?.
        Arch Phys Med Rehabil. 2016; 97: 561-566
        • The Joint Commission
        Preventing falls and fall-related injuries in health care facilities.
        (Available at:)
        • Maeda N.
        • Kato J.
        • Shimada T.
        Predicting the probability for fall incidence in stroke patients using the Berg Balance Scale.
        J Int Med Res. 2009; 37: 697-704
        • Sullivan J.E.
        • Crowner B.E.
        • Kluding P.M.
        • et al.
        Outcome measures for individuals with stroke: process and recommendations from the American Physical Therapy Association Neurology Section Task Force.
        Phys Ther. 2013; 93: 1383-1396
        • Kinney C.
        • Eikenberry M.
        • Noll S.
        • Tompkins J.
        • Verheijde J.
        Standardization of interdisciplinary clinical practice and assessment in stroke rehabilitation.
        Int J Phys Med Rehabil. 2013; 01
        • Goldstein L.B.
        • Samsa G.P.
        Reliability of the National Institutes of Health Stroke Scale: extension to non-neurologists in the context of a clinical trial.
        Stroke. 1997; 28: 307-310
        • Harris P.A.
        • Taylor R.
        • Thielke R.
        • Payne J.
        • Gonzalez N.
        • Conde J.G.
        Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support.
        J Biomed Inform. 2009; 42: 377-381
        • Xu T.
        • Clemson L.
        • O’Loughlin K.
        • Lannin N.A.
        • Dean C.
        • Koh G.
        Risk factors for falls in community stroke survivors: a systematic review and meta-analysis.
        Arch Phys Med Rehabil. 2018; 99: 563-573
        • Kasner S.E.
        Clinical interpretation and use of stroke scales.
        Lancet Neurol. 2006; 5: 603-612
        • Toglia J.
        • Fitzgerald K.A.
        • O’Dell M.W.
        • Mastrogiovanni A.R.
        • Lin C.D.
        The Mini-Mental State Examination and Montreal Cognitive Assessment in persons with mild subacute stroke: relationship to functional outcome.
        Arch Phys Med Rehabil. 2011; 92: 792-798
        • Nasreddine Z.S.
        • Phillips N.A.
        • Bédirian V.
        • et al.
        The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment.
        (Available at:)
        • Blum L.
        • Korner-Bitensky N.
        Usefulness of the Berg Balance Scale in stroke rehabilitation: a systematic review.
        Phys Ther. 2008; 88: 559-566
        • Berg K.
        • Wood-Dauphinee S.
        • Williams J.I.
        The Balance Scale: reliability assessment with elderly residents and patients with an acute stroke.
        Scand J Rehabil Med. 1995; 27: 27-36
        • Ahmed S.
        • Mayo N.E.
        • Higgins J.
        • Salbach N.M.
        • Finch L.
        • Wood-Dauphinée S.L.
        The Stroke Rehabilitation Assessment of Movement (STREAM): a comparison with other measures used to evaluate effects of stroke and rehabilitation.
        Phys Ther. 2003; 83: 617-630
        • Daley K.
        • Mayo N.
        • Wood-Dauphinée S.
        Reliability of scores on the Stroke Rehabilitation Assessment of Movement (STREAM) measure.
        Phys Ther. 1999; 79 ([quiz 20-3]): 8-19
        • Gor-García-Fogeda M.D.
        • Molina-Rueda F.
        • Cuesta-Gómez A.
        • Carratalá-Tejada M.
        • Alguacil-Diego I.M.
        • Miangolarra-Page J.C.
        Scales to assess gross motor function in stroke patients: a systematic review.
        Arch Phys Med Rehabil. 2014; 95: 1174-1183
        • Hsueh I.P.
        • Hsu M.J.
        • Sheu C.F.
        • Lee S.
        • Hsieh C.L.
        • Lin J.H.
        Psychometric comparisons of 2 versions of the Fugl-Meyer Motor Scale and 2 versions of the Stroke Rehabilitation Assessment of Movement.
        Neurorehabil Neural Repair. 2008; 22: 737-744
        • Arya K.N.
        • Pandian S.
        • Abhilasha C.R.
        • Verma A.
        Does the motor level of the paretic extremities affect balance in poststroke subjects?.
        Rehabil Res Pract. 2014; 2014: 767859
        • Jonsdottir J.
        • Cattaneo D.
        Reliability and validity of the Dynamic Gait Index in persons with chronic stroke.
        Arch Phys Med Rehabil. 2007; 88: 1410-1415
        • Lin J.H.
        • Hsu M.J.
        • Hsu H.W.
        • Wu H.C.
        • Hsieh C.L.
        Psychometric comparisons of 3 functional ambulation measures for patients with stroke.
        Stroke. 2010; 41: 2021-2025
        • Peduzzi P.
        • Concato J.
        • Kemper E.
        • Holford T.R.
        • Feinstein A.R.
        A simulation study of the number of events per variable in logistic regression analysis.
        J Clin Epidemiol. 1996; 49: 1373-1379
        • Nyberg L.
        • Gustafson Y.
        Patient falls in stroke rehabilitation: a challenge to rehabilitation strategies.
        Stroke. 1995; 26: 838-842
        • Suzuki T.
        • Sonoda S.
        • Misawa K.
        • Saitoh E.
        • Shimizu Y.
        • Kotake T.
        Incidence and consequence of falls in inpatient rehabilitation of stroke patients.
        Exp Aging Res. 2005; 31: 457-469
        • Schlegel D.
        • Kolb S.J.
        • Luciano J.M.
        • et al.
        Utility of the NIH Stroke Scale as a predictor of hospital disposition.
        Stroke. 2003; 34: 134-137
        • Rundek T.
        • Mast H.
        • Hartmann A.
        • et al.
        Predictors of resource use after acute hospitalization: the Northern Manhattan Stroke Study.
        Neurology. 2000; 55: 1180-1187
        • Ward I.
        • Pivko S.
        • Brooks G.
        • Parkin K.
        Validity of the Stroke Rehabilitation Assessment of Movement Scale in acute rehabilitation: a comparison with the Functional Independence Measure and Stroke Impact Scale-16.
        PM R. 2011; 3: 1013-1021
        • Mao H.F.
        • Hsueh I.P.
        • Tang P.F.
        • Sheu C.F.
        • Hsieh C.L.
        Analysis and comparison of the psychometric properties of three balance measures for stroke patients.
        Stroke. 2002; 33: 1022-1027
        • Cohen J.F.
        • Korevaar D.A.
        • Altman D.G.
        • et al.
        STARD 2015 guidelines for reporting diagnostic accuracy studies: explanation and elaboration.
        BMJ Open. 2016; 6e012799
        • Simundic A.
        Measures of diagnostic accuracy: basic definitions.
        EJIFCC. 2009; 19: 203
        • Riddle D.L.
        • Stratford P.W.
        Interpreting validity indexes for diagnostic tests: an illustration using the Berg Balance Test.
        Phys Ther. 1999; 79: 939-948
        • Moore J.L.
        • Potter K.
        • Blankshain K.
        • Kaplan S.L.
        • O’Dwyer L.C.
        • Sullivan J.E.
        A core set of outcome measures for adults with neurologic conditions undergoing rehabilitation: a clinical practice guideline.
        J Neurol Phys Ther. 2018; 42: 174-220
        • Song J.W.
        • Chung K.C.
        Observational studies: cohort and case-control studies.
        Plast Reconstr Surg. 2010; 126: 2234-2242
        • Jette D.U.
        • Halbert J.
        • Iverson C.
        • Miceli E.
        • Shah P.
        Use of standardized outcome measures in physical therapist practice: perceptions and applications.
        Phys Ther. 2009; 89: 125-135