Early functional factors for predicting outcome of independence in daily living after stroke: a decision tree analysis
DOI:
https://doi.org/10.2340/jrm.v56.35095Keywords:
Stroke, Prediction, activities of daily living, motor function, cognitionAbstract
Objective: This study aimed to investigate the predictive functional factors influencing the acquisition of basic activities of daily living performance abilities during the early stages of stroke rehabilitation using classification and regression analysis trees.
Methods: The clinical data of 289 stroke patients who underwent rehabilitation during hospitalization (164 males; mean age: 62.2 ± 13.9 years) were retrospectively collected and analysed. The follow-up period between admission and discharge was approximately 6 weeks. Medical records, including demographic characteristics and various functional assessments with item scores, were extracted. The modified Barthel Index on discharge served as the target outcome for analysis. A “good outcome” was defined as a modified Barthel Index score ≥ 75 on discharge, while a modified Barthel Index score < 75 was classified as a “poor outcome.”
Results: Two classification and regression analysis tree models were developed. The first model, predicting activities of daily living outcomes based on early motor functions, achieved an accuracy of 92.4%. Among patients with a “good outcome”, 70.9% exhibited (i) ≥ 4 points in the “sitting-to-standing” category in the motor assessment scale and (ii) 32 points on the Berg Balance Scale score. The second model, predicting activities of daily living outcome based on early cognitive functions, achieved an accuracy of 82.7%. Within the “poor outcome” group, 52.2% had (i) ≤ 21 points in the “visuomotor organization” category of Lowenstein Occupational Therapy Cognitive Assessment, (ii) ≤ 1 point in the “time orientation” category of the Mini Mental State Examination.
Conclusion: The ability to perform “sitting-to-standing” and visuomotor organization functions at the beginning of rehabilitation emerged as the most significant predictors for achieving successful basic activities of daily living on discharge after stroke.
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Haghgoo HA, Pazuki ES, Hosseini AS, Rassafiani M. Depression, activities of daily living and quality of life in patients with stroke. J Neurol Sci 2013; 328: 87-91.
https://doi.org/10.1016/j.jns.2013.02.027 DOI: https://doi.org/10.1016/j.jns.2013.02.027
Ghaffari A, Rostami HR, Akbarfahimi M. Predictors of instrumental activities of daily living performance in patients with stroke. Occup Ther Int 2021 Feb 27; 2021:6675680.
https://doi.org/10.1155/2021/6675680 DOI: https://doi.org/10.1155/2021/6675680
Hofgren C, Björkdahl A, Esbjörnsson E, Stibrant-Sunnerhagen K. Recovery after stroke: cognition, ADL function and return to work. Acta Neurol Scand 2007; 115: 73-80.
https://doi.org/10.1111/j.1600-0404.2006.00768.x DOI: https://doi.org/10.1111/j.1600-0404.2006.00768.x
Appelros P, Nydevik I, Terént A. Living setting and utilisation of ADL assistance one year after a stroke with special reference to gender differences. Disabil Rehabil 2006; 28: 43-49.
https://doi.org/10.1080/09638280500165278 DOI: https://doi.org/10.1080/09638280500165278
Pei L, Zang X-Y, Wang Y, Chai Q-W, Wang J-Y, Sun C-Y, et al. Factors associated with activities of daily living among the disabled elders with stroke. Int J Nurs Sci 2016; 3: 29-34.
https://doi.org/10.1016/j.ijnss.2016.01.002 DOI: https://doi.org/10.1016/j.ijnss.2016.01.002
Veerbeek JM, Kwakkel G, van Wegen EE, Ket JC, Heymans MW. Early prediction of outcome of activities of daily living after stroke: a systematic review. Stroke 2011; 42: 1482-1488.
https://doi.org/10.1161/STROKEAHA.110.604090 DOI: https://doi.org/10.1161/STROKEAHA.110.604090
Pettersen R, Dahl T, Wyller TB. Prediction of long-term functional outcome after stroke rehabilitation. Clin Rehabil 2002; 16: 149-159.
https://doi.org/10.1191/0269215502cr482oa DOI: https://doi.org/10.1191/0269215502cr482oa
Rost NS, Bottle A, Lee JM, Randall M, Middleton S, Shaw L, et al. Stroke severity is a crucial predictor of outcome: an international prospective validation study. J Am Heart Assoc 2016; 5: e002433.
https://doi.org/10.1161/JAHA.115.002433 DOI: https://doi.org/10.1161/JAHA.115.002433
Kitago T, Marshall RS. Strategies for early stroke recovery: what lies ahead? Curr Treat Options Cardiovasc Med 2015; 17: 1-10.
https://doi.org/10.1007/s11936-014-0356-8 DOI: https://doi.org/10.1007/s11936-014-0356-8
Galeoto G, Iori F, De Santis R, Santilli V, Mollica R, Marquez MA, et al. The outcome measures for loss of functionality in the activities of daily living of adults after stroke: a systematic review. Top Stroke Rehabil 2019; 26: 236-245.
https://doi.org/10.1080/10749357.2019.1574060 DOI: https://doi.org/10.1080/10749357.2019.1574060
Gialanella B, Santoro R, Ferlucci C. Predicting outcome after stroke: the role of basic activities of daily living. Eur J Phys Rehabil Med 2013; 49: 629-637.
De Wit L, Putman K, Devos H, Brinkmann N, Dejaeger E, De Weerdt W, et al. Long-term prediction of functional outcome after stroke using single items of the Barthel Index at discharge from rehabilitation centre. Disabil Rehabil 2014; 36: 353-358.
https://doi.org/10.3109/09638288.2013.793411 DOI: https://doi.org/10.3109/09638288.2013.793411
Zhang Q, Zhang Z, Huang X, Zhou C, Xu J. Application of logistic regression and decision tree models in the prediction of activities of daily living in patients with stroke. Neural Plast 2022 Jan 28; 2022:9662630.
https://doi.org/10.1155/2022/9662630 DOI: https://doi.org/10.1155/2022/9662630
Ishiwatari M, Honaga K, Tanuma A, Takakura T, Hatori K, Kurosu A, et al. Trunk impairment as a predictor of activities of daily living in acute stroke. Front Neurol 2021; 12: 665592.
https://doi.org/10.3389/fneur.2021.665592 DOI: https://doi.org/10.3389/fneur.2021.665592
Einstad MS, Thingstad P, Lydersen S, Gunnes M, Saltvedt I, Askim T. Physical performance and cognition as predictors of instrumental activities of daily living after stroke: a prospective multicenter cohort study. Arch Phys Med Rehabil 2022; 103: 1320-1326.
https://doi.org/10.1016/j.apmr.2022.01.153 DOI: https://doi.org/10.1016/j.apmr.2022.01.153
Aguiar FS, Almeida LL, Ruffino-Netto A, Kritski AL, Mello FC, Werneck GL. Classification and regression tree (CART) model to predict pulmonary tuberculosis in hospitalized patients. BMC Pulm Med 2012; 12: 1-8.
https://doi.org/10.1186/1471-2466-12-40 DOI: https://doi.org/10.1186/1471-2466-12-40
Mishra S, Dykeman J, Sajobi T, Trivedi A, Almekhlafi M, Sohn S, et al. Early reperfusion rates with IV tPA are determined by CTA clot characteristics. AJNR Am J Neuroradiol 2014; 35: 2265-2272.
https://doi.org/10.3174/ajnr.A4048 DOI: https://doi.org/10.3174/ajnr.A4048
Zimmerman RK, Nowalk MP, Bear T, Taber R, Clarke KS, Sax TM, et al. Proposed clinical indicators for efficient screening and testing for COVID-19 infection using Classification and Regression Trees (CART) analysis. Hum Vaccin Immunother 2021; 17: 1109-1112.
https://doi.org/10.1080/21645515.2020.1822135 DOI: https://doi.org/10.1080/21645515.2020.1822135
Shah S, Vanclay F, Cooper B. Improving the sensitivity of the Barthel Index for stroke rehabilitation. J Clin Epidemiol 1989; 42: 703-709.
https://doi.org/10.1016/0895-4356(89)90065-6 DOI: https://doi.org/10.1016/0895-4356(89)90065-6
Uyttenboogaart M, Stewart RE, Vroomen PC, De Keyser J, Luijckx G-J. Optimizing cutoff scores for the Barthel index and the modified Rankin scale for defining outcome in acute stroke trials. Stroke 2005; 36: 1984-1987.
https://doi.org/10.1161/01.STR.0000177872.87960.61 DOI: https://doi.org/10.1161/01.STR.0000177872.87960.61
Zhang H, Singer BH. Recursive partitioning and applications. Berlin/HeidelbergL Springer Science & Business Media; 2010.
https://doi.org/10.1007/978-1-4419-6824-1 DOI: https://doi.org/10.1007/978-1-4419-6824-1
Lemon SC, Roy J, Clark MA, Friedmann PD, Rakowski W. Classification and regression tree analysis in public health: methodological review and comparison with logistic regression Ann Behav Med 2003; 26: 172-181.
https://doi.org/10.1207/S15324796ABM2603_02 DOI: https://doi.org/10.1207/S15324796ABM2603_02
Wing K, Lynskey JV, Bosch PR. Whole-body intensive rehabilitation is feasible and effective in chronic stroke survivors: a retrospective data analysis. Top Stroke Rehabil 2008; 15: 247-255.
https://doi.org/10.1310/tsr1503-247 DOI: https://doi.org/10.1310/tsr1503-247
Hesse S, Werner C, Pohl M, Mehrholz J, Puzich U, Krebs HI. Mechanical arm trainer for the treatment of the severely affected arm after a stroke: a single-blinded randomized trial in two centers. Am J Phys Med Rehabil 2008; 87: 779-788.
https://doi.org/10.1097/PHM.0b013e318186b4bc DOI: https://doi.org/10.1097/PHM.0b013e318186b4bc
Burton L, Tyson SF. Screening for cognitive impairment after stroke: a systematic review of psychometric properties and clinical utility. J Rehabil Med 2015; 47: 193-203.
https://doi.org/10.2340/16501977-1930 DOI: https://doi.org/10.2340/16501977-1930
Lord SE, McPherson K, McNaughton HK, Rochester L, Weatherall M. Community ambulation after stroke: how important and obtainable is it and what measures appear predictive? Arch Phys Med Rehabil 2004; 85: 234-239.
https://doi.org/10.1016/j.apmr.2003.05.002 DOI: https://doi.org/10.1016/j.apmr.2003.05.002
Janssen W, Bussmann J, Selles R, Koudstaal P, Ribbers G, Stam H. Recovery of the sit-to-stand movement after stroke: a longitudinal cohort study. Neurorehabil Neural Repair 2010; 24: 763-769.
https://doi.org/10.1177/1545968310363584 DOI: https://doi.org/10.1177/1545968310363584
Bohannon RW. Knee extension strength and body weight determine sit-to-stand independence after stroke. Physiother Theory Pract 2007; 23: 291-297.
https://doi.org/10.1080/09593980701209428 DOI: https://doi.org/10.1080/09593980701209428
Silva P, Franco J, Gusmão A, Moura J, Teixeira-Salmela L, Faria C. Trunk strength is associated with sit-to-stand performance in both stroke and healthy subjects. Eur J Phys Rehabil Med 2015; 51: 717-724.
Lord SR, Murray SM, Chapman K, Munro B, Tiedemann A. Sit-to-stand performance depends on sensation, speed, balance, and psychological status in addition to strength in older people. J Gerontol A Biol Sci Med Sci 2002; 57: M539-M543.
https://doi.org/10.1093/gerona/57.8.M539 DOI: https://doi.org/10.1093/gerona/57.8.M539
Hashimoto K, Higuchi K, Nakayama Y, Abo M. Ability for basic movement as an early predictor of functioning related to activities of daily living in stroke patients. Neurorehabil Neural Repair 2007; 21: 353-357.
https://doi.org/10.1177/1545968306297870 DOI: https://doi.org/10.1177/1545968306297870
Makizako H, Kabe N, Takano A, Isobe K. Use of the Berg Balance Scale to predict independent gait after stroke: a study of an inpatient population in Japan. PM R 2015; 7: 392-399.
https://doi.org/10.1016/j.pmrj.2015.01.009 DOI: https://doi.org/10.1016/j.pmrj.2015.01.009
Atkinson J, Braddick O. Spatial cognition, visuomotor action and attention. In: Farren EK, Karmiloff-Smith A, editors. Neurodevelopmental disorders across the lifespan: a neuroconstructivist approach. Oxford: Oxford University Press; 2012. p. 247-262.
https://doi.org/10.1093/acprof:oso/9780199594818.003.0063 DOI: https://doi.org/10.1093/acprof:oso/9780199594818.003.0063
Moore RT, Piitz MA, Singh N, Dukelow SP, Cluff T. Assessing impairments in visuomotor adaptation after stroke. Neurorehabil Neural Repair 2022; 36: 415-425.
https://doi.org/10.1177/15459683221095166 DOI: https://doi.org/10.1177/15459683221095166
Katz N, Hartman-Maeir A, Ring H, Soroker N. Relationships of cognitive performance and daily function of clients following right hemisphere stroke: predictive and ecological validity of the LOTCA battery. Occup Ther J Res 2000; 20: 3-17.
https://doi.org/10.1177/153944920002000101 DOI: https://doi.org/10.1177/153944920002000101
Cho K, Lee W. Cognitive factors associated with activities of daily living in post-stroke patients. J Phys Ther Sci 2012; 24: 779-782.
https://doi.org/10.1589/jpts.24.779 DOI: https://doi.org/10.1589/jpts.24.779
Kim JW, Byun MS, Sohn BK, Yi D, Seo EH, Choe YM, et al. Clinical dementia rating orientation score as an excellent predictor of the progression to Alzheimer's disease in mild cognitive impairment. Psychiatry Investig 2017; 14: 420.
https://doi.org/10.4306/pi.2017.14.4.420 DOI: https://doi.org/10.4306/pi.2017.14.4.420
Schmidt K, Power MC, Ciarleglio A, Nadareishvili Z, Group IS. Post-stroke cognitive impairment and the risk of stroke recurrence and death in patients with insulin resistance. J Stroke Cerebrovasc Dis 2022; 31: 106744.
https://doi.org/10.1016/j.jstrokecerebrovasdis.2022.106744 DOI: https://doi.org/10.1016/j.jstrokecerebrovasdis.2022.106744
Özdemir F, Birtane M, Tabatabaei R, Ekuklu G, Kokino S. Cognitive evaluation and functional outcome after stroke. Am J Phys Med Rehabil 2001; 80: 410-415.
https://doi.org/10.1097/00002060-200106000-00003 DOI: https://doi.org/10.1097/00002060-200106000-00003
Pedersen PM, Jørgensen HS, Nakayama H, Raaschou HO, Olsen TS. Orientation in the acute and chronic stroke patient: impact on ADL and social activities. The Copenhagen Stroke Study. Arch Phys Med Rehabil 1996; 77: 336-339.
https://doi.org/10.1016/S0003-9993(96)90080-5 DOI: https://doi.org/10.1016/S0003-9993(96)90080-5
Schiemanck SK, Kwakkel G, Post MW, Kappelle LJ, Prevo AJ. Predicting long-term independency in activities of daily living after middle cerebral artery stroke: does information from MRI have added predictive value compared with clinical information? Stroke 2006; 37: 1050-1054.
https://doi.org/10.1161/01.STR.0000206462.09410.6f DOI: https://doi.org/10.1161/01.STR.0000206462.09410.6f
Wurzinger H, Abzhandadze T, Rafsten L, Sunnerhagen KS. Dependency in activities of daily living during the first year after stroke. Front Neurol 2021; 12: 736684.
https://doi.org/10.3389/fneur.2021.736684 DOI: https://doi.org/10.3389/fneur.2021.736684
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