A predictive model for functionality improvement after stroke rehabilitation
Abstract
This study develops a simple predictive model for identifying stroke patients who have a better chance of showing improved activities of daily living (ADL) outcomes following a stroke.
The cohort of 489 stroke patients was divided into testing and training groups. Multivariate logistic regression analysis was conducted for each model. Four models were compared using the C statistic (AUC), Akaike's information criterion (AIC), and other metrics. The best model was assessed using a nomogram.
Univariate analysis revealed that several variables measured significantly higher at discharge than at admission, including manual muscle testing, standing, and so on. Multivariate logistic regression analysis revealed that activities-specific balance confidence, Brunnstrom recovery stage for lower extremities, standing, the mini-balance evaluation systems test, and the Hamilton anxiety scale were independent predictors of ADL. Model 1 was found to be more accurate for the prediction of ADL (AUC: training, 0.916 [0.889−0.943] and test, 0.887 [0.806−0.968]; AIC: training, 257.42 and test, 76.79) than model 2 (AUC: training, 0.850 [0.894−0.806] and test, 0.819 [0.715−0.923]; AIC: training, 314.44 and test, 83.78), model 3 (AUC: training, 0.862 [0.901−0.823] and test, 0.830 [0.731−0.929]; AIC: training, 307.76 and test, 86.55), and model 4 (AUC: training, 0.862 [0.901−0.823] and test, 0.833 [0.733−0.932]; AIC: training, 305.8 and test, 86.28).
A multivariate model can be used to predict functionality improvement, as measured by ADL, following hospitalization with a stroke.
Keywords
Electronic Supplementary Material
References
2016 Stroke Collaborators GBD. Global, regional, and national burden of stroke, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Neurol. 2019;18(5):439–458. https://doi.org/10.1016/S1474-4422(19)30034-1.
Feigin VL, Norrving B, Mensah GA. Global burden of stroke. Circ Res. 2017;120(3):439–448. https://doi.org/10.1161/CIRCRESAHA.116.308413.
Winstein CJ, Stein J, Arena R, et al. Guidelines for adult stroke rehabilitation and recovery: a guideline for healthcare professionals from the American heart association/american stroke association. Stroke. 2016;47(6):e98–e169. https://doi.org/10.1161/STR.0000000000000098.
Hebert D, Lindsay MP, McIntyre A, et al. Canadian stroke best practice recommendations: stroke rehabilitation practice guidelines, update 2015. Int J Stroke. 2016;11(4):459–484. https://doi.org/10.1177/1747493016643553.
Zhang QL, Zhang ZY, Huang XQ, et al. Application of logistic regression and decision tree models in the prediction of activities of daily living in patients with stroke. Neural Plast. 2022;2022:9662630. https://doi.org/10.1155/2022/9662630.
Hartley T, Burger M, Inglis-Jassiem G. Post stroke health-related quality of life, stroke severity and function: a longitudinal cohort study. Afr J Disabil. 2022;11:947. https://doi.org/10.4102/ajod.v11i0.947.
Pinedo S, Erazo P, Tejada P, et al. Rehabilitation efficiency and destination on discharge after stroke. Eur J Phys Rehabil Med. 2014;50(3):323–333.
Karaca O, Sütçü G, Kılınç M. The effects of trunk and extremity functions on activities of daily living, balance, and gait in stroke. Neurol Res. 2023;45(4):312–318. https://doi.org/10.1080/01616412.2022.2142424.
Karthikbabu S, Chakrapani M, Ganeshan S, et al. A review on assessment and treatment of the trunk in stroke: a need or luxury. Neural Regen Res. 2012;7(25):1974–1977. https://doi.org/10.3969/j.issn.1673-5374.2012.25.
Lindmark B, Hamrin E. Evaluation of functional capacity after stroke as a basis for active intervention. Presentation of a modified chart for motor capacity assessment and its reliability. Scand J Rehabil Med. 1988;20(3):103–109.
Franchignoni F, Horak F, Godi M, et al. Using psychometric techniques to improve the balance evaluation systems test: the mini-BESTest. J Rehabil Med. 2010;42(4):323–331. https://doi.org/10.2340/16501977-0537.
Langhorne P, Coupar F, Pollock A. Motor recovery after stroke: a systematic review. Lancet Neurol. 2009;8(8):741–754. https://doi.org/10.1016/S1474-4422(09)70150-4.
Kim JS, Choi-Kwon S, Kwon SU, et al. Factors affecting the quality of life after ischemic stroke: young versus old patients. J Clin Neurol. 2005;1(1):59–68. https://doi.org/10.3988/jcn.2005.1.1.59.
Szczepańska-Gieracha J, Mazurek J. The role of self-efficacy in the recovery process of stroke survivors. Psychol Res Behav Manag. 2020;13:897–906. https://doi.org/10.2147/PRBM.S273009.
French MA, Moore MF, Pohlig R, et al. Self-efficacy mediates the relationship between balance/walking performance, activity, and participation after stroke. Top Stroke Rehabil. 2016;23(2):77–83. https://doi.org/10.1080/10749357.2015.1110306.
French MA, Miller A, Pohlig RT, et al. Depressive symptoms moderate the relationship among physical capacity, balance self-efficacy, and participation in people after stroke. Phys Ther. 2021;101(12):pzab224. https://doi.org/10.1093/ptj/pzab224.
Lin WQ, Huang TY, Liu L, et al. Prevalence and related factors of depression and falls among the elderly living in rural communities of Guangzhou. Psychol Health Med. 2020;25(8):980–988. https://doi.org/10.1080/13548506.2020.1714064.
Koleck M, Gana K, Lucot C, et al. Quality of life in aphasic patients 1 year after a first stroke. Qual Life Res. 2017;26(1):45–54. https://doi.org/10.1007/s11136-016-1361-z.
VanGilder JL, Hooyman A, Peterson DS, et al. Post-stroke cognitive impairments and responsiveness to motor rehabilitation: a review. Curr Phys Med Rehabil Rep. 2020;8(4):461–468. https://doi.org/10.1007/s40141-020-00283-3.
E Wurzinger H, Abzhandadze T, Rafsten L, et al. 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.
Quinn TJ, Langhorne P, Stott DJ. Barthel index for stroke trials: development, properties, and application. Stroke. 2011;42(4):1146–1151. https://doi.org/10.1161/STROKEAHA.110.598540.
Scrutinio D, Lanzillo B, Guida P, et al. Development and validation of a predictive model for functional outcome after stroke rehabilitation: the maugeri model. Stroke. 2017;48(12):3308–3315. https://doi.org/10.1161/STROKEAHA.117.018058.
de Ridder IR, Dijkland SA, Scheele M, et al. Development and validation of the Dutch Stroke Score for predicting disability and functional outcome after ischemic stroke: a tool to support efficient discharge planning. Eur Stroke J. 2018;3(2):165–173. https://doi.org/10.1177/2396987318754591.
Douiri A, Grace J, Sarker SJ, et al. Patient-specific prediction of functional recovery after stroke. Int J Stroke. 2017;12(5):539–548. https://doi.org/10.1177/1747493017706241.
Shah S, Vanclay F, Cooper B. Improving the sensitivity of the Barthel Index for stroke rehabilitation. J Clin Epidemiol. 1989;42(8):703–709. https://doi.org/10.1016/0895-4356(89)90065-6.
Hsieh YW, Wang CH, Wu SC, et al. Establishing the minimal clinically important difference of the Barthel Index in stroke patients. Neurorehabilitation Neural Repair. 2007;21(3):233–238. https://doi.org/10.1177/1545968306294729.
Bohannon RW. Manual muscle testing: does it meet the standards of an adequate screening test? Clin Rehabil. 2005;19(6):662–667. https://doi.org/10.1191/0269215505cr873oa.
Bohannon RW, Smith MB. Interrater reliability of a modified Ashworth scale of muscle spasticity. Phys Ther. 1987;67(2):206–207. https://doi.org/10.1093/ptj/67.2.206.
Shear MK, Vander Bilt J, Rucci P, et al. Reliability and validity of a structured interview guide for the Hamilton Anxiety Rating Scale (SIGH-a). Depress Anxiety. 2001;13(4):166–178.
Fava GA, Kellner R, Munari F, et al. The Hamilton depression rating scale in normals and depressives. Acta Psychiatr Scand. 1982;66(1):26–32. https://doi.org/10.1111/j.1600-0447.1982.tb00911.x.
Potts MK, Daniels M, Burnam MA, et al. A structured interview version of the Hamilton Depression Rating Scale: evidence of reliability and versatility of administration. J Psychiatr Res. 1990;24(4):335–350. https://doi.org/10.1016/0022-3956(90)90005-b.
Hamilton M. A rating scale for depression. J Neurol Neurosurg Psychiatry. 1960;23(1):56–62. https://doi.org/10.1136/jnnp.23.1.56.
Nasreddine ZS, Phillips NA, Bédirian V, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment. J Am Geriatr Soc. 2005;53(4):695–699. https://doi.org/10.1111/j.1532-5415.2005.53221.x.
Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models. Med Decis Making. 2006;26(6):565–574. https://doi.org/10.1177/0272989X06295361.
Steyerberg EW, Vergouwe Y. Towards better clinical prediction models: seven steps for development and an ABCD for validation. Eur Heart J. 2014;35(29):1925–1931. https://doi.org/10.1093/eurheartj/ehu207.
Kim JH, Park EY. Balance self-efficacy in relation to balance and activities of daily living in community residents with stroke. Disabil Rehabil. 2014;36(4):295–299. https://doi.org/10.3109/09638288.2013.790488.
Thilarajah S, Mentiplay BF, Bower KJ, et al. Factors associated with post-stroke physical activity: a systematic review and meta-analysis. Arch Phys Med Rehabil. 2018;99(9):1876–1889. https://doi.org/10.1016/j.apmr.2017.09.117.
Löfgren B, Nyberg L, Osterlind PO, et al. In-patient rehabilitation after stroke: outcome and factors associated with improvement. Disabil Rehabil. 1998;20(2):55–61. https://doi.org/10.3109/09638289809166054.
Tyson SF, Hanley M, Chillala J, et al. The relationship between balance, disability, and recovery after stroke: predictive validity of the Brunel Balance Assessment. Neurorehabilitation Neural Repair. 2007;21(4):341–346. https://doi.org/10.1177/1545968306296966.
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