Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Jun 10:12:661816.
doi: 10.3389/fneur.2021.661816. eCollection 2021.

Analysis of Prognostic Risk Factors Determining Poor Functional Recovery After Comprehensive Rehabilitation Including Motor-Imagery Brain-Computer Interface Training in Stroke Patients: A Prospective Study

Affiliations

Analysis of Prognostic Risk Factors Determining Poor Functional Recovery After Comprehensive Rehabilitation Including Motor-Imagery Brain-Computer Interface Training in Stroke Patients: A Prospective Study

Qiong Wu et al. Front Neurol. .

Abstract

Objective: Upper limb (UL) motor function recovery, especially distal function, is one of the main goals of stroke rehabilitation as this function is important to perform activities of daily living (ADL). The efficacy of the motor-imagery brain-computer interface (MI-BCI) has been demonstrated in patients with stroke. Most patients with stroke receive comprehensive rehabilitation, including MI-BCI and routine training. However, most aspects of MI-BCI training for patients with subacute stroke are based on routine training. Risk factors for inadequate distal UL functional recovery in these patients remain unclear; therefore, it is more realistic to explore the prognostic factors of this comprehensive treatment based on clinical practice. The present study aims to investigate the independent risk factors that might lead to inadequate distal UL functional recovery in patients with stroke after comprehensive rehabilitation including MI-BCI (CRIMI-BCI). Methods: This prospective study recruited 82 patients with stroke who underwent CRIMI-BCI. Motor-imagery brain-computer interface training was performed for 60 min per day, 5 days per week for 4 weeks. The primary outcome was improvement of the wrist and hand dimensionality of Fugl-Meyer Assessment (δFMA-WH). According to the improvement score, the patients were classified into the efficient group (EG, δFMA-WH > 2) and the inefficient group (IG, δFMA-WH ≤ 2). Binary logistic regression was used to analyze clinical and demographic data, including aphasia, spasticity of the affected hand [assessed by Modified Ashworth Scale (MAS-H)], initial UL function, age, gender, time since stroke (TSS), lesion hemisphere, and lesion location. Results: Seventy-three patients completed the study. After training, all patients showed significant improvement in FMA-UL (Z = 7.381, p = 0.000**), FMA-SE (Z = 7.336, p = 0.000**), and FMA-WH (Z = 6.568, p = 0.000**). There were 35 patients (47.9%) in the IG group and 38 patients (52.1%) in the EG group. Multivariate analysis revealed that presence of aphasia [odds ratio (OR) 4.617, 95% confidence interval (CI) 1.435-14.860; p < 0.05], initial FMA-UL score ≤ 30 (OR 5.158, 95% CI 1.150-23.132; p < 0.05), and MAS-H ≥ level I+ (OR 3.810, 95% CI 1.231-11.790; p < 0.05) were the risk factors for inadequate distal UL functional recovery in patients with stroke after CRIMI-BCI. Conclusion: We concluded that CRIMI-BCI improved UL function in stroke patients with varying effectiveness. Inferior initial UL function, significant hand spasticity, and presence of aphasia were identified as independent risk factors for inadequate distal UL functional recovery in stroke patients after CRIMI-BCI.

Keywords: motor-imagery brain-computer interface; regression analysis; rehabilitation; stroke; upper limb.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Experimental flow chart.
Figure 2
Figure 2
Improvement of 73 patients after treatment.
Figure 3
Figure 3
(A–C) UL function improvement in groups. Although the overall FMA-UL score improved, the FMA-WH scores in two patients regressed after training in IG. *p < 0.05, **p < 0.01.
Figure 4
Figure 4
(A–D) Univariate analysis of characteristics. Cross graph of groups and classification for p < 0.05, **p < 0.01.

Similar articles

Cited by

References

    1. Aparicio HJ, Himali JJ, Satizabal CL, Pase MP, Romero JR, Kase CS, et al. . Temporal trends in ischemic stroke incidence in younger adults in the Framingham study. Stroke. (2019) 50:1558–60. 10.1161/STROKEAHA.119.025171 - DOI - PMC - PubMed
    1. Woytowicz EJ, Rietschel JC, Goodman RN, Conroy SS, Sorkin JD, Whitall J, et al. . Determining levels of upper extremity movement impairment by applying a cluster analysis to the Fugl-Meyer assessment of the upper extremity in chronic stroke. Arch Phys Med Rehabil. (2017) 98:456–62. 10.1016/j.apmr.2016.06.023 - DOI - PMC - PubMed
    1. Carino-Escobar RI, Carrillo-Mora P, Valdés-Cristerna R, Rodriguez-Barragan MA, Hernandez-Arenas C, Quinzaños-Fresnedo J, et al. . Longitudinal analysis of stroke patients' brain rhythms during an intervention with a brain-computer interface. Neural Plast. (2019) 2019:1–11. 10.1155/2019/7084618 - DOI - PMC - PubMed
    1. Várkuti B, Guan C, Pan Y, Phua KS, Ang KK, Kuah CW, et al. . Resting state changes in functional connectivity correlate with movement recovery for BCI and robot-assisted upper-extremity training after stroke. Neurorehabil Neural Repair. (2013) 27:53–62. 10.1177/1545968312445910 - DOI - PubMed
    1. Ramos-Murguialday A, Broetz D, Rea M, Läer L, Yilmaz O, Brasil FL, et al. . Brain-machine interface in chronic stroke rehabilitation: a controlled study. Ann Neurol. (2013) 74:100–8. 10.1002/ana.23879 - DOI - PMC - PubMed

LinkOut - more resources