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一种改善功能性记忆的多维虚拟现实神经康复方法:谁是理想人选?

A Multidimensional Virtual Reality Neurorehabilitation Approach to Improve Functional Memory: Who Is the Ideal Candidate?

作者信息

Di Tella Sonia, Isernia Sara, Pagliari Chiara, Jonsdottir Johanna, Castiglioni Carlotta, Gindri Patrizia, Gramigna Cristina, Canobbio Samuela, Salza Marco, Molteni Franco, Baglio Francesca

机构信息

IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.

Fondazione Opera San Camillo Presidio Sanitario San Camillo, Turin, Italy.

出版信息

Front Neurol. 2021 Jan 14;11:618330. doi: 10.3389/fneur.2020.618330. eCollection 2020.

Abstract

We aimed to identify the significant predictors of ecological memory amelioration after the Human Empowerment Aging and Disability (HEAD) rehabilitation program, a multidimensional treatment for chronic neurological diseases. Ninety-three patients with Parkinson disease ( = 29), multiple sclerosis ( = 26), and stroke ( = 38) underwent a multidimensional rehabilitation. We focused on changes after treatment on ecological memory (outcome measure) evaluated by Rivermead Behavioral Memory Test, Third Edition (RBMT-3). Minimal clinically important difference (MCID) after treatment were calculated for RBMT-3. The change score on RBMT-3 was categorized in positive effect, stabilization, or no effect of the treatment. Random forest classification identified who significantly benefited from treatment against who did not in terms of ecological memory functioning. Accordingly, logistic regression models were created to identify the best predictors of the treatment effect. A predicted probability value was derived, and the profile of the ideal candidate of HEAD protocol was shown by combining different ranks of significant predictors in a 3 × 3 matrix for each pair of predictors. A significant number of cases reported positive effect of the treatment on ecological memory, with an amelioration over the MCID or a stabilization. The random forest analysis highlighted a discrete accuracy of prediction (>0.60) for all the variables considered at baseline for identifying participants who significantly benefited and who did not from the treatment. Significant logistic regression model (Wald method) showed a predictive role of Montreal Cognitive Assessment (MoCA; = 0.007), 2Minute Walk Test (2MWT; = 0.038), and RBMT-3 ( < 0.001) at baseline on HEAD treatment effect. Finally, we observed a high probability of success in people with higher residual cognitive functioning (MoCA; odds ratio = 1.306) or functional mobility (2MWT; odds ratio = 1.013). The HEAD program is a rehabilitation with effects on multiple domains, including ecological memory. Residual level of cognitive and/or motor functioning is a significant predictor of the treatment success. These findings confirm the intrinsic relationship subsisting between motor and cognitive functions and suggest the beneficial effects of physical activity on cognitive functions and .

摘要

我们旨在确定人类赋权衰老与残疾(HEAD)康复计划(一种针对慢性神经疾病的多维治疗方法)后生态记忆改善的显著预测因素。93例帕金森病患者(n = 29)、多发性硬化症患者(n = 26)和中风患者(n = 38)接受了多维康复治疗。我们关注通过Rivermead行为记忆测试第三版(RBMT-3)评估的治疗后生态记忆(结果指标)的变化。计算了RBMT-3治疗后的最小临床重要差异(MCID)。RBMT-3的变化分数被分类为治疗的积极效果、稳定或无效果。随机森林分类确定了在生态记忆功能方面哪些人从治疗中显著受益,哪些人没有。因此,创建了逻辑回归模型以确定治疗效果的最佳预测因素。得出了预测概率值,并通过在一个3×3矩阵中组合每对预测因素的不同显著预测因素等级,展示了HEAD方案理想候选者的概况。大量病例报告了治疗对生态记忆的积极效果,改善超过了MCID或达到了稳定。随机森林分析强调了在基线时考虑的所有变量对于识别哪些参与者从治疗中显著受益和哪些参与者没有受益具有离散的预测准确性(>0.60)。显著的逻辑回归模型(Wald方法)显示,基线时蒙特利尔认知评估(MoCA;p = 0.007)、2分钟步行测试(2MWT;p = 0.038)和RBMT-3(p < 0.001)对HEAD治疗效果具有预测作用。最后,我们观察到残余认知功能较高(MoCA;优势比 = 1.306)或功能活动能力较高(2MWT;优势比 = 1.013)的人成功的概率较高。HEAD计划是一种对包括生态记忆在内的多个领域有影响的康复治疗。认知和/或运动功能的残余水平是治疗成功的显著预测因素。这些发现证实了运动和认知功能之间存在的内在关系,并表明身体活动对认知功能的有益影响。

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