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Motor neuroprosthesis for promoting recovery of function after stroke

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Versión publicada: 29 marzo 2018 Historial de versiones

https://doi.org/10.1002/14651858.CD012991

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Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

To assess the effects of motor neuroprosthesis (MN) for improving activities and participation in people after stroke.

Background

Description of the condition

Among the cardiovascular diseases, haemorrhagic and ischaemic strokes were considered to be the second and third most common causes of disability‐adjusted life‐years, respectively, in 2015 (Roth 2017). They present a higher prevalence among individuals aged 74 to 79 years (Roth 2017). Projections indicate that by 2030 there will be 70 million stroke survivors (Feigin 2014).

Among stroke survivors, approximately one‐third will have functional dependence during the first year after stroke (de Campos 2017), and they will also face long‐term impairment, activity limitation, and reduced participation that will impact not only on their own lives, but also on the lives of their families (Langhorne 2009). One of the important factors that contributes to being unable to live independently is motor impairment by hemiparesis, because it leads to difficulties in performing functional activities (Schiemanck 2006). Lower limb impairment typically affects the performance of gait and it is common to observe foot drop when the individual tries to take a step with the paretic limb (Stein 2008), while upper limb impairment affects the interaction with objects in the environment, involving movements such as grasp, grip, pinch, and others (Lang 2013). In this scenario, the use of contextual factors, such as assistive technology devices (e.g. orthosis), work as a resource to facilitate the performance of daily activities and the recovery of motor function after stroke (Eng 2007).

Description of the intervention

The first application of electric current to nervous tissue in order to promote movement dates back to the experiment of Galvani in the 1790s (Cambridge 1977). Since then, there have been advances in the use of electrical stimulation of motor neurons to activate paralysed or paretic muscles, and it is widely used in clinical rehabilitation (Sheffler 2007). When electrical stimulus is applied to impaired individuals to achieve functional tasks, it is called 'functional electrical stimulation' (FES) (Sheffler 2007). FES is a routine therapeutic approach that physiotherapists use during stroke rehabilitation in a clinical setting to improve strength, upper extremity function, gait, and to prevent hemiplegic shoulder subluxation (Auchstaetter 2016).

Due to technological advances, especially in electronics, electrical stimulation devices have become increasingly miniaturised and lightweight, and with more refined control and sensor configurations, they can be worn as an orthosis beyond the clinical setting (Melo 2015; Popović 2014). By integrating the electric stimulator with control algorithms and sensors, it is possible to determine the time of delivery of the electrical current in response to the sensor signals (Melo 2015). The first time this integration was implemented occurred in 1961 when Liberson applied electrical stimuli to the common peroneal nerve to activate the tibialis anterior muscle during the swing phase of gait. He used a heel switch as a sensor to control the timing of the stimulation. The train of stimuli was only released when the heel came off the ground at the end of the stance phase and ended when the heel contacted the ground again at the beginning of the stance phase (Liberson 1961). Since then, much progress has been made: the devices became portable, battery powered, and wireless, allowing them to be worn and implemented as an assistive technology device (e.g. an orthosis) that acts as an environmental facilitator for expanded capacity and performance in walking and moving and also carrying and handling objects (Bosch 2014; Cowan 2012). In addition to this direct effect on performance, the orthotic use of the electric current enables people with stroke to experience a greater amount of practice in their current environment. This orthotic use is often called 'motor neuroprosthesis' (MN). MN has been known as electronic devices that interface with the nervous system and attempt to restore functions, generally by electrical stimulation (Naik 2014; Ziat 2015).

The activation of neural structures to promote movement through electrical stimulation is used in both MN and FES; because of that, there may be an overlap between FES and MN concepts (Popović 2014). Although MN and FES both use electrical stimulation, MN has a system technology configuration that allows its use in the actual context in which people live (real‐world setting). In this way MN allows the electrical stimulus to be used as an environmental facilitator (e.g. an orthosis) to achieve a greater level of practice, producing effects during the performance of functional abilities in people's current environment (Laufer 2009). Several studies and guidelines already consider comparisons of MN with other orthotic devices for decision‐making purposes (Bethoux 2015; Bosch 2014; Kluding 2014; NICE 2009). Within the scope of this protocol, we will focus on this perspective that MN consists of a category that uses stimuli to allow the performance of tasks in the actual context in which people live, and it is being used daily for increasing the activities and participation of people with stroke, while FES comprises the use of electrical stimulation to enhance function (Martin 2012; Sheffler 2007), and it is especially used in the context of the clinical setting.

To be able to operate autonomously during the performance of functional activities, MN has a typical architecture composed of a network of sensors, control unit, and a stimulation unit (Melo 2015). The stimulation unit is responsible for generating the electric current that is delivered to the nervous system via electrodes placed in different locations, ranging from the skin surface to directly implanted into different areas of the nervous system (Collinger 2013). Regardless of the location of this interface in the nervous system, all devices that stimulate it electrically for the previously described purposes are considered MN. It is possible to use biological signals, such as electromyography, electroencephalography, and electroneurography signals, eye tracking, and voice control, or non‐biological signals such as force/pressure and inertial sensors as an input to trigger the electrical stimulus to the desired motor function (Ambrosini 2014). Therefore, there is a need to translate and to adjust the command signal provided by sensors as an input to the stimulation unit, a function of the control unit (Horch 2004; Naik 2014). Besides the described requirements, the device needs to be portable, lightweight, autonomously controlled, and battery powered to be an assistive technology device (Melo 2015).

How the intervention might work

MN allows people with stroke to enhance the performance of functional activities in the home and community, including the manipulation of objects with the paretic upper limb or gait activities with the paretic lower limb (Cowan 2012; Moss 2011; Sheffler 2009). The use of these assistive devices can lead people with stroke to benefit from their orthotic effect, reflecting the direct improvement in tasks while using the MN (Dunning 2015; Kottink 2004; Prenton 2016). Furthermore, the daily use of MN allows people with stroke to perform repetitive activities that lead to a longer‐lasting improvement (as an effect of relearning), after the stimulation is turned off (Ambrosini 2011; Dunning 2015; Prenton 2016). This is possibly explained by plasticity mechanisms from peripheral effects in muscles and central effects from the central nervous system reorganisation. It is hypothesised that these devices activate the motor‐related areas of the cortex and their residual corticospinal pathways induce neural plasticity in people with stroke (Everaert 2010). Thus far, direct signs of brain injury repair after one year of using the MN in people with chronic stroke was seen by cortical metabolism improvement over the damaged motor areas, leading to recovery of near‐to‐normal brain metabolism (Thibaut 2017).

Why it is important to do this review

The possible overlapping concepts between MN and FES may lead to a fragmented approach to the use of MN as an assistive device, as mentioned in Description of the intervention. Therefore, although some systematic reviews have been conducted on this topic, comparing them to other assistive technology devices, they focused only on devices directed to specific parts of the lower limb (Dunning 2015; Kottink 2004), or the upper limb (Bolton 2004; Meilink 2008), without establishing the current level of evidence for this whole category of upper limb and lower limb MN. It is important to note that some studies refer to these devices as foot drop stimulators, peroneal stimulators, FES‐based neuroprostheses, ElectroMyoGraphic (EMG)‐triggered stimulation, EMG‐controlled functional electrical stimulation neuroprosthesis, and others. Furthermore, only one systematic review considered daily use of these devices, but did not perform a meta‐analysis (Dunning 2015), nor did any review consider the inclusion of studies using hybrid MN, which combines an exoskeleton or a mechanical orthosis with an electrical stimulation device.

Finally, due to the wide variety of MN, there is a need to clarify which device has the best evidence for improving activity and participation after stroke, the best phase in which to use them, the optimal frequency of use, and which target shows the best results. Moreover, to support clinical practice, we need to consider healthcare managers, policy makers, and consumers, and consider the acceptability of using MN, costs, and benefits. This review aims to bring together the evidence for the use of MN for improving activities and participation after stroke and hence to assist clinical decision‐making.

Objectives

To assess the effects of motor neuroprosthesis (MN) for improving activities and participation in people after stroke.

Methods

Criteria for considering studies for this review

Types of studies

We will include published and unpublished randomised controlled trials (RCTs) and randomised controlled cross‐over trials. For randomised controlled cross‐over trials, we will only analyse the first period as a parallel‐group trial. The cross‐over trial will be eligible if comparison groups include placebo, the evaluation of outcomes is blinded to allocation, and a minimum period of follow‐up is clearly described. We will only consider trials reported in abstract form as eligible for inclusion when adequate information is provided in the abstract or is available from the trial authors. We will exclude quasi‐RCTs (QRCTs), that is trials in which the method of allocating participants to a treatment is not strictly random (e.g. by date of birth, hospital record number, or alternation). If we include a study that is described as randomised, but while performing assessment of the risk of bias we find out that it is a QRCT, we will exclude the data from the analysis.

Types of participants

We will include studies with participants over 18 years of age, of both sexes, after stroke at any stage of the disease. A diagnosis of stroke fulfils the clinical criteria of the World Health Organization (WHO). The WHO defines stroke as "rapidly developed clinical signs of focal/global disturbances of cerebral flow clinically lasting for more than 24 hours or leading to death with no other apparent case of vascular origin" (Hatano 1976). A diagnosis of stroke encompasses ischaemic and haemorrhagic stroke (including subarachnoid, intraventricular, or intracerebral haemorrhage).

Types of interventions

This review will include studies that use motor neuroprosthesis (MN) devices for improving activities and participation after stroke. Considering that this approach focuses on its use as an orthosis, we will only include studies that use MN in the home or community context and that fulfil some device requirements, such as working autonomously, be battery powered to ensure its autonomy, and have stimulus triggered by a sensor. We will also include studies using implanted or superficial electrodes whose application is directed to upper or lower limbs, and studies that address hybrid MN, which combine an exoskeleton or a mechanical orthosis with an electrical stimulation device. We will exclude studies that use sensory stimulation as transcutaneous electrical nerve stimulation (TENS).

We will include the following comparisons.

  • MN with electrical stimulus versus no treatment.

  • MN with electrical stimulus versus MN without electrical stimulus, where both groups use the device, but in one group the stimulator is turned off.

  • MN versus another assistive technology device (e.g. foot drop stimulator versus ankle foot orthosis, ElectroMyoGraphic (EMG)‐triggered stimulation versus hand orthosis, etc.).

Types of outcome measures

We will include outcome measures falling into the International Classification of Functioning, Disability and Health (ICF) categories for activity and participation (Brehm 2011; Mudge 2007; Sullivan 2013). According to the ICF, 'activity' corresponds to the execution of a task or action by an individual, while 'participation' means the involvement in a life situation (WHO 2001).

Primary outcomes

Secondary outcomes

  • Participation: e.g. 36‐Item Short Form Health Survey (SF‐36) (Anderson 1996), Stroke Impact Scale (SIS) (Duncan 1999).

  • Exercise capacity: e.g. six‐minute walk test (6MWT) (Seale 2006).

  • Balance: e.g. Berg Balance Scale (BBS) (Berg 1992), and Functional Reach Test (FRT) (Martins 2012).

  • Adverse events, i.e. pain, skin irritation, dropouts, acceptance.

Search methods for identification of studies

See the 'Specialized register' section in the Cochrane Stroke Group module. We will search for trials in all languages and arrange for the translation of relevant articles when necessary.

Electronic searches

We will search in the Cochrane Stroke Group Trials Register and the following electronic bibliographic databases.

  • The Cochrane Central Register of Controlled Trials (CENTRAL) (the Cochrane Library, latest issue).

  • MEDLINE Ovid (from 1946) (Appendix 1).

  • Embase Ovid (from 1974).

  • CINAHL EBSCO (Cumulative Index to Nursing and Allied Health Literature; from 1937).

  • AMED Ovid (Allied and Complementary Medicine; from 1985).

  • PEDro (Physiotherapy Evidence Database; www.pedro.org.au/).

  • Rehabdata (www.naric.com/?q=en/REHABDATA).

  • IEEE (Institute of Electrical and Electronics Engineers; www.ieee.org/index.html).

We developed the MEDLINE search strategy with the help of the Cochrane Stroke Group Information Specialist and will adapt it for the other databases, as necessary (Appendix 1). The search strategy includes Cochrane's highly sensitive search strategies for identification of RCTs, as described in the Cochrane Handbook for Systematic Reviews of Interventions (Lefebvre 2011), and the Cochrane Stroke Group's search strategies for the identification of stroke studies in respective databases and other resources.

We will also search the following electronic registries, databases, and websites to identify additional relevant published, unpublished, and ongoing trials.

Searching other resources

We will screen reference lists of all relevant articles and use Science Citation Index Cited Reference Search for forward tracking of important articles. We will contact experts, equipment manufacturers, and organisations to obtain additional information for any relevant trials. We may contact original authors for clarification and further data if trial reports are unclear.

Data collection and analysis

Selection of studies

Two review authors (LM and IN), working independently, will screen the titles and abstracts of the studies identified from the search strategy and will remove the obviously irrelevant reports. We will obtain the full‐text of the remaining studies and the same two review authors will select studies for inclusion according to the predefined inclusion criteria. In the case of any methodological questions on whether the study meets the inclusion criteria, we will contact the study authors for clarification. Another review author (VR) will evaluate any discrepancies, if necessary, and will advise in case of disagreement. We will record the reasons for exclusion and complete a PRISMA flowchart (Liberati 2009).

Data extraction and management

The same review authors (LM and IN), working independently, will be responsible for extracting and summarising the trials' details using a standard data extraction sheet, and we will then include the data in Review Manager 5 (Review Manager 2014). Where there is incomplete or unclear data, we will contact the study authors for clarification. We will solve any disagreements by discussion with a third review author (VR). According to the methods described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011a), we will extract the following information.

  • General information: title of the review, study ID and contact details.

  • Methods: study design, instruments used, study duration, 'Risk of bias' criteria (sequence generation, allocation concealment, blinding, incomplete outcome data, selective outcome reporting), year of study.

  • Participants: total number of participants, setting, age, sex, country, motor impairment, type of stroke, phase (acute, subacute or chronic).

  • Intervention: intervention details regarding time (number and duration of exposure, weeks of use, and, in the case of follow‐up, describe the duration), devices (type of electrode and sensor), and place of application (upper or lower limb); methods used in the control group.

  • Outcomes: definition of primary and secondary outcome(s).

  • Results: number of participants allocated to each group, number of withdrawals (by group, with reasons), adverse events, overall sample size and methods used to estimate statistical power (regarding the target number of participants to be recruited, the clinical difference to be detected and the ability of the trial to detect this difference).

  • Notes: contact with authors (information obtained or not), article in a language other than English, funding source and noteworthy conflicts of interest of study authors.

Assessment of risk of bias in included studies

Two review authors (LM and IN) will independently assess the risk of bias for each included study, using the 'Risk of bias' tool described in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011b). We will resolve any disagreements by discussion or by involving a third review author (VR). We will assess the risk of bias according to the following domains.

  • Random sequence generation.

  • Allocation concealment.

  • Blinding of participants and personnel.

  • Blinding of outcome assessment.

  • Incomplete outcome data.

  • Selective outcome reporting.

  • Other bias.

We will grade the risk of bias for each domain as of high, low, or uncertain risk of bias. We will then enter this information into the 'Risk of bias' table produced for each study, along with the reason for each decision. We will use Table 8.5.d contained in the Cochrane Handbook for Systematic Reviews of Interventions that provides criteria for making judgements regarding risk of bias in each of the seven domains of the tool (Higgins 2011b). We will consider the risk of bias of the studies and their contributions to the treatment effect.

Measures of treatment effect

We will perform the data analysis according to Cochrane guidelines. One review author (LM) will enter the quantitative data into Review Manager 5 (Review Manager 2014), which will be checked by another review author (IN), and analysed. We will present the outcome results for each trial with 95% confidence intervals (CIs). We will measure treatment effects using the risk ratio (RR) for dichotomous outcomes, mean difference (MD), and overall effect size (with 95% CI calculated) or as standardised mean differences (SMDs) if different methods of measurement are used in the studies for continuous outcomes.

Unit of analysis issues

We will consider the number of individual participants as the unit of analysis in this review. We will include data from cluster‐randomised trials if the information is available. For cluster‐randomised trials, we will adjust the results when the unit of analysis in the trial is presented as the total number of individual participants, instead of the number of clusters. We will adjust results using the mean cluster size and intracluster correlation coefficient (ICC) (Higgins 2011c). We will assess data from cross‐over trials at the cross‐over point, if available. For meta‐analysis, we will combine data from individually randomised trials using the generic inverse variance method, as described in Chapter 16 (section 16.3) of the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011d).

Dealing with missing data

If there are missing data, we will contact the original researchers to request these data whenever possible. When this is not possible, and we consider the missing data might introduce serious bias, we will perform a sensitivity analysis to explore the impact of including such studies in the overall assessment of results.

Assessment of heterogeneity

We will assess heterogeneity visually by observing the non‐overlapping of CIs in the forest plots. Once identified, we will quantify statistical heterogeneity using the Chi² test (P < 0.10) and I² statistic. The I² statistic estimates the percentage of total variation across trials because of heterogeneity, rather than variation because of chance. We will categorise heterogeneity as I² values of 40% or less as indicating a low level of heterogeneity, and values of 75% or above indicating very high heterogeneity (Higgins 2011c).

Assessment of reporting biases

If we identify a sufficient number of studies (i.e. 10 or more), we will perform a funnel plot analysis to assess reporting bias. If asymmetry is present, we will explore possible causes, including publication bias, poor methodological quality, and true heterogeneity.

Data synthesis

Because of the probable heterogeneity of the trials, we will perform a random‐effects meta‐analysis and use the fixed‐effect method as a sensitivity analysis.

GRADE and 'Summary of findings' table

We will grade the quality of the evidence by creating a 'Summary of findings' table using the following outcomes: independence in activities of daily living, activities involving limbs, participation, exercise capacity, balance, and adverse events. We will use the five GRADE considerations (study limitations, consistency of effect, imprecision, indirectness and publication bias) to assess the quality of a body of evidence as it relates to the studies contributing data to the review for the outcomes (Atkins 2004). We will use the GRADEpro Guideline Development Tool to prepare the table (GRADEpro GDT 2015).

We have developed a template 'Summary of findings' table for our first comparison (MN with electrical stimulus versus no treatment) (Table 1). When more than one study is included for the other comparisons (MN with electrical stimulus versus MN without electrical stimulus and MN versus other assistive technology device), we will include additional ‘Summary of findings’ tables for each comparison.

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Table 1. Template for 'Summary of findings' table

Motor neuroprosthesis for promoting recovery of function after stroke

Participants or population: people with stroke

Setting: community or home setting

Intervention: motor neuroprosthesis

Comparison: no treatment

Outcomes

Illustrative comparative risks (95% CI)

Relative effect (95% CI)

No of participants (studies)

Quality of the evidence (GRADE)

Comments

Assumed risk

No treatment

Corresponding
risk

Motor prosthesis

Independence in activities of daily living

Activities involving limbs

Participation

Exercise capacity

Balance

Adverse events

CI: confidence interval

Subgroup analysis and investigation of heterogeneity

We will examine the following subgroup analysis if data are available.

  • Type of effect (first subgroup defined as immediate effect or orthotic effect, i.e. the effect seen while using MN; second subgroup defined as relearn effect, i.e. the effect seen after the stimulation is turned off).

  • Effect of MN when used for varying durations of use of the device (≤ 4 weeks of use, between 5 and 24 weeks of use, ≥ 25 weeks of use).

  • Effect of MN when used by participants of different phases of disease (< 3 months, ≥ 3 months).

  • Effect of MN with surface or implantable electrodes.

  • Effect of MN when applied on lower limb or upper limb.

We will use random‐effects methods to produce this subgroup analysis for primary outcomes only.

Sensitivity analysis

We will use Cochrane's tool for assessing risk of bias to judge the study methods (Higgins 2011b). We will perform sensitivity analyses to assess the robustness of our results. We will remove studies with a high risk of bias in one or more of these three domains: random sequence generation, allocation concealment, and blinding of outcome assessors.

Table 1. Template for 'Summary of findings' table

Motor neuroprosthesis for promoting recovery of function after stroke

Participants or population: people with stroke

Setting: community or home setting

Intervention: motor neuroprosthesis

Comparison: no treatment

Outcomes

Illustrative comparative risks (95% CI)

Relative effect (95% CI)

No of participants (studies)

Quality of the evidence (GRADE)

Comments

Assumed risk

No treatment

Corresponding
risk

Motor prosthesis

Independence in activities of daily living

Activities involving limbs

Participation

Exercise capacity

Balance

Adverse events

CI: confidence interval
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Table 1. Template for 'Summary of findings' table
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