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Record W4396705775 · doi:10.1002/mus.28108

Understanding the role of the lower motor neuron in spinal cord injury and its impact on electrodiagnostic assessment

2024· editorial· en· W4396705775 on OpenAlexaff
Lawrence R. Robinson, Jana Dengler

Bibliographic record

VenueMuscle & Nerve · 2024
Typeeditorial
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsToronto Rehabilitation InstituteUniversity of Toronto
Fundersnot available
KeywordsMotor neuronSpinal cordSpinal cord injuryMedicinePhysical medicine and rehabilitationNeuroscienceLower motor neuronPsychology

Abstract

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In the accompanying article in this month's journal, Debenham et al.1 provide important information discussing the complex nature of spinal cord injury (SCI) and the greater extent of involvement of the lower motor neuron (LMN) than had previously been considered. As a consequence of this enhanced understanding, it is apparent that electrodiagnostic (EDx) medical consultants (EMCs) will likely play an increasing role in the assessment, prognostication, and treatment planning for persons with SCI (pwSCI). Many have thought of SCI as a predominantly upper motor neuron (UMN) injury, with perhaps a narrow zone of LMN loss at the site of spinal cord trauma. But, as suggested in this review, it is becoming clear that we should now consider SCI in the “metameric” or three-zone model, extending both above and below the level of injury. Readers who commonly see pwSCI will recall that the level of injury is typically determined by strength testing of key muscles, requiring a Medical Research Council (MRC) strength of at least 3/5 at the assigned level with normal strength in more rostral myotomes.2 For example in a person with C6 SCI, biceps would have MRC strength of 5, and wrist extensors would have strength of at least 3, with more severe weakness in more caudal levels. This approach is useful in that it approximates the upper extent of the zone of injury, in which there is LMN loss. This zone of injury then extends for a variable distance caudally along the spinal cord; in fact, it is often asymmetric and heterogeneous. The lower extent of the zone of injury is much more challenging to ascertain with clinical measures, such as strength testing. While spasticity and atrophy may offer some clues, EDx testing is often required. In the metameric model (best shown in Figure 2 in the accompanying paper), for a small extent above the perceived level of injury, strength is relatively normal, but there may be some partial loss of LMNs. Within the zone of injury, there is extensive LMN loss; muscles supplied by LMNs in this zone will essentially undergo denervation changes typical of a peripheral nerve injury. Below the zone of injury (the sublesional zone), the impairment is usually considered a predominantly UMN injury. However, Debenham et al offer some interesting evidence for LMN impairment even in the lower limbs of individuals with a cervical SCI. It is possible that “transsynaptic degeneration” could result in some LMN loss even below the zone of injury; transsynaptic degeneration, to quote the authors, is “an umbrella term for several pathophysiological processes theorized to occur in response to the loss of supraspinal input to the motor neuron pool.” With the adoption of the metameric model, we now need to consider the evaluation and management of SCI in the context of LMN loss, using methods we would typically use in patients with LMN lesions. As discussed in the article, compound muscle action potentials (CMAPs), for example, are important measures of LMN loss and provide insight into prognosis for strength recovery. Because there is often distal axon sprouting in SCI, just as there is in peripheral nerve injuries the CMAP may grow without any corresponding increase in axons and obscure the loss of axons. Thus motor unit number estimates may be required to estimate the number of surviving LMNs supplying a muscle. Needle electromyography may show evidence of denervation not only within the zone of injury but also sometimes in both rostral and caudal segments. At the same time, these approaches are complemented with electrophysiologic techniques to assess the UMN, such as motor evoked potentials. Understanding the impact of SCI on the LMN is not of purely academic interest. Nerve transfers have been a “game changer” in the treatment of pwSCI, and may provide critical hand function to persons who previously had little or none.3 For example, in a person with C6 SCI, the three common nerve transfers discussed involve taking a nerve from a redundant muscle above the level of injury and transferring those axons, via an end-to-end coaptation, to a nonfunctional muscle below the level of injury. These three most common transfers include the following: (1) branch of musculocutaneous nerve to brachialis transferred to anterior interosseous nerve (for finger flexion); (2) branch of radial nerve to supinator transferred to posterior interosseous nerve (for finger extension); and (3) branch of axillary nerve to posterior head of deltoid transferred to radial nerve branch to triceps (for elbow extension). But these life-changing nerve procedures cannot be performed in isolation. They require a start-to-finish programmatic approach that starts with patient identification by surgeons and SCI physicians and teams, and extends through surgery to immediate postoperative care and eventually to rehabilitation.4, 5 The EMC is a critical part of the team. Preoperatively, EDx studies are essential for surgical planning. EMCs may identify coexisting peripheral nervous system (PNS) injuries such as brachial plexopathies or isolated nerve injuries that may have been incurred at the time of the initial trauma. Furthermore, at times patients may also have entrapment neuropathies or peripheral polyneuropathies that need to be treated and considered in surgical planning. Perhaps most importantly, preoperative EDx studies can help to identify whether the intended recipient muscle has suffered an LMN injury (i.e., is within the zone of injury) or is in the sublesional zone and has predominantly UMN weakness. When recipient muscles have suffered a LMN injury, then there is a time-sensitivity to performing nerve transfers, just as there is in PNS injuries; preferably surgery would occur by 6 months after injury so that axons can reach recipient muscles before the muscle undergoes irreversible atrophy at 12–18 months.6, 7 The CMAP amplitude from the recipient muscle is the best determinant of whether the muscle is within the zone of injury and has undergone LMN loss.8 Furthermore, EDx studies may be used to assess potential donor muscles, and confirm the health of redundant muscles to ensure that nerve transfers are not taking away the only elbow flexor, supinator, or shoulder abductor. It is only after a complete set of EDx studies that surgical planning for nerve transfers can effectively occur.4, 5 After nerve transfers, EDx studies are important to detect and assess nerve growth in the recipient muscle. The time required for axons to reach muscle will depend upon the distance they need to grow to reach motor endplates. When they first arrive, nascent motor unit action potentials are usually first detected with donor activation, before any meaningful movement can be detected clinically; this provides important feedback to both the patient and the treatment team as it indicates a favorable prognosis and can guide rehabilitation.9, 10 Donor activation focused rehabilitation is started soon after surgery before there is reinnervation of recipient muscles. This first phase of rehabilitation involves activating the donor muscle(s) frequently in an effort to encourage neural activation and growth. These exercises are subsequently enhanced to add passive or assisted recipient muscle contractions to aid in forming new neural pathways between donor and recipient functions.11 When EDx indicates that the nerve has reached muscle, the patient progresses to the next phase of rehab; at that point, the patient is taught how to use donor activation to contract the newly reinnervated muscle and ultimately how to generate isolated functional movements. EDx information can also be part of the process for helping our surgical colleagues to better understand their surgical successes and failures, with an ultimate goal of improving the quality and outcomes. In summary, an improved understanding of LMN involvement in SCI is critical to the planning and interpretation of EDx studies in pwSCI. We are still at a relatively early stage of understanding the relative contributions of the UMN and LMN in these individuals, as well as how to best use EDx information to guide patient selection and surgical planning for nerve transfer surgery. The review article from Debenham et al.1 is a very good start to enhance our understanding of LMN involvement in SCI, which will ultimately improve the ability of EMCs, peripheral nerve surgeons, and rehabilitation professionals to contribute meaningfully to the care of pwSCI. Lawrence R. Robinson: Conceptualization; writing—original draft. Jana Dengler: Conceptualization; writing—review and editing. None of the authors has any conflict of interest to disclose. No data were created.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.531
Threshold uncertainty score0.777

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.281
Teacher spread0.265 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Published2024
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