Clinical trial NCT06463418: Exoskeleton Training for Spinal Cord Injury Neuropathic Pain (ExSCIP)
Official title: Exoskeleton Training for Spinal Cord Injury Neuropathic Pain (ExSCIP): Protocol for a Phase 2 Feasibility Randomised Trial
Study type: INTERVENTIONAL
Overall status: RECRUITING
Phase: NA
Conditions: Traumatic Spinal Cord Injury
Keywords: Spinal Cord Injuries
Robotics
Pain
Neurorehabilitation
Adult
Neuropathic Pain
Lead sponsor: University College Dublin
Sponsor class: OTHER
Collaborators: name: Royal College of Surgeons, Ireland
name: University of Aarhus
First posted: 2024-06-17
Enrollment: 40
Sex: ALL
Minimum age (years): 18
Maximum age (years): 90
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: TREATMENT

Brief summary: The goal of this feasibility trial is to learn if exoskeleton or robotic walking works to reduce nerve (neuropathic) pain after spinal cord injury.

This study asks is:

* Providing walking practice through use of a robotic device (exoskeleton) three times per week for twelve weeks possible to deliver?
* Would people sign up and stick to the programme?
* And will it help to reduce neuropathic pain levels after spinal injury?

Researchers will compare robotic walking and a relaxation program to see if robotic walking works to reduce neuropathic pain levels after spinal injury.

Participants will:

* Complete a number of questionnaires and tests related to their pain before the trial.
* Complete robotic walking or a relaxation program three times per week for twelve weeks.
* Complete the same questionnaires and tests after the trial finishes and 6 months after.
* Complete an interview telling researchers about their experiences of the trial.

Detailed description: Background and Rationale:

Following SCI, approximately 53% of people develop neuropathic pain (NP). Irish SCI data identifies high pain intensity and pain interference levels with NP and significantly poorer quality of life (QoL) than other pain phenotypes. Individuals can describe NP as more debilitating than the other consequences of SCI, as their most persistent health issue and adequate pain relief as an unmet need.

International data identify the proportional burden of NP following SCI as significant. Ninety-four percent of individuals are prescribed \>1 medication, the mean number of physician office visits in a 6-month period due to SCI NP is reported as 2 and the total annualised cost of NP per subject in the United States (US) is reported as $26,270 (direct $8,636, indirect $17,634).

The presence of pain is further associated with lower return to work rates following injury, and more than a third of individuals with SCI in employment report frequent pain interference with their work . Pain interference with function, health status and work are noted to be significantly worse in individuals with more severe NP, where overall work impairment is reported at 38%.

NP after SCI is multi-faceted and heterogenous, making isolation of specific mechanisms more challenging. Mechanisms hypothesised for NP after SCI include neuronal hyperexcitability (central and peripheral sensitisation) and corticothalamic maladaptive neuroplasticity. Additionally, NP symptom severity post SCI has been reported to be associated with a combination of residual spinothalamic tract (STT) function below the level of injury and with catastrophising pain coping mechanisms.

The mechanistic effects of sensorimotor stimulation on NP stem from Phantom Limb Pain research (PLP) with significant reversal of cortical dysfunction in the primary somatosensory cortex of individuals with PLP evident. Similar maladaptive cortical reorganisation is hypothesised to be associated with NP in SCI.

This is further supported by data garnered from electroencephalography (EEG) studies showing that changes in oscillatory brain activity known as thalamo-cortical dysrhythmia, are associated with the presence of NP. NP in SCI is associated with an EEG power signal increase in the theta band and possibly high beta band but a decrease in the high-alpha-low-beta band. In addition, NP in SCI is associated with decreased reactivity of alpha band power signals in response to eye opening. Thus it has applications as a biomarker for current NP and as a predictor of development of future NP.

The mainstay of NP treatment after SCI is pharmacotherapy with anticonvulsants and antidepressants to reduce pain intensity. Pregabalin/gabapentin, duloxetine, amitriptyline and/or opioids are the first- and second-line treatments recommended, although severe pain remains refractory to these treatments in 2⁄3 of sufferers. Survey data report high use of non-steroidal anti-inflammatories and paracetamol.

Significant side-effects of medications are reported. SCI patients are particularly prone to central nervous system related side effects which are often intolerable. These, together with fear of medication dependency, result in poor adherence to pharmacological regimens leading to a call for non-pharmacological treatment options for people with NP after SCI.

Virtual reality (immersive virtual walking virtual illusion/imagined walking) has shown promise for reducing NP intensity and interference after SCI. Virtual illusion interventions show evidence of direct and corrective stimulation to the reorganised sensorimotor areas in SCI patients with NP, supporting the theory that NP mechanisms are reversible. However, actual sensorimotor intervention studies are inconclusive in SCI at this point with limited focus on walking despite compelling preclinical studies showing prevention and/or reversal of SCI neuropathic pain. Notably in animal studies, other exercise paradigms including swimming and stance training had only transient or no effects on SCI-induced NP suggesting that the rhythmic stimulation of proprioceptive and mechanosensory afferents together with weight bearing experienced in walking might be necessary to reduce NP.

The exoskeleton intervention itself is not new within the neurorehabilitation space for SCI. However, no RCTs to date have specifically recruited participants with moderate-to-severe NP in order to assess its mechanistic effects on NP. The ExSCIP randomised feasibility trial addresses this current knowledge gap, examining exoskeleton-based walking 3 times per week, as a mechanistic-based intervention for NP after SCI. It will test the feasibility and acceptability of an exoskeleton, and whether it demonstrates positive signals in reduction of NP intensity and interference levels to warrant onward progression to a definitive trial.

Aims and Objectives:

The overall aim of this study is to examine the feasibility and acceptability of an exoskeleton, mechanistic-targeted, walking intervention for NP in people with SCI.

The primary objectives for the study are:

1. Implement an exoskeleton training programme for people with below level NP \> 6 months after a traumatic SCI.
2. Pilot and assess the impact of an exoskeleton-based walking intervention in NP \> 6 months after SCI, examining feasibility outcomes and short and long-term (6 months) changes in pain intensity and pain interference.

The ExSCIP study is a phase 2 randomised, single blinded, feasibility trial with the aim of examining progression criteria for a definitive trial.

Progression criteria are based on consideration of the primary objectives around feasibility and the potential for effectiveness and implementation in clinical practice. Quantitative and qualitative process evaluation data will be analysed to consider the following continuation criteria.

* Successful uptake, recruitment, and retention.
* Successful implementation of the ExSCIP intervention.
* Process evaluation indicates that ExSCIP is acceptable to people with NP after SCI and to staff delivering the intervention.
* A positive effect on pain and pain interference outcomes are identified and are meaningful.
* Cost analysis indicates that the ExSCIP intervention might be cost effective. The intervention will be delivered in the Motion Analysis Laboratory at University College Dublin (UCD).

Participant Screening:

Stage 1: Phone Screening:

NP will be screened for as a minimum criterion initially by phone. This phone screening will do the following:

* Confirm their SCI diagnosis (e.g. traumatic aetiology and \>6 months post injury).
* Confirm they are on a stable medication regimen.
* Confirm they are exoskeleton naïve.
* Screen for the presence of NP using the Spinal Cord Injury Pain Instrument (SCIPI).
* Inquire into anthropometric details, e.g. the candidate's height and weight to give further indication relating to their potential suitability/compatibility with the exoskeleton.
* Once the phone screening has been completed, candidates deemed to be potentially suitable to participate in the trial will be booked in for an in-person assessment. Potential participants will be provided with a study information leaflet at this point and informed consent will be sought from participants to complete an in-person assessment. A 1 week grace period will be given to participants between provision of the study information leaflet and obtaining informed consent.

Stage 2: In-Person Assessment:

An in-person assessment to confirm participant suitability will be performed by an independent assessor. The assessment will entail the following steps:

Confirmation of presence of moderate to severe below level NP:

* NP will be confirmed based on a neurological examination, a score of ≥4 on the Douleur Neuropathique 4 (DN4) and a comprehensive pain history.
* This will be supported by the use of the ISCIP Pain Classification.
* Moderate and severe NP as confirmed above will be described as pain ≥ 3 and ≥ 6 on the 0-10 Numerical Rating Scale (NRS) for NP (averaged over a week).

Anthropometric and clinical assessment for compatibility for use of exoskeleton:

- Participants will undergo an anthropometric assessment to ensure no height, weight, joint range of movement or muscle spasticity restrictions to exoskeleton use apply.

Stage 3: Informed consent and data collection:

* Candidates who meet inclusion criteria will be provided with a study information leaflet (see Figure 2) and asked to provide written informed consent that they agree to participate in the study via a consent form.
* The independent assessor will then collect data at baseline for the outcome measures outlined: (Please refer to outcomes section for full details):

Data/statistical analysis:

Descriptive statistics and estimation using 95% CIs will be the main focus of the analysis. The number of participants recruited and retained, and information on missing or incomplete data from all outcome measures will be explored. Baseline demographics and outcome variables will be compared at all assessment times within groups.

For categorical measures, frequencies and percentages will be presented and for continuous measures, the mean and standard deviation (SD) will be reported. For continuous measures which show evidence of some skew a median and interquartile range may also be presented or substituted for the mean and SD. Within group change scores and their 95% CI will be examined in relation to the MCID. Repeated measures ANOVAs will be used to compare between group differences of continuous variables across the three time points. Statistical significance will be determined α-priori at an alpha level of 0.05.

For analysis of EEG data, this will be an exploratory analysis using a multilevel linear mixed model (LMM) approach to examine differences between the intervention groups over time in the EEG alpha, beta and theta band power. Repeated measures within participants will be modelled as a random effect. Fixed effects in the model, will include group assignment and time. The moderating effects of pain intensity and interference will also be evaluated. The LMM will study both main effects and interaction effects using the R package lme4 to fit the models. Models will be compared using Likelihood Ratio Tests (LRT) to assess the significance of effects. Statistical significance will be determined α-priori at an alpha level of 0.05.

When all data is collected, data analysis will be conducted by a data processor blinded to group allocation. A full statistical analysis plan will be prepared prior to final analysis. Statistical analysis will be conducted using SPSS version 29 software and analysis will be conducted as intention to treat (ITT) and per protocol.

Eligibility criteria: Inclusion Criteria:

* Individuals who are 18 years and over.
* Confirmed traumatic SCI (injury resulted from an external physical impact and not an acute or chronic disease process) of \>6 months duration with complete or incomplete paraplegia or tetraplegia.
* Individuals with above confirmed traumatic SCI who have below-level NP (≥ 3 levels below neurological level and/or extending to at-level region) starting after the SCI and persisting for \> 3 continuous months, despite pharmacotherapy.
* NP will be confirmed based on a neurological examination, a score of ≥4 on the Douleur Neuropathique 4 (DN4) (48) and a comprehensive pain history supported by the use of the ISCIP Pain Classification. They endorse one or more of the following pain descriptors to assist in confirmation of below level NP "'hot-burning', 'tingling', 'pricking', 'pins and needles', 'sharp', 'shooting', 'squeezing', 'painful cold' and 'electric shock-like'" (45).
* Moderate and severe NP as confirmed above will be described as pain ≥ 3 and ≥ 6 on the 0-10 Numerical Rating Scale (NRS) for NP (averaged over a week).
* Exoskeleton naive
* Stable medication regimen
* Have the capacity to provide informed consent.

Exclusion Criteria:

* Non-traumatic SCI, cauda equina lesions or Guillain Barré diagnoses
* NP intensities of \<3 (NRS) or nociceptive pain profiles only based on the ISCIP pain classification convention.
* Recent lower limb fracture
* Inadequate bone density (z score \< -2)
* Anthropometric measurements incompatible with the exoskeleton device (i.e. height \>1.9m, weight \>100kgs, significant lower limb spasticity)
* Unstable comorbid medical condition/psychiatric condition/medication regimen
* Planned surgery coinciding with intervention
* Pregnancy
* Drug and alcohol abuse

Primary outcomes:
measure: International Spinal Cord Injury Pain Basic Data Set Version 3.0 (ISCIPBDS 3.0) (Pain intensity)
timeFrame: This will be measured at baseline, week 13 and at 6-month follow-up.
measure: International Spinal Cord Injury Pain Basic Data Set Version 3.0 (ISCIPBDS 3.0) (Pain interference)
timeFrame: This will be measured at baseline, week 13 and at 6-month follow-up.
Secondary outcomes:
measure: Neuropathic Pain Symptom Inventory (NPSI)
timeFrame: This will be measured at baseline, week 13 and at 6-month follow-up.
measure: Electroencephelography (EEG)
timeFrame: This will be measured at baseline, week 13 and at 6-month follow-up.
Other outcomes:
Locations:
city: Dublin
country: Ireland
facility: University College Dublin
Study officials:
affiliation: University College Dublin
name: Olive Lennon, PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Burke D, Fullen BM, Stokes D, Lennon O. Neuropathic pain prevalence following spinal cord injury: A systematic review and meta-analysis. Eur J Pain. 2017 Jan;21(1):29-44. doi: 10.1002/ejp.905. Epub 2016 Jun 24.
citation: Finnerup NB, Norrbrink C, Trok K, Piehl F, Johannesen IL, Sorensen JC, Jensen TS, Werhagen L. Phenotypes and predictors of pain following traumatic spinal cord injury: a prospective study. J Pain. 2014 Jan;15(1):40-8. doi: 10.1016/j.jpain.2013.09.008. Epub 2013 Oct 1.
citation: Burke D, Lennon O, Fullen BM. Quality of life after spinal cord injury: The impact of pain. Eur J Pain. 2018 Oct;22(9):1662-1672. doi: 10.1002/ejp.1248. Epub 2018 Jun 25.
citation: Burke D, Fullen BM, Lennon O. Pain profiles in a community dwelling population following spinal cord injury: a national survey. J Spinal Cord Med. 2019 Mar;42(2):201-211. doi: 10.1080/10790268.2017.1351051. Epub 2017 Jul 24.
citation: Hearn JH, Cotter I, Fine P, A Finlay K. Living with chronic neuropathic pain after spinal cord injury: an interpretative phenomenological analysis of community experience. Disabil Rehabil. 2015;37(23):2203-11. doi: 10.3109/09638288.2014.1002579. Epub 2015 Jan 20.
citation: Kennedy P, Lude P, Taylor N. Quality of life, social participation, appraisals and coping post spinal cord injury: a review of four community samples. Spinal Cord. 2006 Feb;44(2):95-105. doi: 10.1038/sj.sc.3101787.
citation: Siddall PJ. Management of neuropathic pain following spinal cord injury: now and in the future. Spinal Cord. 2009 May;47(5):352-9. doi: 10.1038/sc.2008.136. Epub 2008 Nov 11.
citation: Mann R, Schaefer C, Sadosky A, Bergstrom F, Baik R, Parsons B, Nalamachu S, Stacey BR, Tuchman M, Anschel A, Nieshoff EC. Burden of spinal cord injury-related neuropathic pain in the United States: retrospective chart review and cross-sectional survey. Spinal Cord. 2013 Jul;51(7):564-70. doi: 10.1038/sc.2013.34. Epub 2013 Apr 16.
citation: Widerstrom-Noga EG, Felipe-Cuervo E, Yezierski RP. Relationships among clinical characteristics of chronic pain after spinal cord injury. Arch Phys Med Rehabil. 2001 Sep;82(9):1191-7. doi: 10.1053/apmr.2001.25077.
citation: Finnerup NB, Grydehoj J, Bing J, Johannesen IL, Biering-Sorensen F, Sindrup SH, Jensen TS. Levetiracetam in spinal cord injury pain: a randomized controlled trial. Spinal Cord. 2009 Dec;47(12):861-7. doi: 10.1038/sc.2009.55. Epub 2009 Jun 9.
citation: Widerstrom-Noga E, Felix ER, Adcock JP, Escalona M, Tibbett J. Multidimensional Neuropathic Pain Phenotypes after Spinal Cord Injury. J Neurotrauma. 2016 Mar 1;33(5):482-92. doi: 10.1089/neu.2015.4040. Epub 2015 Dec 2.
citation: Foell J, Andoh J, Bekrater-Bodmann R, Diers M, Fuchs X, Colloca L, Flor H. Peripheral origin of phantom limb pain: is it all resolved? Pain. 2014 Oct;155(10):2205-2206. doi: 10.1016/j.pain.2014.08.028. Epub 2014 Aug 29. No abstract available.
citation: Flor H. Maladaptive plasticity, memory for pain and phantom limb pain: review and suggestions for new therapies. Expert Rev Neurother. 2008 May;8(5):809-18. doi: 10.1586/14737175.8.5.809.
citation: Wrigley PJ, Press SR, Gustin SM, Macefield VG, Gandevia SC, Cousins MJ, Middleton JW, Henderson LA, Siddall PJ. Neuropathic pain and primary somatosensory cortex reorganization following spinal cord injury. Pain. 2009 Jan;141(1-2):52-9. doi: 10.1016/j.pain.2008.10.007. Epub 2008 Nov 21.
citation: Sarnthein J, Jeanmonod D. High thalamocortical theta coherence in patients with neurogenic pain. Neuroimage. 2008 Feb 15;39(4):1910-7. doi: 10.1016/j.neuroimage.2007.10.019. Epub 2007 Oct 25.
citation: Vuckovic A, Jajrees M, Purcell M, Berry H, Fraser M. Electroencephalographic Predictors of Neuropathic Pain in Subacute Spinal Cord Injury. J Pain. 2018 Nov;19(11):1256.e1-1256.e17. doi: 10.1016/j.jpain.2018.04.011. Epub 2018 May 8.
citation: Boord P, Siddall PJ, Tran Y, Herbert D, Middleton J, Craig A. Electroencephalographic slowing and reduced reactivity in neuropathic pain following spinal cord injury. Spinal Cord. 2008 Feb;46(2):118-23. doi: 10.1038/sj.sc.3102077. Epub 2007 May 15.
citation: Jensen MP, Sherlin LH, Gertz KJ, Braden AL, Kupper AE, Gianas A, Howe JD, Hakimian S. Brain EEG activity correlates of chronic pain in persons with spinal cord injury: clinical implications. Spinal Cord. 2013 Jan;51(1):55-8. doi: 10.1038/sc.2012.84. Epub 2012 Jul 17.
citation: Vuckovic A, Hasan MA, Fraser M, Conway BA, Nasseroleslami B, Allan DB. Dynamic oscillatory signatures of central neuropathic pain in spinal cord injury. J Pain. 2014 Jun;15(6):645-55. doi: 10.1016/j.jpain.2014.02.005. Epub 2014 Mar 1.
citation: Vuckovic A, Gallardo VJF, Jarjees M, Fraser M, Purcell M. Prediction of central neuropathic pain in spinal cord injury based on EEG classifier. Clin Neurophysiol. 2018 Aug;129(8):1605-1617. doi: 10.1016/j.clinph.2018.04.750. Epub 2018 May 23.
citation: Mussigmann T, Bardel B, Lefaucheur JP. Resting-state electroencephalography (EEG) biomarkers of chronic neuropathic pain. A systematic review. Neuroimage. 2022 Sep;258:119351. doi: 10.1016/j.neuroimage.2022.119351. Epub 2022 Jun 2.
citation: Loh E, Mirkowski M, Agudelo AR, Allison DJ, Benton B, Bryce TN, Guilcher S, Jeji T, Kras-Dupuis A, Kreutzwiser D, Lanizi O, Lee-Tai-Fuy G, Middleton JW, Moulin DE, O'Connell C, Orenczuk S, Potter P, Short C, Teasell R, Townson A, Widerstrom-Noga E, Wolfe DL, Xia N, Mehta S. The CanPain SCI clinical practice guidelines for rehabilitation management of neuropathic pain after spinal cord injury: 2021 update. Spinal Cord. 2022 Jun;60(6):548-566. doi: 10.1038/s41393-021-00744-z. Epub 2022 Feb 5.
citation: Guy SD, Mehta S, Casalino A, Cote I, Kras-Dupuis A, Moulin DE, Parrent AG, Potter P, Short C, Teasell R, Bradbury CL, Bryce TN, Craven BC, Finnerup NB, Harvey D, Hitzig SL, Lau B, Middleton JW, O'Connell C, Orenczuk S, Siddall PJ, Townson A, Truchon C, Widerstrom-Noga E, Wolfe D, Loh E. The CanPain SCI Clinical Practice Guidelines for Rehabilitation Management of Neuropathic Pain after Spinal Cord: Recommendations for treatment. Spinal Cord. 2016 Aug;54 Suppl 1:S14-23. doi: 10.1038/sc.2016.90.
citation: Jensen MP, Dworkin RH, Gammaitoni AR, Olaleye DO, Oleka N, Galer BS. Assessment of pain quality in chronic neuropathic and nociceptive pain clinical trials with the Neuropathic Pain Scale. J Pain. 2005 Feb;6(2):98-106. doi: 10.1016/j.jpain.2004.11.002.
citation: Cardenas DD, Jensen MP. Treatments for chronic pain in persons with spinal cord injury: A survey study. J Spinal Cord Med. 2006;29(2):109-17. doi: 10.1080/10790268.2006.11753864.
citation: Siddall PJ, Cousins MJ, Otte A, Griesing T, Chambers R, Murphy TK. Pregabalin in central neuropathic pain associated with spinal cord injury: a placebo-controlled trial. Neurology. 2006 Nov 28;67(10):1792-800. doi: 10.1212/01.wnl.0000244422.45278.ff.
citation: Widerstrom-Noga E, Anderson KD, Perez S, Martinez-Arizala A, Calle-Coule L, Fleming L. Barriers and Facilitators to Optimal Neuropathic Pain Management: SCI Consumer, Significant Other, and Health Care Provider Perspectives. Pain Med. 2020 Nov 1;21(11):2913-2924. doi: 10.1093/pm/pnaa058.
citation: Lofgren M, Norrbrink C. "But I know what works"--patients' experience of spinal cord injury neuropathic pain management. Disabil Rehabil. 2012;34(25):2139-47. doi: 10.3109/09638288.2012.676146. Epub 2012 Apr 18.
citation: Austin PD, Siddall PJ. Virtual reality for the treatment of neuropathic pain in people with spinal cord injuries: A scoping review. J Spinal Cord Med. 2021 Jan;44(1):8-18. doi: 10.1080/10790268.2019.1575554. Epub 2019 Feb 1.
citation: Gustin SM, Bolding M, Willoughby W, Anam M, Shum C, Rumble D, Mark VW, Mitchell L, Cowan RE, Richardson E, Richards S, Trost Z. Cortical Mechanisms Underlying Immersive Interactive Virtual Walking Treatment for Amelioration of Neuropathic Pain after Spinal Cord Injury: Findings from a Preliminary Investigation of Thalamic Inhibitory Function. J Clin Med. 2023 Sep 4;12(17):5743. doi: 10.3390/jcm12175743.
citation: Trost Z, Anam M, Seward J, Shum C, Rumble D, Sturgeon J, Mark V, Chen Y, Mitchell L, Cowan R, Perera R, Richardson E, Richards S, Gustin S. Immersive interactive virtual walking reduces neuropathic pain in spinal cord injury: findings from a preliminary investigation of feasibility and clinical efficacy. Pain. 2022 Feb 1;163(2):350-361. doi: 10.1097/j.pain.0000000000002348.
citation: Eick J, Richardson EJ. Cortical activation during visual illusory walking in persons with spinal cord injury: a pilot study. Arch Phys Med Rehabil. 2015 Apr;96(4):750-3. doi: 10.1016/j.apmr.2014.10.020. Epub 2014 Nov 15.
citation: Moseley LG. Using visual illusion to reduce at-level neuropathic pain in paraplegia. Pain. 2007 Aug;130(3):294-298. doi: 10.1016/j.pain.2007.01.007. Epub 2007 Mar 1.
citation: Nees TA, Finnerup NB, Blesch A, Weidner N. Neuropathic pain after spinal cord injury: the impact of sensorimotor activity. Pain. 2017 Mar;158(3):371-376. doi: 10.1097/j.pain.0000000000000783. No abstract available.
citation: Dugan EA, Sagen J. An Intensive Locomotor Training Paradigm Improves Neuropathic Pain following Spinal Cord Compression Injury in Rats. J Neurotrauma. 2015 May 1;32(9):622-32. doi: 10.1089/neu.2014.3692. Epub 2015 Mar 6.
citation: Dugan EA, Schachner B, Jergova S, Sagen J. Intensive Locomotor Training Provides Sustained Alleviation of Chronic Spinal Cord Injury-Associated Neuropathic Pain: A Two-Year Pre-Clinical Study. J Neurotrauma. 2021 Mar 15;38(6):789-802. doi: 10.1089/neu.2020.7378. Epub 2021 Jan 21.
citation: Hutchinson KJ, Gomez-Pinilla F, Crowe MJ, Ying Z, Basso DM. Three exercise paradigms differentially improve sensory recovery after spinal cord contusion in rats. Brain. 2004 Jun;127(Pt 6):1403-14. doi: 10.1093/brain/awh160. Epub 2004 Apr 6.
citation: Bryce TN, Richards JS, Bombardier CH, Dijkers MP, Fann JR, Brooks L, Chiodo A, Tate DG, Forchheimer M. Screening for neuropathic pain after spinal cord injury with the spinal cord injury pain instrument (SCIPI): a preliminary validation study. Spinal Cord. 2014 May;52(5):407-12. doi: 10.1038/sc.2014.21. Epub 2014 Mar 11.
citation: Bouhassira D, Attal N, Alchaar H, Boureau F, Brochet B, Bruxelle J, Cunin G, Fermanian J, Ginies P, Grun-Overdyking A, Jafari-Schluep H, Lanteri-Minet M, Laurent B, Mick G, Serrie A, Valade D, Vicaut E. Comparison of pain syndromes associated with nervous or somatic lesions and development of a new neuropathic pain diagnostic questionnaire (DN4). Pain. 2005 Mar;114(1-2):29-36. doi: 10.1016/j.pain.2004.12.010. Epub 2005 Jan 26.
citation: Bryce TN, Biering-Sorensen F, Finnerup NB, Cardenas DD, Defrin R, Lundeberg T, Norrbrink C, Richards JS, Siddall P, Stripling T, Treede RD, Waxman SG, Widerstrom-Noga E, Yezierski RP, Dijkers M. International spinal cord injury pain classification: part I. Background and description. March 6-7, 2009. Spinal Cord. 2012 Jun;50(6):413-7. doi: 10.1038/sc.2011.156. Epub 2011 Dec 20.
citation: Bates D, Maechler M, Bolker B, Walker S, Christensen RH, Singmann H, Dai B, Grothendieck G, Green P, Bolker MB. Package 'lme4'. convergence. 2015 Oct 6;12(1):2.
citation: IBM Corp. Released 2023. IBM SPSS Statistics for Windows, Version 29.0.2.0 Armonk, NY: IBM Corp